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Module Catalogue

for the Subject

Business Information Systems

as a Bachelor’s with 1 major with the degree "Bachelor of Science"

(180 ECTS credits)


Examination regulations version: 2021 Responsible: Faculty of Business Management and Economics



JMU Würzburg • generated 12-Mai-2023 • exam. reg. data record 82|277|-|-|H|2021


Contents

The subject is divided into 6

Learning Outcomes 7

Abbreviations used, Conventions, Notes, In accordance with 8

Compulsory Courses 9

Business Informatics 10

Business Informatics 11

E-Business 13

Data Management and Analysis 15

Integrated Business Processes 17

Business Management and Economics 19

Organization 20

Accounting 25

Managerial Accounting 26

Marketing 28

Supply, Production and Operations Management 30

Entrepreneurship 32

Methoden 34

Differential Calculus for Economics and Management 35

Linear Algebra for Economics and Management 36

Statistics 37

Econometrics 39

Computer Science 41

Algorithms and Data Structures Level One Course 42

Fundamentals of Programming 43

Practical Course in Programming for Business Informatics 45

Software Technology 46

Data Bases 48

Compulsory Electives 50

Business Informatics 51

IT-Law for Business Informatics 52

Forward and Reverse Business Engineering 54

Seminar: Information Systems 56

Web Programming 58

Advanced Web Engineering 60

E-Business Project 62

Business Intelligence 64

Planning and Decision Making in Business Information Systems 66

Primer in Data Science 68

Supply Chain Management 70

Seminar: Logistics & Supply Chain Management 72

Toyota Supply Chain Management 74

Information Economics - Software Project 76

Practical Course in Software for Students in Business Information Systems 77

Seminar 1 78

Seminar 2 80

Computer Information Systems 1 81

Computer Information Systems 2 82

Business Administration 83

Entrepreneurship, Competition and Strategy 84

Sales and Customer Relationship Management 86

Seminar: Marketing 88

International Marketing 90

Supply, Production and Logistics Management. Material Requirements Planning 92

Humanitarian Supply Chain Management 94

Seminar: Supply, Production and Logistics Management 96

Modern Approaches in Logistics 98

Foundations of transport logistics 100

Digital Science 1 102

Digital Science 2 104

Digital Science 3 106

Digital Science 4 108

Financial Accounting 110

International Accounting 112

Financial Statement Analysis and Valuation 114

Seminar: Financial Accounting 116

Investment and Finance 118

Decision Theory 120

Seminar: Investment and Finance 122

Introduction to Risk Management 124

Business Valuation between Financial Mathematics and Data on Capital Market 127

Business Taxation 1: An Introduction to Tax Law & Tax Planning 129

Business Taxation 2: The Taxation of Income in Germany 131

Business Taxation 3: Introduction to VAT 133

Selected Topics in Business Taxation 135

Seminar: Business Taxation 136

Human Resource Management 137

Seminar: Human Resource Management & Organizational Theory 139

Strategic and Innovation Management 140

Seminar: Research Seminar 142

Seminar: Business Simulation 144

Seminar: Business Plan 146

Managerial Accounting: cost-based decision-making and control 148

Sales Accounting & Management 150

Seminar: Managerial Accounting 152

Selected Topics in Business Management 1 153

Selected Topics in Business Management 2 154

Economics 155

Microeconomics 1 156

Microeconomics 2 158

Macroeconomics 1 160

Macroeconomics 2 162

Monetary Policy and Financial Markets 164

International Money & Finance 166

Applied Business Cycle Analysis and Forecasting 168

Seminar: Economic Policy 170

International Economics 172

Seminar: International Economics 174

Applied Regional and Urban Economics 176

Games and Strategies 178

Competition Policy 180

Economics of Regulation 182

Seminar: Competition and Strategy 184

Business Strategy for Information and Network Industries 185

Industrial Organization 187

Public Policy 189

Labour Economics 190

Seminar: Labour Economics 192

Seminar: Public Finance 194

Computational Economics 195

Practice of Data Analysis 197

Computerlab - Applied Econometrics 199

Seminar: Econometrics 201

Economic Principles of Risk Management 202

Insurance Markets 204

Economics of Information 206

Seminar: Decision Making and Incentive Design 208

Business Cycle Analysis 210

Seminar: Business cycles, corporate finance and asset markets 212

European Macroeconomics 214

Challenges of China’s Economic Rise 216

Introduction to Business Journalism 218

Crossmedia Storytelling in Business Communication 220

Seminar: Business Journalism and Business Communication 222

Managerial Practice Lectures 224

Economist Practice Lectures 226

Selected Topics in Economics 1 228

Selected Topics in Economics 2 229

Computer Science 230

Knowledge-based Systems 231

Data Mining 233

Operating Systems 235

Advanced Programming 237

Digital computer systems 239

Introduction into Human-Computer Interaction 241

Key Skills Area 242

General Key Skills 243

Subject-specific Key Skills 244

Internship (about 4 weeks, graded) 245

Internship (about 4 weeks, not graded) 246

Internship (about 8 weeks or more, graded) 247

Internship (about 8 weeks or more, not graded) 248

Student Teaching Assistant 1 249

Student Teaching Assistant 2 250

Bachelor Orientation Tutorial 251

Introduction to Scientific Work 252

Seminar: Cross-Cultural Management 1 - Introduction to Cross-Cultural Management 253

Cross-Cultural Management 2 - Leading Across Cultures 255

China: Business location and trading partner 257

India: Business location and trading partner 259

Intercultural Business Competence 260

Intercultural Management 1 262

Intercultural Management 2 264

Global Systems and Intercultural Competences - Economic Aspects of Globalization. An Introduction 266

Global Systems and Intercultural Competences - Economic Aspects of Globalization - Advanced Level 268

Economic and Business Ethics 270

Securities Management 272

DATEV - Introduction to DATEV-Software for Tax Accounting 274

SAP ERP Human Capital Management 276

Managerial Problem Solving 278

Basics of Supply Networks 280

Management of Supply Networks 282

Professional Apply 283

Professional Presentation 284

Management Case Studies 285

Managing interactive - Business Simulation Game 287

Project Management 289

Career planning and professional skills for students of Business and Economics 291

Modern Chinese Basics 1 293

Modern Chinese Basics 2 298

Modern Chinese Basics 3 303

Chinese Intensification 1 308

Chinese Intensification 2 313

Chinese technical language 1 318

Chinese Studies 320

General Management 1 321

General Management 2 322

General Management 3 323

General Management 4 324

Thesis Area 325

Bachelor Thesis Business Information Systems 326

The subject is divided into

section / sub-section

ECTS credits

starting

page

Compulsory Courses

105

9

Business Informatics

20

10

Business Management and Economics

30

19

Methoden

20

34

Computer Science

35

41

Compulsory Electives

45

50

Business Informatics

min. 20

51

Business Administration

max. 25

83

Economics

max. 25

155

Computer Science

max. 25

230

Key Skills Area

20

242

General Key Skills

5

243

Subject-specific Key Skills

15

244

Thesis Area

10

325


Learning Outcomes

German contents and learning outcome available but not translated yet.

Der Bachelorstudiengang Wirtschaftsinformatik wird von der Wirtschaftswissenschaftlichen Fakultät der JMU als grundlagenorientierter Studiengang mit dem Abschluss „Bachelor of Science" (B. Sc.) im Rahmen eines konsekutiven Bachelor- und Masterstudiums angeboten. Der Grad des Bachelor of Science stellt einen ersten berufsqualifizierenden Abschluss dar.

Das Ziel der Ausbildung in diesem Studiengang ist es, den Studierenden Kenntnisse in den wichtigsten Teilgebieten der Wirtschaftswissenschaft sowie der Informationsverarbeitung zu vermitteln und eine ana-lytische Denkweise zu schulen. Dazu erhalten die Studierenden einen umfassenden Überblick über die verschiedenen Disziplinen der Wirtschaftsinformatik, der Wirtschaftswissenschaft und der Informatik, sowie die zugrundeliegenden mathematischen und theoretischen Methoden und Sichtweisen und ler-nen, Aufgaben der Planung, Gestaltung und Entwicklung betrieblicher Informationsverarbeitung selbstständig zu lösen.

In diesem Sinne werden die Grundlagen, die in einer globalisierten Welt eng ineinandergreifen, erlernt und ein fundiertes Basiswissen erworben. Dabei bildet die Integration ethischer und sozialer Aspekte die Fähigkeit der Studierenden, ökonomische Fragestellungen ethisch verantwortungsvoll zu beurteilen und gesellschaftliche oder ökologische Folgen abzuschätzen.

Im Studienverlauf und während der von der Fakultät geförderten Auslandsaufenthalte erwerben die Studierenden Schlüsselqualifikationen zur Förderung von Team- und Kommunikationsfähigkeit, interkultu-reller Sensibilität und Selbstorganisation.

Die Studierenden können zentrale ökonomische und informatische Fragestellungen und deren Analyse erklären. Durch diese Kenntnisse treten Sie als Bindeglied zwischen der reinen Informations- und Kom-munikationstechnologie auf der einen und der Wirtschaftswissenschaft auf der anderen Seite auf, was sie dazu befähigt, übergreifende Fragestellungen problemorientiert zu analysieren und geeignete Lösungs-vorschläge zu entwickeln und umzusetzen. Die Studierenden erlangen die Fähigkeit, die später in der be-ruflichen Praxis an sie herangetragenen Aufgabenstellungen selbstständig zu bearbeiten. Durch die Ausbildung dieser Fähigkeiten erwerben sie zudem die für ein sich gegebenenfalls anschließendes postgra-duales Studium, insbesondere im Rahmen eines konsekutiven Master-Studiums, erforderlichen Grund-kenntnisse.

Durch die Abschlussarbeit zeigen die Studierenden, dass sie ihr Fach in angemessener Weise beherrschen und in einem thematisch und zeitlich eng begrenzten Umfang in der Lage sind, Sachverhalte und Fragestellungen der Wirtschaftsinformatik nach wissenschaftlichen Maßstäben unter Anleitung eigenständig zu beurteilen und zu bearbeiten.

Die erfolgreich abgelegte Bachelor-Prüfung berechtigt nach Maßgabe der FSB der einschlägigen Master¬ Studiengänge der JMU in ihren jeweils geltenden Fassungen zur Aufnahme eines Master-Studiums.


Abbreviations used

Course types: E = field trip, K = colloquium, O = conversatorium, P = placement/lab course, R = project, S = seminar, T = tutorial, Ü = exercise, V = lecture

Term: SS = summer semester, WS = winter semester

Methods of grading: NUM = numerical grade, B/NB = (not) successfully completed

Regulations: (L)ASPO = general academic and examination regulations (for teaching-degree programmes), FSB = subject-specific provisions, SFB = list of modules

Other: A = thesis, LV = course(s), PL = assessment(s), TN = participants, VL = prerequisite(s)


Conventions

Unless otherwise stated, courses and assessments will be held in German, assessments will be offered every semester and modules are not creditable for bonus.


Notes

Should there be the option to choose between several methods of assessment, the lecturer will agree with the module coordinator on the method of assessment to be used in the current semester by two weeks after the start of the course at the latest and will communicate this in the customary manner.

Should the module comprise more than one graded assessment, all assessments will be equally weighted, unless otherwise stated below.

Should the assessment comprise several individual assessments, successful completion of the module will require successful completion of all individual assessments.


In accordance with

the general regulations governing the degree subject described in this module catalogue:

ASPO2015

associated official publications (FSB (subject-specific provisions)/SFB (list of modules)):

28-Apr-2021 (2021-48)

31-Jan-2023 (2022-85)

This module handbook seeks to render, as accurately as possible, the data that is of statutory relevance according to the examination regulations of the degree subject. However, only the FSB (subject-spe-cific provisions) and SFB (list of modules) in their officially published versions shall be legally binding. In the case of doubt, the provisions on, in particular, module assessments specified in the FSB/SFB shall prevail.


Compulsory Courses

(105 ECTS credits)


Business Informatics

(20 ECTS credits)


Module title

Abbreviation

Business Informatics

12-EWiinf-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This course offers an introduction to the essential aspects of business information systems.


Outline of syllabus:

  1. Integration of IT systems

  2. From data processing to information processing

  3. eCommerce and eGovernment

  4. Functionality of IT technology

  5. Application development principles

  6. Intercommunication


Reading:

Thome: Grundzüge der Wirtschaftsinformatik.

Intended learning outcomes

The course "Einführung in die Wirtschaftsinformatik" communicates

  1. an overview of the different task fields of the business informations systems discipline;

  2. an understanding for recent developments in the discipline and related technologies.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

E-Business

12-Ebus-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Information Systems Engineering

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

E-business is a comprehensive, digital processing of business transactions between private and public enterprises as well as institutions and their clients on global public and private networks such as the internet. Precisely because euphoria for e-business has waned considerably in recent years, a lot of emphasis is now being placed on introducing such solutions in a user-oriented way. This lecture will first discuss the supporting economic theories and will then describe and analyse individual solutions such as e-procurement, e-shop, e-marketplace and e-community in detail.

Intended learning outcomes

The module provides students with knowledge about:

  1. E-Procurement

  2. E-Shop

  3. E-Marketplace

  4. E-Community

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 15 pages) or

  3. term paper (approx. 10 pages) and presentation (approx. 10 minutes), weighted 2:1 or

  4. oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 13 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Master's degree (1 major) Media Entertainment (2022)

Master's degree (1 major) Psychology of digital media (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Data Management and Analysis

12-DM-F-202-m01

Module coordinator

Module offered by

Holder of the Chair of Business Analytics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module teaches on the one hand basics and concepts of modeling data and querying and manipulating databases. Additionally, fundamentals of data analysis as well as data analysis processes are introduced.


Focal points are:

  • Fundamentals and application of semantic data modelling

  • Fundamentals and application of the relational data model

  • Fundamentals and application of data query languages

  • Hypothesis-driven and model-building data analysis

  • Data analysis processes and their comparison

  • Supervised and unsupervised learning processes

Intended learning outcomes

Upon completion of the module students are able

  • to design good conceptual and logical data models;

  • to transform conceptual data models into physical data schemas;

  • to formulate complex database queries;

  • to design different applications with databases

  • perform and interpret hypothesis testing on real data

  • understand the basics of supervised and unsupervised machine learning

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. term paper (approx. 15 pages) or

  3. term paper (approx. 10 pages) and presentation (approx. 10 minutes); (weighted 2:1) or

  4. oral examination (groups of up to 3; approx 10 minutes per candidate)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

50 places.

  1. No restrictions with regard to available places for Bachelor's students of Wirtschaftsinformatik (Business Information Systems) (BSc with 180 ECTS credits).

  2. Additional places will be allocated to students of other subjects provided there is enough capacity. These additional places will be allocated by lot among all applicants irrespective of their subjects.

  3. Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (4) A waiting list will be maintained and places re-allocated by lot as they become available.

  4. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Module title

Abbreviation

Integrated Business Processes

12-GP-G-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course is aimed at students of Wirtschaftsinformatik (Business Information Systems) and Wirtschaftswissenschaft (Business Management and Economics) interested in the topic. The course is divided up into two parts. In the theoretical part, students will acquire the necessary theoretical knowledge that will serve as a basis for the practical part. The practical exercise will present students with an opportunity to apply their newly acquired knowledge by working with an SAP S4/HANA on case studies on the model company Almika. In this context, the human resources, purchasing, sales, service, project management and finance departments will be dealt with.

The course will introduce students to business processes of an ERP system (Enterprise Resource Planning) using the example of SAP S/4HANA. In addition to the basic principles, students will also become familiar with the processes and functionalities.

Intended learning outcomes

After completing the course, the students will be able to

  1. reflect technical principles and operational models of ERP systems,

  2. understand the functionality of ERP systems and

  3. perform and understand business processes within the ERP system SAP Business ByDesign.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) term paper (approx. 10 to 15 pages) and presentation (approx. 10 minutes), weighted 2:1

creditable for bonus

Allocation of places

15 places. (1) The number of places is not restricted for students of the Bachelor's degree subject Wirtschaftsinformatik (Business Information Systems) (BSc with 180 ECTS credits). (2) Additional places will be allocated to students of other subjects provided there is enough capacity. These additional places will be allocated by lot

among all applicants irrespective of their subjects. (3) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (4) A waiting list will be maintained and places re-alloca-

ted by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--


Module appears in

Bachelor' degree (1 major) Computer Science (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Master's degree (1 major) Media Communication (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Master's degree (1 major) Media Communication (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Computer Science (2017) Master's degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Computer Science (2019)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Master's degree (1 major) Media Communication (2019)

Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Business Management and Economics

(30 ECTS credits)


Module title

Abbreviation

Organization

12-EBWL-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Human Resource Management and Organisation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course will introduce students to relevant subject areas of business administration. Students will acquire an overview of the different perspectives and main points of view from which a theoretical examination of business enterprise may take place. The course will focus on what companies or other organisations are, how they behave and in what form they are organised. For this purpose, a study will be made of the economic subject's decision-making behaviour.

Reading list to be provided during lecture.

Intended learning outcomes

The aim of the lectures is to familiarise the students with the basic problem issues and perspectives within the field of business administration.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

Teaching cycle: every year, winter semester

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013) Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)

Bachelor's degree (1 major, 1 minor) Pedagogy (2013)


Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Nanostructure Technology (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015) Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 21 / 326


Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016) Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016)

Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 22 / 326


Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Modern China (2017) Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Games Engineering (2017)

Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021) Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021)

Bachelor's degree (1 major, 1 minor) Theological Studies (2021) Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 23 / 326


Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Master's degree (1 major) Media Entertainment (2022)

Master's degree (1 major) Psychology of digital media (2022) exchange program Business Management and Economics (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Module title

Abbreviation

Accounting

12-ExtUR-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course offers an introduction to the fundamentals of financial accounting, including the technique of double-entry book-keeping as well as the fundamentals of recognition, valuation and presentation of assets, liabilities and equity according to German commercial law.

Intended learning outcomes

Students acquire a basic understanding of the fundamentals of financial accounting. They are able to arrange, reproduce and apply this knowledge, i.e. they are able to solve simple accounting problems.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Managerial Accounting

12-IntUR-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This course offers an introduction to aims and methods of managerial accounting (cost accounting).


Outline of syllabus:

  1. Managerial accounting and financial accounting

  2. Managerial accounting: basic terms

  3. Different types of costs

  4. Cost centre accounting based on total costs

  5. Job costing based on total costs

  6. Cost centre accounting and job costing based on direct/variable costs

  7. Budgeting and cost-variance analysis

  8. Cost-volume-profit analysis

  9. Cost information and operating decisions


Reading:

Coenenberg/Fischer/Günther: Kostenrechnung und Kostenanalyse, Stuttgart. Friedl/Hofmann/Pedell: Kostenrechnung. Eine entscheidungsorientierte Einführung.

(most recent editions)

Intended learning outcomes

After completing the course "Management Accounting and Control", the students will be able to

  1. set out the responsibilities of the company's internal accounting and control;

  2. define the central concepts of internal enterprise computing restriction and control and assign case studies the terms;

  3. apply the basic methods of internal corporate accounting and control on a full and cost base to idealized case studies of medium difficulty that calculate relevant costs and benefits and take on this basis a reasoned deci-

sion.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Marketing

12-Mark-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Marketing

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description

In this module, students will acquire the theoretical foundations of market-oriented management.


Content:

With the stakeholder approach as a starting point, the basic design of market-oriented management will be explained and exemplified in the 5 classical steps: situation analysis, objectives, strategies, tools and controlling. The course will focus not only on the behavioural approaches of consumer behaviour but also on industrial purchasing behaviour. A case study introducing students to the fundamental principles of market research based on a conjoint analysis will provide students with deeper insights into the topic.


Outline of syllabus:

  1. Marketing, entrepreneurship and business management

  2. Explanations of consumer behaviour

  3. Fundamentals of market research

  4. Strategic marketing; marketing tools

  5. Corporate social responsibility versus creating shared value


Reading:

Foscht, T. / Swoboda, B.: Käuferverhalten: Grundlagen -- Perspektiven -- Anwendungen, 4th revised and exp. ed., Wiesbaden 2011.

Homburg, Ch.: Grundlagen des Marketingmanagements: Einführung in Strategie, Instrumente, Umsetzung und Unternehmensführung, 4th revised and exp. ed., Wiesbaden 2012.

Homburg, Ch.: Grundlagen des Marketingmanagements: Einführung in Strategie, Instrumente, Umsetzung und Unternehmensführung, 3rd ed., Wiesbaden, 2012a.

Kroeber-Riel, W. /Weinberg, P.: Konsumentenverhalten, 9th ed., Munich 2009.

Meffert, H. / Burman, Ch / Kirchgeorg, M.: Marketing -- Grundlagen marktorientierter Unternehmensführung: Kon-zepte -- Instrumente -- Praxisbeispiele, 11th revised and exp. ed., Wiesbaden 2012.

Meffert, H. / Burman, Ch / Becker, Ch.: Internationales Marketing-Management -- Ein markenorientierter Ansatz, 4th ed., Stuttgart 2010.

Meyer, M.: Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unternehmung, Wiesbaden 1995.

Porter, M. E.: Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frankfurt / New York 2014. (Original: Porter, M.: Competitive Advantage, New York 1985.)

Simon, H. / Fassnacht, M.: Preismanagement, Strategie -- Analyse -- Entscheidung -- Umsetzung, 3rd ed., Wies-

baden 2009.

Intended learning outcomes

The students have a basic understanding of business management and are able to classify the knowledge systematically. In addition, they can use the acquired knowledge solve and identify the conventional problem fields of business management.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)


Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Supply, Production and Operations Management

12-BPL-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course will provide students with an overview of fundamental processes in procurement, production and logistics and the related corporate functions as well as a model-based introduction to related planning procedures.

Intended learning outcomes

The students will be able to describe and discuss the objectives and major processes in the domains of corporate procurement, production and logistics as well as their interdependencies. Furthermore, they are capable of developing and applying basic planning models in these fields.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Economathematics (2023)


Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Entrepreneurship

12-EPS-212-m01

Module coordinator

Module offered by

holder of the Chair of Entrepreneurship and Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

The course introduces students to the basics of entrepreneurial self-employment. In addition to discussing theoretical concepts covering the definition, creation and performance of new ventures, the course will also discuss methods and instruments for a potential entrepreneurial career. Several content areas of start-up planning are being covered during the course of the lecture including team compilation, business model creation and financing.


Contents of the course:

  1. Introduction to entrepreneurship

  2. Human resources in start-ups

  3. Opportunity analysis

  4. Business modelling

  5. Entrepreneurship in the digital industry

  6. Business planning

  7. Finance

  8. Marketing in start-ups

Intended learning outcomes

After completing the module "Entrepreneurship", the students should be able to

  1. describe and problematize the concept of entrepreneurship and the entrepreneurial perspective;

  2. describe and analyze the entrepreneurial process, its drivers, characteristics and context;

  3. apply theories within the entrepreneurship field to real life situations;

  4. take initiatives and independently develop a business idea and use knowledge gained from earlier courses in business administration in order to develop this idea in a business plan sketch;

  5. plan human resources and marketing in a start-up.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (as individual or group work; approx. 10 pages per person) or

  3. oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Master's degree (1 major) Media Entertainment (2022) Master's degree (1 major) Psychology of digital media (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Methoden

(20 ECTS credits)


Module title

Abbreviation

Differential Calculus for Economics and Management

10-M-MWW1-212-m01

Module coordinator

Module offered by

Dean of Studies Mathematik (Mathematics)

Institute of Mathematics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Theory of real-valued functions in one or two variables.

Intended learning outcomes

The student learns the basic mathematical tools in the field of analysis, and is able to apply these methods to simple problems in economical modelling.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 120 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) exchange program Business Management and Economics (2022) exchange program Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Linear Algebra for Economics and Management

10-M-MWW2-212-m01

Module coordinator

Module offered by

Dean of Studies Mathematik (Mathematics)

Institute of Mathematics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Theory of real-valued functions in several variables and basics in linear algebra.

Intended learning outcomes

The student deepens his/her knowledge in analysis and learns basic linear algebra. He/She is able to apply these methods to simple problems in economical modelling.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 120 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) exchange program Business Management and Economics (2022) exchange program Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Statistics

12-Stat-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Econometrics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This module deals with the basic terms and concepts of descriptive statistics, indices and probability calculus. It introduces students to common frequency distributions and fundamental distributional characteristics of one-dimensional data as well as basic concepts and methodology necessary for the description and interpretation of multi-dimensional data. In addition, interpretation and calculation with indices as well as fundamental terms of probability calculus are discussed in the second half of the course.


Outline of syllabus:

  1. Basic terms in statistics

  2. Frequency distributions

  3. Distributional characteristics

  4. Multi-dimensional data

  5. Index calculus

  6. Fundamental probability calculus

  7. Random variables and distributions


Reading:

Assenmacher, W.: Deskriptive Statistik, Springer. Bamberg, G., Baur, F.: Statistik, Oldenbourg.

Bohley, P.: Statistik, Oldenbourg.

Hartung, J., Elpelt, B., Klösner, K.-H.: Statistik, Oldenbourg. Hippmann, H.-D.: Statistik, Schäffer-Poeschel.

Leiner, B.: Einführung in die Statistik.

Litz, H.-P.: Statistische Methoden in den Wirtschafts- und Sozialwissenschaften, Oldenbourg. Mosler, K., Schmid, F.: Beschreibende Statistik und Wirtschaftsstatistik, Springer.

Schaich, E., Köhle, B., Hartung, J.: Statistik I für Volkswirte, Betriebswirte und Soziologen, Verlag Franz Vahlen.

Schira, J.: Statistische Methoden der VWL und BWL, Pearson Studium.

Intended learning outcomes

Students acquire knowledge of the fundamental terms and concepts of descriptive statistics. In particular, they become familiar with the application and interpretation of common visual and formal tools for descriptive data analysis while simultaneously learning how to competently deal with economic and/or statistical data. On the visual side, this includes knowledge of the construction and interpretation of histograms, bar plots, pie charts, and empirical distribution functions, while on the formal side students learn how to deal with basic distributional characteristics and correlation measures. Additionally, students are familiarized with index calculus and interpretation (in particular the Laspeyres and the Paasche price index) as well as with the most fundamental concepts and terms of probability calculus.

The competences acquired in this course serve as a prerequisite for "Introductory Statistics II".

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (60 to 90 minutes)


Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Econometrics

12-QWF-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Econometrics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This module deals with random variables and their statistical distributions as well as with the basic terms and methods of inferential statistics. Some of the most famous distributions such as the normal, binomial, poisson or the exponential distribution are introduced in the first half of the course. The second half deals with the fundamental concepts and techniques used in inferential statistics, including interval estimation and the construction, application and interpretation of hypothesis tests. Additionally, an introduction to multiple regression analysis is given towards the end of the course.

The knowledge and skills acquired in this course serve as a prerequisite for the course "Computerprakti-

kum" ("Computer Lab in Regression Analysis") and the subsequent Master's course "Ökonometrie I" ("Econometrics I").


Outline of syllabus:

  1. Random variables and their distributions

  2. Distribution parameters

  3. On the importance of the normal distribution

  4. Central limit theorems

  5. Inferential statistics

  6. Interval estimation

  7. Hypothesis testing

  8. Regression analysis

Intended learning outcomes

Students acquire a basic knowledge of the techniques necessary for the analysis of random events. They will be familiar with different distributions and their respective parameters. Apart from basic estimation methods for these unknown parameters, students learn how to construct and interpret common statistical tests and are able to apply these to specific economic or business questions. Additionally, students acquire a basic understanding of ordinary least square (OLS), enabling them to read simple scientific papers and to apply these tools to scientific questions.


The competences acquired in this course serve as a prerequisite for the course "Computer Lab in Regression Analysis" and the subsequent Master's course "Econometrics I".

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (60 to 120 minutes)

Allocation of places

--

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Computer Science

(35 ECTS credits)


Module title

Abbreviation

Algorithms and Data Structures Level One Course

10-I-GADS-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Design and analysis of algorithms, recursion vs. iteration, sort and search methods, data structures, abstract data types, lists, trees, graphs, basic graph algorithms, programming in Java.

Intended learning outcomes

The students are able to independently design algorithms as well as to precisely describe and analyse them. The students are familiar with the basic paradigms of the design of algorithms and are able to apply them in practical programs. The students are able to estimate the run-time behaviour of algorithms and to prove their correctness.

Courses (type, number of weekly contact hours, language — if other than German)

V (4) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes) or oral examination of one candidate each (approx. 20 minutes) or oral examination in groups of 2 candidates (approx. 15 minutes per candidate)

creditable for bonus

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor's degree (1 major, 1 minor) Digital Humanities (Minor, 2015) Bachelor's degree (2 majors) Digital Humanities (2015)

First state examination for the teaching degree Realschule Computer Science (2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (1 major, 1 minor) Digital Humanities (Minor, 2018) Bachelor's degree (2 majors) Digital Humanities (2018)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Fundamentals of Programming

10-I-GdP-172-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science II

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Data types, control structures, foundations of procedural programming, selected topics of C, introduction to object orientation in Java, selected topics of C++, further Java concepts, digression: scripting languages.

Intended learning outcomes

The students possess a fundamental knowledge about programming languages (in particular Java, C and C++) and are able to independently develop average to high level Java programs.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Aerospace Computer Science (2017) Bachelor' degree (1 major) Computer Science (2017)

Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Aerospace Computer Science (2020) Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Mathematical Data Science (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023)


Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Practical Course in Programming for Business Informatics

10-I-PPWI-202-m01

Module coordinator

Module offered by

--

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

P (6)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

practical examination (programming exercises, approx. 240 hours) and written examination (approx. 60 to 120 minutes); If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Software Technology

10-I-ST-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Object-oriented software development with UML, development of graphical user interfaces, foundations of databases and object-relational mapping, foundations of web programming (HTML, XML), software development processes, unified process, agile software development, project management, quality assurance.

Intended learning outcomes

The students possess a fundamental theoretical and practical knowledge on the design and development of software systems.

Courses (type, number of weekly contact hours, language — if other than German)

V (4) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

creditable for bonus

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

§ 49 I Nr. 1b

§ 69 I Nr. 1b

Module appears in

Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Economathematics (2015) Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Computational Mathematics (2015)

Bachelor' degree (1 major) Aerospace Computer Science (2015)

First state examination for the teaching degree Realschule Computer Science (2015) First state examination for the teaching degree Gymnasium Computer Science (2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Aerospace Computer Science (2017)


Bachelor' degree (1 major) Economathematics (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019) Module studies (Bachelor) Orientierungsstudien (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)


Module title

Abbreviation

Data Bases

10-I-DB-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Relational algebra and complex SQL statements; database planning and normal forms; transaction management.

Intended learning outcomes

The students possess knowledge about database modelling and queries in SQL as well as transactions.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

§ 49 I Nr. 1b

§ 69 I Nr. 1b

Module appears in

Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Aerospace Computer Science (2015) Bachelor' degree (1 major) Functional Materials (2015)

First state examination for the teaching degree Realschule Computer Science (2015) First state examination for the teaching degree Gymnasium Computer Science (2015) Master's degree (1 major) Physics (2016)

Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Aerospace Computer Science (2017)


Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Mathematical Data Science (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Compulsory Electives

(45 ECTS credits)


Business Informatics

(min. 20 ECTS credits)


Module title

Abbreviation

IT-Law for Business Informatics

12-ITRW-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Data protection law:


The course provides a systematic overview of key aspects of German and European data protection laws specifically in relation to IT and internet issues. The course will use numerous practical examples and exercises from the areas of IT and internet to illustrate the respective contents.


Outline of syllabus:

  • Principles and historical development of data protection law

  • Legal goals of data protection law

  • Statutory powers for data use

  • Privacy policy regarding IT and internet issues

  • Privacy regarding IT outsourcing

  • Privacy and marketing

  • Consequences of data breaches

  • Rights of the person concerned

  • Employee data protection

  • Outlook on the forthcoming EU Data Protection Regulation

Media law:

The course will first address the classification of the two areas of law in the legal system. In the section on media law, the course will focus on the basic principles of the right to report (press freedom, moral rights) and internet law. In addition, the course will discuss the basic principles of copyright with its manifestations in IT law. The section on trademark law will include a comprehensive overview of the law of intellectual property (patents, design rights, competition law aspects). This section will focus on the core area of trademark law: registration of trademarks, delineation of brands and trademarks, protection of trade marks, infringement of trademarks and law enforcement. The course will mainly work with cases.

Intended learning outcomes

Data Protection Law:

After completing the course, the students will be able to

  1. provide an overview of key aspects of the german and european data protection lay with practical examples. Media Law:

After completing the course, the students will be able to

  1. classify the two areas of law in the legal system,

  2. reflect the principles of the law of reporting (press freedom, moral rights) and Internet Law,

  3. constitute the basics of copyright and its manifestations in IT Law and

  4. give an overall view of the law of intellectual property (patents, design rights, competition law aspects).


Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Forward and Reverse Business Engineering

12-FRBE-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

"Business Engineering" refers to the method and model-based design theory for companies in the information age. "Forward" refers to design methods (such as situation analysis, requirements analysis and business process modelling) that help implement a new solution. "Reverse" refers to approaches (such as the use and process analysis) that make it possible to improve or re-design existing structures and processes. Market requirements and technological innovation potential are typical reasons for the continuous transformation of a company. The resulting change needs to be implemented into the organisational structure, business processes and information systems.

The course traces the implementation cycle of enterprise software from the point of view of a member of a project team. In addition to acquainting students with the theoretical basis of adaptation, the course will also discuss examples from practical projects.

Intended learning outcomes

The students know in detail the process of adaptation of business software libraries. They master the methods of Forward Engineering (such as situation analysis, requirement analysis, process modeling and business blueprint) and Reverse Engineering (Reverse Business Engineering) and their implementation in tools.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) term paper (approx. 10 to 15 pages) and presentation (approx. 10 minutes), weighted 2:1

creditable for bonus

Allocation of places

50 places. Should the number of applications exceed the number of available places, places will be allocated as follows: (1) Bachelor's students of Wirtschaftsinformatik (Business Information Systems) (BSc with 180 ECTS credits) will be given preferential consideration. (2) The remaining places will be allocated to students of other subjects. (3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group. (4) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (5) A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--


Module appears in

Bachelor' degree (1 major) Computer Science (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Master's degree (1 major) Media Communication (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Master's degree (1 major) Media Communication (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Computer Science (2017) Master's degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Computer Science (2019)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Master's degree (1 major) Media Communication (2019)

Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Information Systems

12-Wiinf-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the fields of information systems and enterprise systems.


Reading:

will vary according to topic

Intended learning outcomes

After completing the course "Wirtschaftsinformatik-Seminar", students will be able to

  1. understand the fundamentals of scientific literature reviews;

  2. integrate elaborated content in a scientific thesis;

  3. create presentations independently.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 20 pages) and presentation (approx. 20 minutes), (weighted 2:1)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

15 places. Should the number of applications exceed the number of available places, places will be allocated as follows: (1) Bachelor's students of Wirtschaftsinformatik (Business Information Systems) (BSc with 180 ECTS credits) will be given preferential consideration. (2) The remaining places will be allocated to students of other subjects. (3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group. (4) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (5) A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Web Programming

12-WebP-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The lecture "Web Programming" will introduce students to the basic principles of internet-based programming. After a general introduction to web technologies (one unit), the lecture will discuss the markup language HTML and the style sheet language CSS (four units). The basics of the scripting language PHP will be discussed in another four units.

Intended learning outcomes

The module provides students with knowledge of:

  1. HTML, CSS, PHP

  2. Databases

  3. Database-based Internet applications

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) completion of programming exercises (approx. 20 hours) and written examination (approx. 60 minutes), weighted 1:1

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 58 / 326


Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 59 / 326


Module title

Abbreviation

Advanced Web Engineering

12-AWE-152-m01

Module coordinator

Module offered by

Holder of the Chair of Information Systems Engineering

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module provides an introduction to the development of web-based applications based on current development systems, software components and frameworks.

Intended learning outcomes

  • Understand the technological foundations of web applications

  • Designing the architecture and data model of an application system

  • Implementing with the help of SW components and frameworks

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) completion of programming exercises (approx. 20 hours) and written examination (approx. 60 minutes), weighted 1:1

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 60 / 326


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 61 / 326


Module title

Abbreviation

E-Business Project

12-EBP-152-m01

Module coordinator

Module offered by

Holder of the Chair of Information Systems Engineering

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire the technical, organisational and social skills necessary for a real e-busi-ness. The principal distinguishing feature of this course is its high practical relevance. The project work - evolving from the conceptual design to status presentations and final report - will be completed in small groups.

Intended learning outcomes

  • Understand challenges of real e-business organisations

  • Apply the acquired knowledge to solve a specific, real problem

  • Present the developed results

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) term paper (approx. 10 to 20 pages) and presentation (approx. 15 minutes), weighted 2:1 or d) entirely or partly computerised written examination (approx. 60 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 62 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Business Intelligence

12-BIF-211-m01

Module coordinator

Module offered by

Holder of the Chair of Information Systems Engineering

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Technologies and methods of "Business Intelligence" are aimed at supporting managerial decision-making processes by analyzing and presenting large amounts of data. The module provides an overview of the corresponding analytical information systems, their technical architecture and areas of application. In the practical exercises, the concepts taught are practically demonstrated and applied by the example of a state-of-the-art BI software suite.

Intended learning outcomes

  • Understand the technological foundations of data warehouses and BI tools.

  • Analyse and design conceptual models for analytical information systems.

  • Apply real-world BI software products to analyse large structured data sets

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (approx. 20 pages) or

  3. Term paper (10 to 20 pages) and presentation (approx. 15 minutes), weighted 2:1 or

  4. entirely or partly computerised written examination (apprx. 60 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021)


Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Planning and Decision Making in Business Information Systems

12-PEBI-211-m01

Module coordinator

Module offered by

Holder of the Chair of Business Analytics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Quantitative methods form a central basis for business planning and decision-making. From the information systems perspective, these methods must be integrated into IT systems and processes. The lecture presents fundamental concepts and methods from the areas of decision theory and analysis, mathematical optimization and discrete Markov chains. The methods are applied in the exercise on the basis of examples and solved computer-aided.

Intended learning outcomes

  • Normative and empirical decision theory

  • Fundamentals of linear programming

  • Sensitivity analysis

  • Discrete Optimization

  • Discrete Markov chains

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. oral examination of one candidate each (approx. 20 to 30 minutes)

  3. exercises (approx. 6 pages)

Language of assessment: German and/or English

Creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 66 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Module title

Abbreviation

Primer in Data Science

12-PDS-211-m01

Module coordinator

Module offered by

Holder of the Chair of Business Analytics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Data science is concerned with extracting knowledge and valuable insights from data assets. It is an emerging field that is currently in high demand in both academia and industry. This course provides a practical introduction to the full spectrum of data science techniques spanning data acquisition and processing, data visualization and presentation, creation and evaluation of machine learning models.

The course focuses on the practical aspects of data science, with emphasis on the implementation and use of the above techniques. Students will complete programming homework assignments that emphasize practical understanding of the methods described in the course.

Intended learning outcomes

Topics covered include:

  • Data acquisition and processing

  • graph and network models

  • text analysis

  • working with geospatial data

  • Usage of machine learning models (supervised and unsupervised)

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) oral examination of one candidate each (approx. 20 to 30 minutes) or c) exercises (approx. 6 pages)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Supply Chain Management

12-SCM-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Logistics and Quantitative Methods in Business Administration

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The seminar "Supply Chain Management" will introduce students to tactical and operational planning problems of supply chain management. It will discuss the wording of these as formal models and, with the help of a continuous case study, will acquaint students with the implementation of these models in SAP APO.

Intended learning outcomes

After completing this seminar students can

  1. apply selected and applied quantitative models for procurement, production, sales and supply chain management;

  2. face the practical problems when using real data to feed models;

  3. understand the challenges to reach a coordinated decision in a company.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 15 pages) or

  3. term paper (approx. 10 to 15 pages) and presentation (approx. 10 minutes); (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 70 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)



Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 71 / 326


Module title

Abbreviation

Seminar: Logistics & Supply Chain Management

12-LSCM-212-m01

Module coordinator

Module offered by

holder of the Chair of Logistics and Quantitative Methods in Business Administration

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this module, students will learn, on a case-by-case basis, how companies successfully implemented quantitative planning methods to optimise their processes in logistics and supply chain management.

Intended learning outcomes

After completing this module students can

  1. understand mathematical models to solve practical problems in logistics and supply chain management,

  2. evaluate and critique the results of such models, and

  3. understand, describe, and evaluate the limits of such models.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 10 to 15 pages) and presentation (approx. 10 minutes), (weighted 2:1) Language of assessment: German and/or English

Allocation of places

20 places. Should the number of applications exceed the number of available places, places will be allocated as follows: (1) Applicants who have already achieved a total of 90 ECTS credits or more will be given preferential consideration. (2) When places are allocated in accordance with (1) and the number of applications exceeds the

number of available places, places will be allocated according to the average grade of assessments taken so far;

among applicants with the same average grade, places will be allocated by lot.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Economathematics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 72 / 326


Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Toyota Supply Chain Management

12-MDM-212-m01

Module coordinator

Module offered by

holder of the Chair of Logistics and Quantitative Methods in Business Administration

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Toyota is still considered to be a pioneer in the field of automobile production although it has recently had to cope with difficulties (e. g. recalls, production shortfalls caused by natural disasters) and had lost its dominant position in the automotive market to General Motors and Volkswagen–at least temporarily. The development of concepts, such as Lean Manufacturing, Total Quality Management, Kaizen, Kanban, etc. can be attributed completely or at least partially to Toyota. These concepts integrated in the so-called Toyota Production System (TPS) are now considered standard elements of modern production systems and are standard repertoire in business management. However, with a focus on the management of production systems, they only represent one of the cornerstones of the successful Toyota model. Toyota currently operates extremely efficient global supply chains with international production sites (in Japan, USA, France, Brazil, Argentina, Malaysia, Pakistan, etc.), globally distributed suppliers and a worldwide dealer network. Toyota implemented not only efficient production (with TPS), but also sustained efficient design and coordination of globally distributed value-added activities. To accomplish this, Toyota has consistently developed its management philosophy and the principles underlying TPS and integrated these in the "Toyota supply chain".While we were able to learn from Toyota in the past as to how production systems can be designed, today we can learn from Toyota as to how complex global supply chains in the automotive industry - but also in other industries - should be designed and coordinated. Notably its planning principles are - despite the greater complexity - easy to understand, simple to implement and are based on simple 'ground rules'. The aim of this seminar is to learn from the Toyota supply chain.

Intended learning outcomes

Drawing on current cutting-edge research, students are enabled to critically and independently analyze current research questions and to learn and apply research methods. The seminar style of the course teaches them to present their own seminar papers and research both in written and in oral form. Students are enabled to critically analyze and discuss the work of their peers.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 10 to 15 pages) and presentation (approx. 10 minutes), (weighted 2:1) Language of assessment: German and/or English

Allocation of places

20 places. Should the number of applications exceed the number of available places, places will be allocated as follows: (1) Applicants who have already achieved a total of 90 ECTS credits or more will be given preferential consideration. (2) When places are allocated in accordance with (1) and the number of applications exceeds the

number of available places, places will be allocated according to the average grade of assessments taken so far;

among applicants with the same average grade, places will be allocated by lot.

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Information Economics - Software Project

12-WI-SWP-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This module will present students with an opportunity to practically apply and consolidate their theoretical knowledge and skills, over the course of several weeks, in a project on a software-related topic.


Reading:

will vary according to content

Intended learning outcomes

After completing the course "Wirtschaftsinformatik Software-Praktikum", students will be able to

  1. outline practical problem solutions on different topics on IS and IT;

  2. assess and solve practical IS situations.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 20 pages) and presentation (approx. 15 minutes), weighted 2:1 Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Practical Course in Software for Students in Business Information Systems

10-I-SWP-WI-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

10

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Completion of a project assignment in groups, problem analysis, creation of requirements specifications, specification of solution components (e. g. UML) and milestones, user manual, programming documentation, presentation and delivery of the runnable software product in a colloquium.

Intended learning outcomes

The students possess the practical skills for the design, development and execution of a software project in small teams.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

project

Completion of a larger software project in groups (approx. 300 hours per person) and final presentation (approx.

10 minutes per group)

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Seminar 1

10-I-SEM1-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Independent review of a current topic in computer science on the basis of literature and, where applicable, software with written and oral presentation. The topics in modules 10-I-SEM1 and 10-I-SEM2 must come from different areas (this usually means that they are assigned by different lecturers).

Intended learning outcomes

The students are able to independently review a current topic in computer science, to summarise the main aspects in written form and to orally present these in an appropriate way.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 10 to 15 pages) and presentation (approx. 30 to 45 minutes) with subsequent discussion on a topic from the field of computer science

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

§ 22 II Nr. 3b

Module appears in

Bachelor' degree (1 major) Computer Science (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

First state examination for the teaching degree Gymnasium Computer Science (2015) Bachelor' degree (1 major) Business Information Systems (2016)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016)

Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Computer Science (2019) Module studies (Bachelor) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)

Bachelor' degree (1 major) Business Information Systems (2020)


Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Seminar 2

10-I-SEM2-152-m01

Module coordinator

Module offered by

Dean of Studies Informatik (Computer Science)

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Independent review of a current topic in computer science on the basis of literature and, where applicable, software with written and oral presentation. The topics in modules 10-I-SEM1 and 10-I-SEM2 must come from different areas (this usually means that they are assigned by different lecturers).

Intended learning outcomes

The students are able to independently review a current topic in computer science, to summarise the main aspects in written form and to orally present these in an appropriate way.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Wrap-up report on tutoring activities (5 to 10 pages) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Computer Science (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Computer Science (2017)

Bachelor' degree (1 major) Computer Science (2019) Module studies (Bachelor) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Computer Information Systems 1

12-CIS1-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This is a dummy module in the Bachelor's degree programme Wirtschaftsinformatik (Business Information Systems) that may be used, for example, for the accreditation of courses taken abroad. Contents will vary according to the subject selected.


Among others, the subject Agiles Vorgehen in Softwareprojekten (Agile Approach to Software Projects) may be accredited as Computer Information Systems.

Intended learning outcomes

The Competences differ depending on the course to be taken into account.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)

Assessment offered: Only when announced in the semester in which the courses are offered and in the subsequent semester

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Computer Information Systems 2

12-CIS2-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This is a dummy module in the Bachelor's degree programme Wirtschaftsinformatik (Business Information Systems) that may be used, for example, for the accreditation of courses taken abroad. Contents will vary according to the subject selected.


Among others, the subject Agiles Vorgehen in Softwareprojekten (Agile Approach to Software Projects) may be accredited as Computer Information Systems.

Intended learning outcomes

The Competences differ depending on the course to be taken into account.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (groups of up to 3: approx. 10 minutes per candidate)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Business Administration

(max. 25 ECTS credits)


Module title

Abbreviation

Entrepreneurship, Competition and Strategy

12-U&UF-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Marketing

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

The module builds on the introductory course "Grundlagen marktorientierter Unternehmensführung" ("Fundamentals of Market-based Management"). It provides a systematic introduction to the approaches of corporate management (stakeholder and shareholder value approach) as well as an overview of market-oriented corporate governance. In addition, aspects of responsible leadership will be discussed.

The theory of Chester Barnard with the idea of creating a complex economic incentive contribution balance in the company will help students develop an in-depth understanding of typical management tasks. In addition, the course will focus on the development of business plans for the successful establishment and the continued existence of companies.

Outline of syllabus:

  1. Business and strategy in economic theory

  2. Business plan as a strategy concept

  3. Stakeholder management and responsible leadership

  4. Stakeholder value, shareholder value and creating shared value

Intended learning outcomes

Students will gain profound knowledge of basics in business as well as basics in different approaches in corporate management. Furthermore the students will get an overview of the main tools to create a business plan.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015)


Master's degree (1 major) China Business and Economics (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Sales and Customer Relationship Management

12-SCRM-211-m01

Module coordinator

Module offered by

Holder of the Junior Professorship of Digital Marketing and E-Commerce

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

A key challenge for companies in a marketing context is to choose the right approaches on how to deliver their products and services to customers. In doing so, companies need to carefully consider their customers’ needs and requirements to successfully manage company-customer relationships.


This course focuses on classic and new approaches of sales and customer relationship management. In particular, it covers the set-up of sales systems in terms of offline channels (e.g., retail stores) and online channels (e.g., online shops or market places), their interplay (e.g., multi-channel management), or the management of the sales force.

Moreover, it focuses on different types of customer-firm interactions, on approaches of analyzing customer satisfaction and loyalty, as well as on customer complaint management, cross-selling management or customer experience management.

Intended learning outcomes

The major goal of this class is to learn about and understand how sales management and customer relationship management work and to be able to transfer respective concepts to real life / business practice.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) Written examination (approx. 60 to 120 Minutes) or b) Term paper (to be prepared by one candidate or in groups of 3 candidates approx. 10 pages each ) or c) oral examination in groups (groups of 3, approx. 10 minutes per candidate)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015)


Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Marketing

12-SMA-211-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Marketing

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured paper and to present the results of their work with the help of relevant topics in the fields of strategic marketing and strategic management.


Reading:

will vary according to topic

Intended learning outcomes

After completing the course "Marketing Strategie", students will be able to


  1. understand the fundamentals of scientific literature reviews;

  2. integrate elaborated content in a scientific thesis;

  3. create presentations independently.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 25 minutes), weighted 2:1 Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 88 / 326


Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 89 / 326


Module title

Abbreviation

International Marketing

12-INMA-211-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course seeks to familiarize students with the tools and terminology to explore and understand marketing practices in an international environment. They will learn the scope and challenges of international marketing, the dynamic environment of international trade, culture, political, legal, and business systems of globalizing markets, opportunities and threats on global markets and develop decision-making skills for the successful formulation, implementation and control of international marketing strategies. In particular, the course highlights strategic and managerial issues related to international marketing.

Intended learning outcomes

Students are required to study and prepare marketing approaches to enter and operate in international markets. Students intensify their knowledge and develop theoretical and practical concepts through case studies.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) Written examination (approx. 60 minutes) or b) Term paper (15 to 20 pages) or

  1. Term paper (10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  2. oral examination of one candidate each (approx. 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 90 / 326


exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Supply, Production and Logistics Management. Material Requirements Planning

12-BPL-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module builds on the course "Beschaffung, Produktion und Logistik - Grundlagen" ("Procurement, Production and Logistics - Basics"). Selected tasks and processes, in particular in the area of materials management, will be analysed in detail and related planning and control models and methods will be developed.

Intended learning outcomes

The students are able to analyze the areas of responsibility of the functions of procurement, production and logistics as well as their interdependencies in an integrated perspective and evaluate concepts for their management. In addition, they are able to develop models in the domain of materials management and apply solution procedures to the planning problems.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (15 to 20 pages) or

  3. term paper (10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  4. oral examination (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Economathematics (2023)


Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Humanitarian Supply Chain Management

12-HSCM-211-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Despite the solidarity-based nature of humanitarian aid, up to 70% of the activities of humanitarian aid organizations are related to both, the design and the coordination of logistical processes. Humanitarian assistance is delivered through humanitarian supply chains, systems concerned with planning, executing, and controlling the effective, cost-efficient flow and storage of materials, goods, and related information from the point of origin to the point of consumption in order to meet the needs of the beneficiaries. While aid organizations do not operate in a traditional business environment, the requirements for managing humanitarian supply chains effectively and efficiently are fundamentally comparable to those of commercial supply chains. Similarly, humanitarian organizations often employ business managers to manage their business processes. The management of the supply chain of a humanitarian organization, therefore, requires basic business knowledge that will be addressed in this course.

Intended learning outcomes

The course will provide you with a basic understanding of factors influencing humanitarian supply chains and fundamental insights in managing them efficiently and effectively. You will learn about the different roles of humanitarian organizations and the challenges they face. Furthermore, you will be introduced to general supply chain management concepts that can also be applied in the humanitarian context, and that can provide a significant positive impact on the organization of humanitarian operations.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Supply, Production and Logistics Management

12-BPL-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The seminar will focus on special problems in the areas of procurement, production, logistics or business management. Students will independently work on the respective problem and write a seminar (term) paper. Usually, this will be largely literature based with students learning how to carry out structured literature analyses and prepare systematic evaluations. In individual cases, students may also conduct empirical research of their own or further develop formal models. Students will be required to deliver a talk on the subject in class.

Intended learning outcomes

The students will be able to study advanced problems on their own and structure them in a (seminar) paper. They will learn to present the central results and discuss related issues in class.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. term paper (approx. 15 pages) and presentation (approx. 20 minutes); (weighted 2:1) or

  2. term paper (approx. 20 to 25 pages)

Language of assessment: German and/or English

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 96 / 326


Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 97 / 326


Module title

Abbreviation

Modern Approaches in Logistics

12-AAL-221-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (15 to 20 pages) or

  3. Term paper (10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  4. oral examination (approx. 20 minutes) or

  5. Portfolio (approx. 15-20 pages)

Language of assessment: German and/or English Assessment offered: yearly, to be announced

creditable for bonus

Allocation of places

30 places.

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

Module can be taught in form of E Learning course, seminar, workshop etc.

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 98 / 326


Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 99 / 326


Module title

Abbreviation

Foundations of transport logistics

12-GT-221-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (15 to 20 pages) or

  3. Term paper (10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  4. oral examination (approx. 20 minutes) or

  5. Portfolio (approx. 15-20 pages)

Language of assessment: German and/or English Assessment offered: yearly, to be announced

creditable for bonus

Allocation of places

30 places.

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

Module can be taught in form of E Learning course, seminar, workshop etc.

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 100 / 326


Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Digital Science 1

12-DS1-222-m01

Module coordinator

Module offered by

--

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (approx. 15 pages) or

  3. Term paper (10 to 15 pages) and presentation (approx. 10 minutes); (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Digital Science 2

12-DS2-222-m01

Module coordinator

Module offered by

--

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (approx. 15 pages) or

  3. Term paper (10 to 15 pages) and presentation (approx. 10 minutes); (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Digital Science 3

12-DS3-222-m01

Module coordinator

Module offered by

--

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Term paper (approx. 15 pages) and presentation (approx. 20 minutes); (weighted 2:1) or

  2. Term paper (20 to 25 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Digital Science 4

12-DS4-222-m01

Module coordinator

Module offered by

--

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Term paper (approx. 15 pages) and presentation (approx. 20 minutes); (weighted 2:1) or

  2. Term paper (20 to 25 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023)


Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Financial Accounting

12-Wipr1-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content: This module is based on introductory courses in the areas of financial and managerial accounting and includes essential aspects of corporate financial accounting. It delivers a systematic presentation and interpretation of financial reporting standards according to the Handelsgesetzbuch (German Commercial Code, HGB) and International Financial Reporting Standards (IFRS). In addition, it introduces students to financial statement analysis methods.


Outline of syllabus: Fundamentals of financial statements; purpose and basic assumptions of financial accounting; recognition, valuation and presentation of assets, liabilities and equity; financial statement analysis.


Reading:

Baetge, J./Kirsch, H-J./Thiele, St.: Bilanzen, Düsseldorf.

Coenenberg, A.G.: Jahresabschluss und Jahresabschlussanalyse, Stuttgart. Heuser, P.J./Dörschell, A.: IFRS Hand-

buch, Cologne 2012. Most recent editions.

Intended learning outcomes

The students have a deeper understanding of business fundamentals in accounting according to national (HGB) and international (IFRS) principles. They can systematically arrange and play with the knowledge and apply the acquired knowledge, i.e. resolve accounting and financial statement analysis problems of medium difficulty.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

International Accounting

12-Wipr2-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Outline of syllabus:

  1. Fundamentals of group accounting

  2. Legal obligations for group accounts

  3. Consolidated companies

  4. Capital consolidation

  5. Debt consolidation

  6. Consolidation of intercompany results

  7. Consolidation of income and expenses

  8. Equity method

  9. Selected problems


Reading:

Baetge/Kirsch/Thiele: Konzernbilanzen, Düsseldorf.

(most recent edition)

Intended learning outcomes

After finishing this module "Konzernrechnungslegung nach HGB und IFRS", the students will be able

  1. to present the purposes of group accounting;

  2. to identify and interprete central legal rules;

  3. to apply consolidation methods on problems of moderate difficulty (in terms of capital, debt, interim results, expenses and income) and preparing the necessary entries for the group accounts;

  4. to name central differences for group accounts according to the German Commercial Code (HGB) and IFRS

and give reasons for the differences.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Module title

Abbreviation

Financial Statement Analysis and Valuation

12-Wipr3-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This module builds on the introductory courses in the areas of Financial and Managerial Accounting and, in particular, on the course "Jahresabschluss und -- analyse nach HGB und IFRS" ("Financial Accounting according to HGB and IFRS"). The module provides students with a systematic introduction to practical, methodical and theoretical aspects of business audits, i. e. financial statement audits.


Outline of syllabus:

  1. Audits and audit-related services - introduction and overview

  2. Audit process: functional aspects of economic examination

  3. Audit institutions: institutional aspects of economic examination

  4. Economical audit theory: the low-balling model of DeAngelo


Reading:

Marten, K.-U./Quick, R./Ruhnke, K.: Wirtschaftsprüfung, Düsseldorf (most recent edition).

Intended learning outcomes

The students have a deeper understanding of the basics of business (balance) checks. They can organize, play back and apply the systematically gained knowledge, i.e solve simple problems of business (balance sheet) tests.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in


Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Financial Accounting

12-Wipr-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module provides students with deeper insights into current problems of external accounting and auditing, usually with the help of textbooks or adequate scientific primary literature in English or German language.

Intended learning outcomes

After completing this module, students are able to

  1. consolidate what they have learned and if necessary apply additional techniques of scientific work;

  2. create and defend a qualification level relevant scientific work;

  3. carry out scientific analysis of the results from other seminar participant;

  4. ability to present and reflect solution-oriented the own performance considering communication aspects.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 20 minutes), weighted 2:1 Language of assessment: German and/or English

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 116 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Investment and Finance

12-I&F-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management, Banking and Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This course offers an introduction to principles of financial mathematics, several methods of capital budgeting and principles of financial economics.


Outline of syllabus:

  1. Principles of financial mathematics

  2. Fundamental concepts

  3. Problems of investment and finance in one commodity world under certainty

  4. Problems of investment and finance in one commodity world under uncertainty

  5. Problems of investment and finance in many commodities world under uncertainty

  6. Capital market and corporate financing in Germany

Intended learning outcomes

After completing the course "Principles of Investments and Finance", the students will be able

  1. to understand the fundamentals in financial mathematics and solve several problems, e.g. via the PV approach;

  2. to address the central problems in intertemporal allocation given different capital market scenarios;

  3. to budget and calculate the optimal useful life given static and dynamic investment approaches under the consideration of several other investment opportunities and the capital market scenario, especially the influence

of taxes.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Decision Theory

12-I&F-F-192-m01

Module coordinator

Module offered by

Holder of the Chair of Corporate Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Based on the decision theory under certainty, this module covers normative decision theory under uncertainty in its manifestations of the expected utility theory and the μ - # theory.


Syllabus:

Part 1: Decisions under certainty

  1. Fisher mode

  2. Revealed preferences

  3. Preference relations

Part 2: Decisions under uncertainty: Expected Utility Theory

  1. The basic model

  1. Risk preferences

  2. Intensity of risk aversion

  3. Stochastic dominance

  4. Prospect Theory

Part 3: Decisions under uncertainty: μ − # principle

  1. Introduction

  2. Relation to expected utility theory

  3. Application in Portfolio Theory & Tobin-Separation

  4. Properties

Intended learning outcomes

The students acquire knowledge about how to describe appropriate decision situations and how to solve them based on the learned concepts.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Investment and Finance

12-I&F-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management, Banking and Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This seminar deals with current topics of investments and finance. Students will be required to independently analyse a selected topic and to write a term paper. This term paper may be largely literature based or empirical or may be based on independent work with formal models. In addition, students will be required to deliver a talk on the topic.

Intended learning outcomes

After completing the seminar "Investments and Finance", the students acquired detailed knowledge of important fields of investments and finance. They are also able to process their research findings in a written assignment and to present their findings.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and oral examination (approx. 25 minutes), (weighted 3:2)

Allocation of places

15 places.

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 122 / 326


Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Introduction to Risk Management

12-ERM-211-m01

Module coordinator

Module offered by

Holder of the Chair of Corporate Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module provides an overview of the form and approach of the systematic risk management process in a business context. This risk management process consists of the process steps of risk identification, risk assessment and aggregation, risk management and risk control.


This course is based on this process structure and is structured accordingly:


Legal and business motivation for risk management. Risk identification

Risk assessment and aggregation Risk control

Risk control and reporting

Risk management information systems (RMIS)

M1 | Legal and business motivation for risk management


In Germany, outside the banking sector, there have been legal regulations for setting up corporate risk management since the KonTraG came into force in 1998. In addition to the legal obligation to set up a risk management system, the systematic handling of risks is also of interest from a business management point of view, as the conscious acceptance of risks has a significant positive influence on the company's ability to plan and control.


M2 | Risk identification


Risk identification involves systematically recording all of a company's major risks. The earlier risks are identified, the more comprehensively appropriate countermeasures can be taken.

Risk identification is a fundamental task of risk management, as it provides the information basis for all further process steps, because only identified risks can be assessed, aggregated and controlled. Various methods can be used to identify risks.


M3 | Risk assessment and aggregation


Once risks have been identified, they must be assessed. Both qualitative and quantitative methods are available for this purpose. The objective of risk assessment is to describe the risk in terms of appropriate statistical distribution functions. Once the relevant risks have been described by distribution functions, the next task is to determine the company's overall risk position by means of a so-called risk aggregation.


M4 | Risk management


This module deals with the options for risk control. Risk management is strongly linked to a company's strategy, as this is also where the company's attitude towards risk is anchored (risk appetite). In addition, the risk coverage potential (=available equity capital) is of decisive and existential importance.

Various strategies can be used to manage risks. M5 | Risk control and reporting

With the help of early warning indicators (so-called key risk indicators, KRI), (negative) changes in the scope or

probability of risk occurrence can be monitored and identified in good time. However, risk control does not only


monitor KRI, it is also used to control measures implemented as part of risk management and to evaluate them for efficiency and success.

As part of risk reporting, all findings from the individual risk management process phases are transferred to a risk report. The addressees of the risk report are risk officers, department heads, the Board of Management, the Supervisory Board or external parties such as auditors, shareholders or rating agencies. The scope and level of detail of the risk report depend on the recipient of the report.

M6 | Risk management information systems (RMIS)

A prerequisite for the company-wide and sustainable establishment of a risk management system is the software support provided by risk management information systems. Although known risks can be recorded and processed using standard tools such as Excel spreadsheets, they quickly reach their limits. As soon as additional users are to be integrated, an integrated software approach is required, as risk management information systems entail.

Intended learning outcomes

Students are taught the fundamentals of risk management. The students are able to identify, record and evaluate risks in a structured manner and furthermore express the scope of risk on a mathematical basis. The students are able to derive suitable risk measures and know how risks can be monitored.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Business Valuation between Financial Mathematics and Data on Capital Market

12-UBW-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Corporate Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

This course deals with the "objectified corporate valuation" of public companies, the components of the discount rate and the mathematical structure of the DCF methods.

Outline of syllabus:

  1. Introduction

  2. Uncertainty as the central problem in the valuation of a company

  3. Estimation of surpluses: accuracy and consistency

  4. Risk free rate: capitalised value under certainty applying different interest rate structures

  5. The risk premium: identification of the relevant risk and its equivalence for valuation object and alternative investment

  6. Different discounted cash flow valuation methods: formal foundations and economic principles

Intended learning outcomes

After completion of the module "Business valuation between Financial Mathematics and capital market data" students can

  1. understand the modern process of objectified business valuation theory;

  2. examine submitted reviews according to consistent application of these methods.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)


Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Business Taxation 1: An Introduction to Tax Law & Tax Planning

12-St1-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module will introduce students to the field of business taxation. It will provide an overview of German tax law and will analyse tax effects on economic decisions in standard models for investment and financing decisions.

Intended learning outcomes

Students get an overview of the German tax law and they acquire the ability to recognize and understand the effect of taxation in fundamental ecomonic decisions. Therefore, the module is recommended also for students who don't want to specialize in finance and accounting but rather in management studies.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021)


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)


Module title

Abbreviation

Business Taxation 2: The Taxation of Income in Germany

12-St2-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this module, students will acquire an in-depth knowledge of the system of income taxation in Germany which consists of personal income tax, corporate income tax and trade tax, a special income tax on business income.

Intended learning outcomes

Students acquire in-depth knowledge of the system of income taxation in Germany. They are able to solve practical problems of medium to high complexity in this filed by means of the tax code, other legal texts and secondary literature.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Business Taxation 3: Introduction to VAT

12-St3-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Introduction to German value added tax.

Intended learning outcomes

Students acquire a thorough knowledge of German VAT law. They are able to solve VAT problems of low to medium complexity by using the tax code itself as well as related literature.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Economathematics (2021)


Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Selected Topics in Business Taxation

12-StAP-V-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module deals with selected problems and issues of business taxation.

Intended learning outcomes

The students will be able to edit and solve selected problems and issues of business.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), (weighted 2:1) or

  3. c) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Business Taxation

12-StAP-S-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module deals with selected problems and issues of business taxation.

Intended learning outcomes

The students will be able to edit and solve selected problems and issues of business taxation.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), (weighted 2:1) or

  3. c) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Human Resource Management

12-P&O-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Human Resource Management and Organisation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The lecture "Personal und Organisation" ("Human Resources Management and Organisation") presents and discusses basic theories, estimation techniques and empirical results from the area of personnel economics and organisation.

Reading list to be provided during lecture

Intended learning outcomes

The aim of the lecture is to enable students to understand and apply basic theories, estimation techniques and empirical results in the area personnel economics and organisation on the basis of text books and scientifc literature.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Master's degree (1 major) Media Entertainment (2022) Master's degree (1 major) Psychology of digital media (2022)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Economathematics (2023)


Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Human Resource Management & Organizational Theory

12-P&O-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Human Resource Management and Organisation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Students will write a seminar paper on, deliver a talk on and discuss current issues in the field of human resources management and organisation in class.

Intended learning outcomes

The students learn to handle, formulate in own words, present, and discuss current research literature.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 20 minutes), (weighted 1:1) Language of assessment: German and/or English

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Strategic and Innovation Management

12-IM-212-m01

Module coordinator

Module offered by

holder of the Chair of Entrepreneurship and Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course will provide students with an overview of essential topics of innovation management. Particular emphasis will be on the application of theoretical concepts to practical examples and cases. The course will develop the innovation process starting with the idea and ending with the market entry of an innovation. The course will consist of two core elements: 1. "Creating Value": how can companies create something new? and 2. "Profiting from Value": how can companies profit from innovations? The course will use practical examples from numerous industries such as world-class restaurants, music, consumer goods, electricity or the software industry.

Intended learning outcomes

At the end of the module students are able to understand:

  • The importance of innovations

  • The sources of innovations

  • The New Product Development process

  • The roles in the innovation process

  • The importance of intellectual property rights

  • How innovations diffuse in the market

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (as individual or group work; approx. 10 pages per person) or

  3. oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Master's degree (1 major) Media Entertainment (2022) Master's degree (1 major) Psychology of digital media (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Research Seminar

12-RES-211-m01

Module coordinator

Module offered by

Holder of the Chair of Entrepreneurship and Strategy

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation and present the key insights from their work.

Intended learning outcomes

Educational aims

  • Raise students’ awareness of research positioning and theoretical modelling

  • Familiarize students with systematic literature search

  • Enable students to develop a well-structured, academic manuscript


    Learning outcomes


    On successful completion of this module students will be able to:

  • Formulate an adequate research question

  • Effectively search the literature

  • Structure and write-down an academic manuscript

  • Present and explain their research outcomes in class

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Term paper (10 to 15 pages) and presentation (in groups of up to 3 candidates, approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

15 places.

Should the number of applications exceed the number of available places, places will be allocated as follows:

  1. Applicants who have already achieved a total of 90 ECTS credits or more will be given preferential consideration.

  2. When places are allocated in accordance with (1) and the number of applications exceeds the number of available places, places will be allocated according to the average grade of assessments taken so far; among ap-

plicants with the same average grade, places will be allocated by lot.

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Business Simulation

12-BUS-211-m01

Module coordinator

Module offered by

Holder of the Chair of Entrepreneurship and Strategy

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This action-oriented module complements the lecture “Strategic and Innovation Management” (12-IM). In teams of up to four students, student compete in a business simulation that covers critical elements of managerial decision making. Participants act as a board of directors to develop the business by making decisions related to strategy, finance, market, operations, staffing, and innovation. This provides a unique opportunity to directly apply and critically reflect topics discussed in the classroom, while working in a team.

Intended learning outcomes

Educational aims

  • Raise students’ situational awareness in managerial decision making

  • Promote students’ ability to make informed managerial decisions in complex situation

  • Sensitize students for the need to anticipate competitive actions and reactions


    Learning outcomes


    On successful completion of this module students will be able to:

  • Understand how management theories can be applied in ‘real-life’ decision making scenarios

  • Understand the interconnectivity of managerial decisions in different areas of a company, e.g., marketing, finance, and innovation

  • Make managerial group decisions based on anticipated competitor behavior

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Term paper (10 to 15 pages) and presentation (in groups of up to three candidates, approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

15 places.

WB4

Should the number of applications exceed the number of available places, places will be allocated as follows:

  1. Applicants who have already achieved a total of 90 ECTS credits or more will be given preferential consideration.

  2. When places are allocated in accordance with (1) and the number of applications exceeds the number of available places, places will be allocated according to the average grade of assessments taken so far; among ap-

plicants with the same average grade, places will be allocated by lot.

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Business Plan

12-BPS-211-m01

Module coordinator

Module offered by

Holder of the Chair of Entrepreneurship and Strategy

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Students work in teams of up to three students to develop a business model and a business plan for an own business idea or a notional one.

Intended learning outcomes

Educational aims

  • Clarify the role of business models and business plans

  • Clarify theoretical concepts related to business models and business plans

  • Enable students to critically appraise alternative approaches to business modelling and business planning

  • Enable students to evaluate the boundaries and risks of business modelling and business planning


    Learning outcomes


    On successful completion of this module you will be able to:

  • Assess the role of business models and business plans for startups and established companies

  • Make judgements about the design of business models and business plans

  • Create and evaluate concepts related to business models and business plans

  • Systematically choose between different routes of action

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Term paper (10 to 15 pages) and presentation (in groups of up to three candidates, approx. 10 minutes per candidate)

Language of assessment: German and/or English

Allocation of places

15 places.

WB4

Should the number of applications exceed the number of available places, places will be allocated as follows:

(1) Applicants who have already achieved a total of 90 ECTS credits or more will be given preferential consideration. (2) When places are allocated in accordance with (1) and the number of applications exceeds the number of available places, places will be allocated according to the average grade of assessments taken so far; among ap-

plicants with the same average grade, places will be allocated by lot.

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Managerial Accounting: cost-based decision-making and control

12-KR-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management, Management Accounting and Control

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

First, this module will discuss basic principles of accounting such as full and direct costing as well as cost and performance accounting in the context of decision-making. The course will then focus on decision-making processes (short-term production planning, pricing decisions) and internal control calculations (the role of controls, deviation analyses).

Intended learning outcomes

This module provides competences in order to apply systems of full and direct costing, cost and performance accounting with regard to decision-making and internal control processes. After completing the course unit, students will be able to understand and assess the theoretical principles and interrelationships in decision-making and control as well as be able to apply them to examples from corporate practice. The goal is to promote analytical thinking and problem-solving abilities by analyses of complex problem structures.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019)

Bachelor' degree (1 major) Business Management and Economics (2019)


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Sales Accounting & Management

12-VeCo-212-m01

Module coordinator

Module offered by

holder of the Chair of Chair of Business Management, Controlling and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The focus of the lecture is the support of sales management by controlling. The course covers the positioning of sales and sales management with a special emphasis on B2B sales of IT companies and the position of sales controlling as a subset of overall controlling in different business organisations. The course discusses basic requirements of an ideal support of sales by controlling as well as possible elements with which this support function can be realised, such as management information systems, target management and customer relationship management.

Intended learning outcomes

Knowledge about the practice of working in sales management and the associated sales is acquired. By displaying theoretical tools to support sales management by the controlling and the balance with the reality in companies, participants further acquire skills to evaluate the possible use of sales management tools in practice.

Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

40 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 150 / 326


Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Managerial Accounting

12-AAC-212-m01

Module coordinator

Module offered by

holder of the Chair of Chair of Business Management, Controlling and Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured paper and to present the results of their work with the help of relevant topics in the field of the focuses of module "Entscheidungs- und Kontrollrechnung" ("Management Accounting: Decision Making and Control").

Intended learning outcomes

After completing the controlling bachelor seminar, students will be able to

  1. understand and apply the fundamentals of scientific literature reviews;

  2. use elaborated content to write scientific papers;

  3. create presentations and lectures independently.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 12 pages) and presentation (approx. 20 minutes), (weighted 2:1)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Selected Topics in Business Management 1

12-APB1-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (approx. 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Selected Topics in Business Management 2

12-APB2-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (approx. 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Economics

(max. 25 ECTS credits)


Module title

Abbreviation

Microeconomics 1

12-Mik1-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Economics, Information and Contract Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The lecture covers the following topics


Theory of the household:

  1. Utility maximisation under constraints

  2. Comparative statics

  3. Income and substitution effects

  4. Labour supply

  5. Intertemporal consumption / savings decisions


    Theory of the firm:

  6. Production functions (technology)

  7. Profit maximisation

  8. Long run versus short run cost minimisation

  9. Supply of goods

Intended learning outcomes

Students are systematically trained in microeconomic methods relevant in household and firm theory. Accordingly, they will know how to solve optimization problems under constraints. These scientific methods will serve as useful in many fields of specialization in economics and business administration. In particular, studends know analytically how to analyze the impact of changes in the economic environment, e.g., wages, interest rates, income on individual decision making.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in


Module studies (Bachelor) Business Management and Economics (2019) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Microeconomics 2

12-Mik2-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Outline of syllabus:

  1. Cost minimisation

  2. Profit maximisation and the supply function

  3. Short-run market equilibrium

  4. Long-run market equilibrium

  5. Government interventions

  6. Monopoly

  7. Pricing strategies with market power

  8. Introduction to game theory

  9. Strategic interaction and oligopoly

Intended learning outcomes

The aim of the course is to understand how markets work. We will investigate the behavior of a company in different market structures; namely perfectly competitive markets, monopoly markets and all forms in between, the so-called oligopoly markets. Ultimately, we are interested in whether the market results from a social point of view is desirable. Using our models, we will also try to analyze the consequences of different government interventions. The knowledge that students gain in this course will be in their future course of studies of benefits to them. In almost all business and economics lectures markets play a role. It also discussed in detail how economic actors make their decisions. Students will thus learn the important building blocks of economic thought. This knowledge will also be useful in the workplace and even in their private lives.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Macroeconomics 1

12-Mak1-G-212-m01

Module coordinator

Module offered by

holder of the Chair of International Macroeconomics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This module covers basic macroeconomic relationships, the declaration of employment, production, interest, current and capital account, nominal and real exchange rate, prices and inflation - in the long run (with flexible wages and prices) and in the short term (with fixed wages and prices). The course will familiarise students with concepts which are of central importance in a globalised environment (e. g. interest rate arbitrage, foreign exchange risk, purchasing power parity). The explanations will be applied to current issues (e. g. current account balances in the global economy; questions related to the European monetary union and the global financial crisis).


Outline of syllabus:

  1. Macroeconomic issues and characteristics

    • Issues of macroeconomics

    • The measurement of economic activity

  2. Long-term relationships

    • The classic long-term model of the closed economy

    • Money and Inflation

    • The classic long-term model of a small open economy

    • Unemployment

  3. Short and medium-term relationships

    • Fluctuations of economic activity: an introduction

    • The IS-LM model of a closed economy

    • The IS-LM model of an open economy

    • Aggregate supply and Phillips curve

    • Conclusion and outlook

Reading:

The latest editions of the following textbooks:

N. Gregory Mankiw: Macroeconomics [students are recommended to read the original English edition; they may also read the German translation]

Olivier Blanchard and David H. Johnson, Macroeconomics Prentice Hall; [a German-language edition of the book by Oliver Blanchard and Gerhard Illing is available from Pearson Studium].

Michael Burda and Charles Wyplosz: Macroeconomics. A European text.

To illustrate the lecture, case studies in particular will be developed in which more current sources are used.

Intended learning outcomes

This expertise enables the students to penetrate economically-intuitively and analytically macroeconomic interactions and problems in the course of advancing globalization and to deal with these arguments. Students learn to interpret on a scientific basis the impact of macroeconomic developments in individual economic actors (businesses, households, the state).

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)


Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Macroeconomics 2

12-Mak2-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Public Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

The lecture provides an introduction to long run or dynamic issues of macroeconomic theory and policy.


Contents:

  1. Phillips curve and dynamic model

  2. Growth theory and policy

  3. Microeconomic foundations of macroeconomics

  4. Macroeconomic policy


Lecture notes to be provided by Chair.

Intended learning outcomes

After completing the course "Makroökonomie 2" students are familiar with the most important concepts of growth theory, they know the microeconomic foundations of modern macroeconomic theory and understand the intertemporal budget constraint of the government. Therefore they are able to discuss the growth and distributional consequences of policy reforms by applying simple economic models.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 162 / 326


Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 163 / 326


Module title

Abbreviation

Monetary Policy and Financial Markets

12-EuGP-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Monetary Policy and International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course discusses the following questions:

  1. Why is price stability the main objective of the ECB?

  2. How can the ECB control interest rates and the creation of credit? Why did the financial crisis happen?

  3. How does interest rate policy influence macroeconomic objectives (price stability and full employment)?

  4. Why is it important for monetary policy to be independent?

  5. How does the ECB know, how to set interest rates? (strategies of monetary policy)

  6. Why did central banks engage in unconventional monetary policy during the last years?

Intended learning outcomes

By completing this course, students receive a profound understanding of theory and practice of monetary policy. Next to a profound knowledge of monetary policy in general, students are able to form a critical opinion about the conduct of monetary policy by the European Central Bank and in part about the policy of other central banks.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022)

Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 164 / 326


Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

International Money & Finance

12-IFM-212-m01

Module coordinator

Module offered by

Holder of the Chair of Monetary Policy and International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module introduces students to exchange rate theory, the determinants of international financial flows and monetary open economy models for the analysis of monetary and fiscal policy. The module is divided into three parts. The first one covers exchange rates and the second one the balance of payments, international financial flows and financial market globalization. Based on these two, the third one focusses on economic policy applications including the exchange rate regime choice, exchange rate crises and optimum currency area theory.


Format of the module: Lectures and exercise sessions


Prerequisites: Basic knowledge of microeconomics and macroeconomics as taught for example in a Principles of Economics class or in Microeconomics I and Macroeconomics I.


Usability: Bachelor Wirtschaftswissenschaften


Requirements for getting credit points according to the Eropean Credit Transfer System (ECTS): Passing the final exam.

ECTS and grading: 5 ECTS, Grading on a scale from 1-5 based on the final exam. Frequency of the module: Each summer term

Workload: 150 hours (Lecture + Exercise Session + Self Study)

Duration: 1 Semester

Intended learning outcomes

Students will acquire a basic understanding of international finance and learn analyzing practical examples with monetary models. Students gain expertise on institutional aspects and theoretical models. Having completed the module, students will be able to understand current developments in international finance and apply models and theories to analyze and evaluate these.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Applied Business Cycle Analysis and Forecasting

12-AKP-211-m01

Module coordinator

Module offered by

Holder of the Chair of Monetary Policy and International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module is an introduction to economic forecasting and business cycle analysis. The course is divided into three sections. In the first section, statistical and methodological basics on quantitative macroeconomic analysis and forecasting are discussed. The second section covers various aspects and issues related to economic forecasting. In the last sections, recent developments, topics, and research insights are presented.


Format of the module: lectures


Prerequisites: Basic knowledge of microeconomics and macroeconomics as taught for example in a Principles of Economics class or in Microeconomics I and Macroeconomics I.


Usability: Bachelor Wirtschaftswissenschaften


Requirements for getting credit points according to the European Credit Transfer System (ECTS): Passing the final exam.

ECTS and grading: 5 ECTS, Grading on a scale from 1-5 based on the final exam. Frequency of the module: Each summer term

Workload: 150 hours (Lecture + Self Study)

Duration: 1 Semester

Intended learning outcomes

Students will acquire a basic understanding of the theory and practice of applied business cycle analysis and forecasting. Further, students will learn how to analyze and answer real-world economic problems using their economic toolkit. Students gain expertise on applying their knowledge gained in basic economics courses on policy-relevant issues. Having completed the module, students will be able to understand current macroeconomic and economic policy developments and to use models and theories to analyze and evaluate these.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) Written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes); (weighted 2:1) or d) oral examination (approx 20 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Economic Policy

12-VWL1-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Monetary Policy and International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Acquiring an in-depth understanding of specific problems of macroeconomics.

Intended learning outcomes

After the seminar, students can

  1. consolidate acquired knowledge and if necessary apply additional techniques of scientific work;

  2. create, present and defend a scientific paper;

  3. deal with the working papers of other participants;

  4. prepare beter for the processing of the bachelor thesis.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 25 minutes), (weighted 2:1) Language of assessment: German and/or English

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Economathematics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 170 / 326


Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

International Economics

12-IntÖk-152-m01

Module coordinator

Module offered by

Holder of the Chair of International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content


The course starts with an introduction into facts, trends and issues pertaining to the real side of globalization. The main part of the course deals with explanations of international trade (comparative advantage, product variety) and for international factor movements (if time permits). Current issues and controversies (e.g. globalization and labor; globalization and the environment; migration within the European Union) are analyzed on this background.


Outline

I nternational Economics – Trends and current developments

II Internationale Trade

  1. Ricardian Theory: Labor productivity and comparative advantage

  2. Heckscher-Ohlin-factor proportion theory and the general neoclassical model

  3. New Trade Theory: Product differentiation, scale economies, firm heterogeneity III International Factor Movements [time permitting]

Literature:

This course does not strictly follow a single textbook. The best general reference is


Krugman, P.R., M. Obstfeld, M.J. Melitz (2018), International Economics. Theory and policy (older versions will also do).

The course develops case studies that use additional references.

Intended learning outcomes

The students acquire the ability to critically reflect and understand trends and developments concerning the real side of the world economy: trade flows and international factor movements. They are enabled to understand and defend the causes and consequences of globalization both analytically as well as in an intuitive manner. They acquire the scientific knowledge to evaluate controversies associated with the ongoing deepening of the international division of labor.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English


Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019)

Module studies (Bachelor) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Module studies (Bachelor) Orientierungsstudien (2020)

Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: International Economics

12-IntÖk-FS-152-m01

Module coordinator

Module offered by

Holder of the Chair of International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content


Current topics in international economics and economic geography [e.g. Urbanization and Inequality; Tasks, Trade, and Cities; Outsourcing, Offshoring and Multinational Firms; Competition of Locations, Jurisdictions and Systems; Globalization and the Environment; Trade, Multinational Firms and Labor Markets; Triumph of the City]


Literature:

Peer-reviewed articles and/or monographs.

Intended learning outcomes

Drawing on current cutting-edge research, students are enabled to analyze current research questions and to learn and apply research methods. The seminar style of the course teaches them to present their own seminar papers and research both in written and in oral form. Students are enabled to critically analyze and discuss the work of their peers.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 30 minutes), weighted 3:1 Language of assessment: German and/or English

Allocation of places

10 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015)


Master's degree (1 major) China Business and Economics (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Applied Regional and Urban Economics

12-ARS-152-m01

Module coordinator

Module offered by

Holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

I A brief revision of econometrics: OLS and fixed effects regression

  1. Geographical agglomeration of economic activity

  2. Firm heterogeneity and the exporter wage premium

  3. A brief revision of econometrics: Instrumental variables regression

  4. German local labour markets and "the Rise of the East"

Intended learning outcomes

This course focuses on the empirical analysis of current topics in international and regional economics. After reviewing some theoretical background and empirical methods, students learn to comprehend empirical studies, recognize possible pitfalls and conduct their own analyses using statistical software packages and authentic datasets. A strong focus is put on the identification of causal effects. Students should already have basic knowledge in econometric analysis and international trade theory.

The lecture starts with a revision of basic empirical methods. The first application is to analyse if and why (and to what magnitude) firms benefit from being located in agglomerations such as the Silicon Valley. Next, we analyse the role of firms in international trade. What distinguishes exporters from non-exporters and are employees of exporters better off? Returning to a regional perspective, we then discuss several recent research papers on the adjustment of local labor markets to increasing trade with China and Eastern Europe.

In a complementary lab tutorial (Übung) students learn to conduct empirical analyses by themselves. In hands-on exercises, they first practice how to obtain and prepare datasets and how to use summary statistics to find general patterns in the data. We then apply our theoretical knowledge from the lecture to devise empirical strate-

gies and to interpret our results.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 pages) including empirical analysis prepared by candidates

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in


Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Games and Strategies

12-S&W1-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Outline of syllabus:

  1. Static games with complete information

    • Concept of a game

    • Solution concepts and the Nash equilibrium

    • Continuous strategy sets

    • Nash equilibrium in mixed strategies

  2. Dynamic games with complete information

    • Subgame perfect Nash equilibrium

    • Repeated games

  3. Static games with incomplete information: Bayesian Nash equilibrium

  4. Dynamic games with incomplete information

    • Perfect Bayesian Nash equilibrium

    • Signaling games

Intended learning outcomes

Students which complete this course will be able to

  1. explain different equilibrium concepts (Nash equilibrium, subgame perfect equilibrium, bayesian equilibrium, perfect bayesian equilibrium);

  2. explain for which kind of strategic situation each of these equilibrium concepts were developed;

  3. apply these concepts to simple realistic strategic situations;

  4. choose the appropriate equilibrium concept which fits best to a given strategic situation.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in


Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Competition Policy

12-S&W2-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Content:

German and European Competition Policy illustrated by real world cases of the Competition Protection Office.


Outline of syllabus:

  1. History of economic thought on competition and mission statements

  2. Overview of German and European competition law

  3. Fundamentals of industrial economics

  4. Classic cartels

  5. Tacit collusion

  6. Horizontal mergers

  7. Joint ventures

  8. Abuse of dominant positions: price level

  9. Abuse of dominant positions: price discrimination

  10. Vertical restraints

  11. Vertical mergers


Reading:

Schulz: Wettbewerbspolitik, Tübingen.

Intended learning outcomes

After completing the course students are able to

  1. recognize the potential of lessening competition due to certain practices by firms;

  2. argue by using results from industrial economics why certain practices hinder competition;

  3. understand decisions of the Bundeskartellamt and of the European Commission and evaluate such decisi-

ons from an economic point of view.

Courses (type, number of weekly contact hours, language — if other than German)

V (3) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 to 90 minutes) or

  2. term paper (approx. 10 pages) and presentation (approx. 15 minutes), (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Economics of Regulation

12-S&W3-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Outline of syllabus:

  1. Repetition of micro skills

    • Definitions and basic concepts

    • Market analysis

  2. Introduction to regulation theory

    • The regulatory process

    • The natural monopoly

    • Optimal pricing of natural monopoly

    • Privatisation

  3. Practice of economic regulation

    • Past and recent experience in Europe and around the world

    • Analysis of selected naturally monopolistic markets

This course will be taught in English.

Intended learning outcomes

The aim of this course is to provide the students with an understanding of the economic analysis that underpins competition policy and regulatory policy towards network utilities and to provide them with some institutional background.

Upon successful completion of this module the students will

(i) acquire an understanding of the underlying reasons why some markets cannot be made competitive; (ii)acquire a knowledge of the economic principles that lie behind the application of competition policy and utility regulation;

  1. develop an understanding of the ways in which economic analysis can positively inform competition policy and utility regulation, and the limitations of economic analysis in this context;

  2. learn from the practical experiences of market regulation and deregulation of the last 20-30 years.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 to 120 minutes) or

  2. term paper (approx. 10 pages) and presentation (approx. 15 minutes), (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Competition and Strategy

12-S&W-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course covers selected topics from the field of industrial economics. Students will be expected to independently work on a topic, submit a written piece of work and present their findings orally.

Intended learning outcomes

Students are able to independently investigate and classify scientific publications on their relevance to a given theme. In addition, they are able to present the results orally and in writing by conventional scientific standards.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 20 minutes), (weighted 2:1) Language of assessment: German and/or English

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Business Strategy for Information and Network Industries

12-BSINI-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Outline of syllabus:

  1. Pricing of information goods

    • market segmentation methods

    • digital rights management and piracy

    • alternative monetisation strategies

  2. Network effects

    • consumer demand in markets with network effects, rational expectations

    • monopoly pricing

    • competition in markets with network effects

    • compatibility and multi-homing: dynamic competition

  3. Competition in markets with switching costs

  4. Two (multi)-sided markets and platforms

    • monopoly pricing in platform markets

    • competition in platform markets: non-price strategies

The course will be taught in English.

Intended learning outcomes

After successful completion of this class, the students should be familiar with issues arising in many of the increasingly important hi-tech industries. They will be able to comment on emerging selling mechanisms for books, music and video. They will be able to explain the underlying logic for observed pricing patterns for software products, social media sites and the services found in the so called sharing economy. They will not only be able to understand observed behavior in information goods markets, industries which exhibit network effects and platform markets but will be able argue for new strategies in light of the specific features a market/product may exhibit.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60-120 minutes) or

  2. term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 185 / 326


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Industrial Organization

12-IIO-212-m01

Module coordinator

Module offered by

holder of the Chair of Industrial Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

The purpose of this course is to provide an introduction to the main concepts and analytical tools of the theory of industrial organisation. Industrial organisation studies examine how firms interact and compete with each other in the market. The focus is predominantly on markets characterised by imperfect competition (so-called oligopoly competition), i. e. markets where firms can exercise market power.


Outline of syllabus:

  1. Games and strategy

  2. Oligopoly

  3. Product differentiation

  4. Dynamic and repeated games

  5. Collusion

  6. Market structure, entry and exit

  7. Mergers

  8. Vertical relations

  9. Strategic behaviour by incumbent firms


This course will be taught in English.

Intended learning outcomes

The purpose of this course is to provide an introduction to the main concepts and analytical tools of the theory of industrial organization. Industrial organization studies how firms interact and compete with each other in the market. The focus is predominantly on markets characterized by imperfect competition, i.e. markets where firms

can exercise market power. Students who complete this course will be able to comprehend and use simple game theoretic models of oligopoly competition. By using these models, they will be able to understand and suggest managerial policies. They will be able to comment on governmental remedies in case of market failure within the context of the existing competition laws.


This course will be taught in English.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 to 120 minutes) or

  2. term paper (approx. 10 pages) and presentation (approx. 15 minutes), weighted 2:1

Language of assessment: German and/or English

Allocation of places

--

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Public Policy

12-WiPo-G-212-m01

Module coordinator

Module offered by

holder of the Chair of Economic Order and Social Policy

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + T (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. portfolio (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Labour Economics

12-A&S-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Economic Order and Social Policy

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This course offers an introduction to labour economics and social policy.


Outline of syllabus:

  1. Worlds of welfare capitalism

  2. Labour economics

  3. Social policy


Basic reading:

Sapir, A. (2005): Globalisation and the Reform of the European Social Models, Brussels. Franz, W. (2009): Arbeitsmarktökonomik, 7th edition.

Wagner, T./Jahn, E.J. (2004): Neue Arbeitsmarkttheorien, 2nd edition. Ehrenberg, R.G./Smith, R.S. (1996): Modern Labor Economics, 6th edition. Breyer, F./Buchholz, W. (2009): Ökonomie des Sozialstaats, 2nd edition.

Lampert, H./Althammer, J. (2004): Lehrbuch der Sozialpolitik, 7th edition.

Intended learning outcomes

The students analyze the function of the labor market and get an impression of relevant aspects in social policy. The students are able to illustrate the underlying theoretical models, can interpret them economically and apply to the current situation.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. portfolio (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in


Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Labour Economics

12-LES-211-m01

Module coordinator

Module offered by

Holder of the Chair of Labor Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course provides an introduction into modern labor economics. The lecture will cover the following three core topics:


I. Structure of the labor market

  1. Labor supply

  2. Labor demand

  3. Labor market equilibrium


The objective of this part is to provide an understanding of the determinants of labor supply and labor demand and how they match and finally reach an equilibrium. This also implies studying the design and effects of policy interventions in order to combat inefficiencies.


II. Wage formation

  1. Human capital formation

  2. Compensating wage differentials

  3. Discrimination

  4. Wage structure and inequality


The objective of the second part to investigate the different determinants of wages and to understand the reasons (justified or unjustified) why some people earn more than others.

III. Unemployment

The third and last part of the lecture deals with one of the biggest challenges to policy makers: unemployment.

Intended learning outcomes

Participants will be familiarized with the core theoretical models of modern labor economics and the basic methods of modern empirical labor economics. As such the course will be divided into two parts: the lecture where the theory is taught as well as the exercise class which are „hands on“ sessions in order to be able to conduct an economic analysis both theoretically as well as empirically.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 3:2 Language of assessment: German and/or English

Allocation of places

--

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Public Finance

12-Fiwi-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Public Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire an in-depth understanding of specific problems discussed in "Makroökono-mik II" ("Macroeconomics II") and "Mikroökonomik III" ("Microeconomics III"). The course will use scientific economic journal articles in German and English language.

Intended learning outcomes

After completing this module, students

  1. consolidate what they have learned and if necessary apply additional techniques of scientific work;

  2. create, present and defend a research paper;

  3. deal with the working papers of other participants;

  4. are better prepared for the processing of the bachelor thesis.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 25 minutes), weighted 2:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Computational Economics

12-CE-212-m01

Module coordinator

Module offered by

holder of the Chair of Public Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module introduces students to the numerical implementation of economic models. It consists of three main parts:

  1. The programming language FORTRAN 90

  2. Numerical solution methods

  3. Economic applications:

    • The static general equilibrium model

    • Topics in finance and risk management

    • Life cycle model

    • Overlapping generations model

Intended learning outcomes

After finishing this module students are able to

  1. implement simple economic models on the computer using Fortran 90

  2. using MonteCarlo techniques to find optimal portfolio structures and option prices

  3. quantify the risks of portfolios of banks and insurance companies

  4. simulate simple reforms of the tax and transfer system

  5. interpret the simulation results economically.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) and exercises (approx. 10 pages), (weighted 1:1) Language of assessment: German and/or English

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021)


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Practice of Data Analysis

12-PD-152-m01

Module coordinator

Module offered by

Holder of the Chair of Econometrics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Daily work in all areas of business - companies, science, institutions and politics - is based on the acquisition, processing and analysis of various data. These must be collected or generated and then processed and analyzed. In addition, data-based processes and business models offer many opportunities and challenges. The course covers the above mentioned topics and includes a theoretical and a practical part. In the theoretical part, basic knowledge in dealing with data, empirical work and the statistical software R will be taught. In the practical part of the research seminar webinars & field trips are offered.

Intended learning outcomes

Students able to apply statistical methods to collect numerical data.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 pages) and presentation (approx. 20 minutes), weighted 2:1

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Master's degree (1 major) China Business and Economics (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021)


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Computerlab - Applied Econometrics

12-CQW-212-m01

Module coordinator

Module offered by

holder of the Chair of Econometrics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module builds on the lectures "Grundlagen der Statistik" ("Descriptive Statistics and Introduction to Probability") and "Grundlagen der QWF" ("Introduction to Statistical Inference and Regression Analysis"). It introduces students to the simulation of different distributions and the application of linear regression analysis.

In the first part of the course, different distributions are introduced, simulated with Excel and their theoretical moments are estimated. In the second part, linear regression analysis is introduced, different specifications are

estimated and interpreted and potential pitfalls are pointed out.

Intended learning outcomes

After finishing this course students acquired several skills. They

  1. get an overview of several distributions;

  2. know how to simulate those distributions in MS Excel and are able to estimate and interpret the related theoretical moments;

  3. can perform smaller simulations in Excel;

  4. get to know a variety of different Excel commands which are important for statistical working;

  5. are introduced to the linear regression analysis, can perform it in Excel and Gretl, and know how to interpret

the results.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 pages) and presentation (approx. 20 minutes), weighted 2:1

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Economathematics (2021)


Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Econometrics

12-QWF-FS-212-m01

Module coordinator

Module offered by

holder of the Chair of Econometrics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module will take the form of a seminar. Participants will independently work on a subdomain of applied quantitative economics, either theoretically or applying the techniques they have acquired in an empirical study.

Intended learning outcomes

Students acquire the ability to work independently on a given topic in applied quantitative economics, write a summary, and present it to and discuss it with other seminar participants.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 25 minutes), (weighted 2:1)

Allocation of places

15 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Economic Principles of Risk Management

12-Risk-152-m01

Module coordinator

Module offered by

Holder of the Chair of Economics, Information and Contract Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

graduate

--

Contents

Rational decisions under uncertainty

  1. Measures of risk aversion

  2. Mean preserving spread

  3. Axiomatic foundations of the expected utility hypothesis (Neumann/Morgenstern, Savage)

  4. Insurance contracts

  5. Optimal portfolios

  6. Adverse selection

  7. Moral Hazard

  8. Experimental evidence and alternative approaches

Intended learning outcomes

After completing the course students are able to

  1. explain the results of the economic theory of decisions under risk,

  2. apply the involved methods to given simple examples on their own,

  3. recognise, in which real life situations and how the results can be applied.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: German and/or English creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 202 / 326


Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 203 / 326


Module title

Abbreviation

Insurance Markets

12-VM-152-m01

Module coordinator

Module offered by

Holder of the Chair of Economics, Information and Contract Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Asymmetric information makes insurance markets different from common goods markets. Research questions and methods thus have to take these special features into account. Typical subjects covered in the course:

  1. Demand for insurance

  2. Supply of insurance

  3. Adverse selection in insurance markets

  4. Moral hazard in insurance markets

  5. Empirical assessment of information problems

  6. Informal insurance schemes

  7. Insurance and bounded rationality

Intended learning outcomes

After completing the course students are able to

  1. explain the essential results of the economic analysis of insurance markets,

  2. apply the involved methods to given simple examples on their own,

  3. recognise, in which real life situations and how the results can be applied,

  4. analyse the impact of certain insurance contracts on market outcomes.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 204 / 326


Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Economics of Information

12-IÖ-152-m01

Module coordinator

Module offered by

Holder of the Chair of Economics, Information and Contract Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

During the 1960/70s, microeconomic theory came to acknowledge that many (if not most) economic transactions are characterized by asymmetric distribution of information – i.e., at least one of the parties participating in a transaction usually is privy to information that the remaining parties do not have access to. This asymmetric distribution of information subsequently was recognized to be a major impediment for transactions to be economically efficient. Contract theory addresses the question how the inefficiencies arising from asymmetric distribution of information can best be mitigated by appropriate design of the contractual (or, more generally, institutional) framework that governs the transaction under consideration. This lecture covers the baseline models of “moral hazard” (i.e., situations where one party has private knowledge after a contract has been signed) and

“adverse selection” (i.e., situations where one party has private knowledge before a contract is signed). As applications we will address questions discussed in organizational, personnel or industrial economics, such as incentive design within organizations or the design of labor law regulations and competition laws.


Even though we will work with precise mathematical formalizations of the ideas that we want to think and talk about, this course requires little more than a solid understanding of basic differential calculus. More important than having a solid mathematical background is having a strong interest in formal economic analysis and fun with logical thinking and puzzle solving.


The exposition is primarily based on the following textbook:

  • Laffont und Martimort (2002): "The Theory of Incentives"

Intended learning outcomes

After completing the course students will be able to

  • explain essential findings of contract theory,

  • apply the involved methods to given stylized examples on their own,

  • interpret the properties of real-life contracts as the outcome of the interaction between two or more contracting parties in the presence of asymmetric information,

  • evaluate government interventions with regard to their effect on the efficiency properties of the interaction

between the contracting parties.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

--

Additional information

--

Workload

150 h


Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Master's degree (1 major) China Business and Economics (2016)

Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Master's degree (1 major) China Business and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Decision Making and Incentive Design

12-IAO-212-m01

Module coordinator

Module offered by

holder of the Chair of Economics, Information and Contract Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This seminar covers the following special topics in organisational economics:

  • Hidden costs of control - theory and evidence

  • Reciprocity and incentives - experimental evidence

  • Task meaning, respect, and performance effects - experimental evidence

  • Leadership - theory and evidence

Intended learning outcomes

Drawing on current cutting-edge research, students are enabled to critically and independently analyze current research questions and to learn and apply research methods. The seminar style of the course teaches them to present their own seminar papers and research both in written and in oral form. Students are enabled to critically analyze and discuss the work of their peers.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Module taught in: German and/or English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Term paper (approx. 10 pages) and presentation (approx. 20 minutes), (weighted 2:1) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 208 / 326


Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)



Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 209 / 326


Module title

Abbreviation

Business Cycle Analysis

12-Konj1-F-212-m01

Module coordinator

Module offered by

holder of the Chair of Monetary Policy and International Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course will introduce students to the theory of business cycle dynamics. Capitalist based economies are subject to pronounced cycles of economic booms and busts. In this course, we will find out why! Kicking off the lecture, we will look at some stylised empirical facts of business cycles. Afterwards, we will give a structural interpretation, focusing in particular on housing and asset markets and their role for the business cycle. We will also take a closer look at investment, one of the main cycle-makers. Afterwards, we will ask the question of how monetary and fiscal policy can safeguard the business cycle. Special attention will be given to the euro area. We will also invite an expert to give a practical introduction to business cycle indicators.

Intended learning outcomes

The course offers an introduction into a vast array of analytical tools. Students

  1. are exposed to 1st and 2nd order difference equations and learn how to solve them;

  2. learn how business cycle indicator are constructed;

  3. are supplied with up to date knowledge on the interaction of business cycles, asset markets and economic

policy which enables them to critically access contemporaneous policy.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (as group or individual work, approx. 10 pages each person) or

  3. oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 210 / 326


exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Business cycles, corporate finance and asset markets

12-KUV-211-m01

Module coordinator

Module offered by

Head of the Work Group of Empirical Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The modul is located in the nexus of business cycles, corporate finance and asset markets. Being located at the intersection between economics and finance the modul adresses the interaction between business cycles, corporate fiannce and aset markets. Concretely students can work on subjects like „what is the impact of interest rate changes by the central bank on the housing market“, „how do asset markets and household consumption interact“ and „what is the interrelationship bewtween financing conditions and the business cycle“. From a methodological point of view the course targets to built on existing methological toolkits aquired during the bachelor studies. Students are guided to deepen their understanding on those toolkits to analyze data and to generate results.

Intended learning outcomes

The modul equips students with the necessary tools to analyze data to generate results on topics of interest. Besides students need to present their findings and communicate their results to other studends.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 pages) and presentation (approx. 25 minutes), weighted 2:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019)

Bachelor' degree (1 major) Business Information Systems (2020)


Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

European Macroeconomics

12-EM-211-m01

Module coordinator

Module offered by

Holder of the Senior Professorship for Economics, Money and International Economic Relations

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course focuses on the macroeconomics of the euro area. It is based on a theoretical part which provides a critical presentation of the two core macroeconomic paradigms: the (neo)classical approach and the Keynesian approach. This allows a comparative analysis of policy implications for important macroeconomic topics (unemployment, inflation, government debt, financial system). The policy-oriented part discusses the monetary policy of the ECB and the challenges for fiscal policy in the euro area, which are due to the lack of fiscal policy integration. The course will also present other euro area specific topics (e.g. Optimum currency area, euro crises, Next Generation EU).

Intended learning outcomes

After completing this course, students will have gained a profound understanding of (applied) macroeconomic policies in general and specifically in the EMU. The students will have a deeper understanding of the two core macroeconomic models and their application for economic policy by using empirical data. Thus, they will enhance their general macroeconomic understanding by applying it to real world problems. In addition, students will develop a sound knowledge of the institutions of common fiscal and monetary policy in Europe.

Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) Written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes); (weighted 2:1) or c) oral examination (approx 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 214 / 326


Module studies (Bachelor) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Module studies (Bachelor) Orientierungsstudien (2020)

Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 215 / 326


Module title

Abbreviation

Challenges of China’s Economic Rise

12-CCER-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course will be taught in English.Over the last 30 years, China has experienced an unprecedented economic growth period. This economic success is awesome and challenging at the same time. Within this seminar we take a look at a selection of challenges resulting from China's economic rise. We look into challenges arising within China, but also into selected international ones. We approach the challenges by first looking at how they have been discussed in Western media. Starting from there we look 'behind the curtain' to analyse the topics and debates more in-depth in the context of China's economic rise and relevant economic theories. To attend this class you do not need ex ante knowledge about China. You should, however, be willing to read texts, also academic texts, in English language. Apart from reading, participants of the seminar are expected to prepare inputs for the seminar and to participate in class discussion. The seminar ends with a written examination.

Intended learning outcomes

Students of the seminar gain knowledge about China and its global relevance. In addition they learn how the experiences of an emerging markets at times defy mainstream economic theory.

Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 15 to 20 pages) and presentation (approx. 10 to 15 minutes), (weighted 2:1)

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Module studies (Bachelor) Business Management and Economics (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 216 / 326


Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Introduction to Business Journalism

12-EWJ-192-m01

Module coordinator

Module offered by

Holder of the Professorship of Economic Journalism

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course provides a practical introduction to the functions and goals of business journalism and gives an initial overview of the subject area of journalism. The focus is on the following questions: What is communication? What are the special features of business journalism? How does one communicate complex economic-political contexts? What needs to be taken into account when providing information and conducting research? How are sources handled in journalism? How are journalistic products such as a report or news item or a report written? How does storytelling work? What is the most efficient way to disseminate journalistic products? What comprises the field of journalistic ethics?

Intended learning outcomes

Through practical exercises, students learn about different forms of presentation and gain insight into research techniques. After completing the "Introduction to Business Journalism" module, students are able to comprehend and evaluate the work of journalists and likewise write journalistic products independently.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Portfolio (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019)


Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Crossmedia Storytelling in Business Communication

12-CWK-192-m01

Module coordinator

Module offered by

Holder of the Professorship of Economic Journalism

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Online and cross-media journalism takes into account the current media convergence. This seminar focuses on the individual elements and phases of production for the website, Facebook, Instagram, Twitter, and Tiktok against the background of current trends and developments. In addition, the seminar covers current trends in journalism. In addition to content-related topics, the focus is also on new methods (e.g. of storytelling), as well as technical developments.

Intended learning outcomes

After successful completion, students will be able to name the individual phases of online and cross-media journalism and carry them out on sample projects, explain and go through the individual production stages, use methods and tools for the individual steps.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Portfolio (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

20 places.

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 220 / 326


Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Seminar: Business Journalism and Business Communication

12-WUW-211-m01

Module coordinator

Module offered by

Holder of the Professorship of Economic Journalism

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This seminar is offered as a preparatory seminar for the bachelor thesis. Basic scientific knowledge is taught. The focus is on the goal of independently preparing a well-founded scientific thesis. For this purpose, the individual steps from the generation of a research question to the actual survey are explained. In addition, an overview of scientific writing is provided.

Intended learning outcomes

Upon completion of the seminar, students will be able to independently prepare a scientific paper.

  • Consolidation of the learned and, if necessary, application of further techniques of scientific work

  • Preparation, presentation, and defense of a scientific paper

  • Examination of the working papers of other seminar participants

  • Preparation for the Bachelor and Master Thesis

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 10 to 15 pages) and presentation (approx. 15 minutes); (weighted 1:1) Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019)

Bachelor' degree (1 major) Business Information Systems (2020)


Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Managerial Practice Lectures

12-VGP-192-m01

Module coordinator

Module offered by

Holder of the Professorship of Economic Journalism

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this lecture, we invite board members of publicly listed companies, SMEs and Startups to discuss contemporary challenges of corporate management.


Students gain sustainable insights into current management practices, challenges of corporate management in various industries, and discuss pressing managerial issues with C-level executives. In individual and group assignments, students are required to connect management theories with the managerial challenges of the speakers.


Managers of the different companies are required to address the following questions that will foster a detailed discussion at the end of each lecture:

  • What are the current challenges facing your company?

  • Which strategies do you employ to respond to these challenges?

  • How have leadership concepts and approaches changed in your company?

Intended learning outcomes

After participating in this module, students should be able to combine theoretical approaches with current challenges in management. The students obtain a realistic insight into a cross-section of the German economy.

Through discussions reports and group presentations students’ social skills are trained in addition to professio-

nal skills.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Portfolio (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015)


Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Economist Practice Lectures

12-VWP-211-m01

Module coordinator

Module offered by

Holder of the Senior Professorship for Economics, Money and International Economic Relations

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The content of the seminar is the active participation in as well as the follow-up of the lectures of economists from different national and international fields of activity, which are organized for the event.


The invitation of speakers from practice strengthens the practical orientation of the scientifically founded and at the same time internationally oriented education at the faculty of economics of the University of Würzburg.

In this way, students will gain lasting insights into the fields of activity of economists, gain an insight into practical activities, discuss these with high-ranking economists and combine them with theoretical economic knowledge gained during their studies.

Intended learning outcomes

By participating in the seminar, Master's students of the faculty of economics and business administration should get to know the different fields of activity of economists and the questions that determine the daily work of the speakers in the course of the lectures.

In addition, the participants of the seminar will have the opportunity to apply the knowledge of economics they have acquired during their studies. For this purpose, in addition to a discussion with the speakers following the respective lecture, a debating workshop is offered to the participants of the seminar, in which the students are to learn economic argumentation and debate management. The learned contents and competencies will be tested at the end of the semester.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) oral examination (approx 30 minutes) or b) term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1) or c) written examination (approx. 60 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 226 / 326


Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2015) Bachelor' degree (1 major) Business Information Systems (2016)

Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2020)

Master's degree (1 major) China Business and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor's degree (1 major, 1 minor) Business Management and Economics (Minor, 2023)


Module title

Abbreviation

Selected Topics in Economics 1

12-APV1-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (approx. 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Selected Topics in Economics 2

12-APV2-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or c) oral examination (approx. 20 minutes)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)


Computer Science

(max. 25 ECTS credits)


Module title

Abbreviation

Knowledge-based Systems

10-I-WBS-152-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science VI

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Foundations in the following areas: knowledge management systems, knowledge representation, solving methods, knowledge acquisition, learning, guidance dialogue, semantic web.

Intended learning outcomes

The students possess theoretical and practical knowledge for the understanding and design of knowledge-based systems including knowledge formalisation and have acquired experience in a small project.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

§ 22 II Nr. 3b

Module appears in

Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Aerospace Computer Science (2015)

First state examination for the teaching degree Gymnasium Computer Science (2015) Bachelor' degree (1 major) Business Information Systems (2016)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016)

Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Computer Science (2017)


Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)

Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020) Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Data Mining

10-I-DM-152-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science VI

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Foundations in the following areas: definition of data mining and knowledge, discovery in databases, process model, relationship to data warehouse and OLAP, data preprocessing, data visualisation, unsupervised learning methods (cluster and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, SVM), learning methods for special data types, other learning paradigms.

Intended learning outcomes

The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of data mining and machine learning. They are able to solve practical knowledge discovery problems with the help of the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use or implementation of data mining algorithms.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

§ 22 II Nr. 3b

Module appears in

Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Aerospace Computer Science (2015)

First state examination for the teaching degree Gymnasium Computer Science (2015) Bachelor' degree (1 major) Business Information Systems (2016)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 233 / 326


Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2016) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2019)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)

Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020) Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Master's degree (1 major) Information Systems (2022)

Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Operating Systems

10-I-BS-191-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science II

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Introduction to computer systems, development of operating systems, architecture principles, interrupt processing in operating systems, processes and threads, CPU scheduling, synchronisation and communication, memory management, device and file management, operating system virtualisation.

Intended learning outcomes

The students possess knowledge and practical skills in building and using essential parts of operating systems.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Module taught in: English

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Computer Science (2019) Master's degree (1 major) Nanostructure Technology (2020) Master's degree (1 major) Physics (2020)

Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) Physics International (2020)

Master's degree (1 major) Quantum Engineering (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Master's degree (1 major) Quantum Technology (2021)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Advanced Programming

10-I-APR-172-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science II

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler programs. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and code a sensible structure. Also, further topics in the areas of software security and parallel programming are discussed.

Intended learning outcomes

Students learn advanced programming paradigms especially suited for space applications. Different patterns are then implemented in multiple languages and their efficiency measured using standard metrics. In addition, parallel processing concepts are introduced culminating in the use of GPU architectures for extremely quick processing.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Computer Science (2019) Module studies (Bachelor) Computer Science (2019) Master's degree (1 major) Nanostructure Technology (2020) Master's degree (1 major) Physics (2020)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020) Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 237 / 326


Bachelor' degree (1 major) Business Information Systems (2020) Master's degree (1 major) Physics International (2020)

Master's degree (1 major) Quantum Engineering (2020)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Master's degree (1 major) Quantum Technology (2021)

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Digital computer systems

10-I-RAL-152-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science V

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Introduction to digital technologies, Boolean algebras, combinatory circuits, synchronous and asynchronous circuits, hardware description languages, structure of a simple processor, machine programming, memory hierarchy.

Intended learning outcomes

The students possess a knowledge of the fundamentals of digital technologies up to the design and programming of easy microprocessors as well as knowledge for the application of hardware description languages for the design of digital systems.

Courses (type, number of weekly contact hours, language — if other than German)

V (4) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 to 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

creditable for bonus

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Aerospace Computer Science (2015) Bachelor' degree (1 major) Aerospace Computer Science (2017) Bachelor' degree (1 major) Computer Science (2017)

Bachelor' degree (1 major) Computer Science (2019) Module studies (Bachelor) Orientierungsstudien (2020)

Master's teaching degree Gymnasium MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)

Supplementary course MINT Teacher Education PLUS, Elite Network Bavaria (ENB) (2020)


Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020) Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Module title

Abbreviation

Introduction into Human-Computer Interaction

10-I-MCS-191-m01

Module coordinator

Module offered by

holder of the Chair of Computer Science IX

Institute of Computer Science

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

No information on contents available.

Intended learning outcomes

No information on intended learning outcomes available.

Courses (type, number of weekly contact hours, language — if other than German)

V (3) + Ü (1)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 120 minutes).

If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (approx. 15 minutes per candidate).

Language of assessment: German and/or English

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Computer Science (2019)

Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Mathematical Data Science (2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023)


Key Skills Area

(20 ECTS credits)


General Key Skills

(5 ECTS credits)


Subject-specific Key Skills

(15 ECTS credits)


Module title

Abbreviation

Internship (about 4 weeks, graded)

12-Prak1-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes a placement with a duration of approximately 4 weeks at a company or other organisation in the area of economics as well as the subsequent presentation of the placement report.

Intended learning outcomes

Students have the knowledge of relevant practical problem areas and the ability to implement the knowledge acquired in the course of study.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

report on practical course (approx. 10 pages) and presentation (approx. 20 minutes), weighted 2:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Internship (about 4 weeks, not graded)

12-Prak2-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes a placement with a duration of approximately 4 weeks at a company or other organisation in the area of economics as well as the subsequent presentation of the placement report.

Intended learning outcomes

Students have the knowledge of relevant practical problem areas and the ability to implement the knowledge acquired in the course of study.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

report on practical course (approx. 10 pages) and presentation (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Internship (about 8 weeks or more, graded)

12-Prak3-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes a placement with a duration of approximately 8 weeks at a company or other organisation in the area of economics as well as the subsequent presentation of the placement report.

Intended learning outcomes

Students have the knowledge of relevant practical problem areas and the ability to implement the knowledge acquired in the course of study.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

report on practical course (approx. 15 pages) and presentation (approx. 20 minutes), weighted 2:1

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Internship (about 8 weeks or more, not graded)

12-Prak4-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

10

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes a placement with a duration of approximately 8 weeks at a company or other organisation in the area of economics as well as the subsequent presentation of the placement report.

Intended learning outcomes

Students have the knowledge of relevant practical problem areas and the ability to implement the knowledge acquired in the course of study.

Courses (type, number of weekly contact hours, language — if other than German)

P (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

report on practical course (approx. 15 pages) and presentation (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Student Teaching Assistant 1

12-Tut1-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes tutoring activities in a tutorial offered by a Chair at the Faculty of Business Management and Economics.

Intended learning outcomes

Students have the ability to guide a group, to present content understandable and to develop training materials.

Courses (type, number of weekly contact hours, language — if other than German)

Ä (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 15 to 25 pages) and presentation (approx. 90 minutes), weighted 1:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Student Teaching Assistant 2

12-Tut2-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module includes tutoring activities in a tutorial offered by a Chair at the Faculty of Business Management and Economics.

Intended learning outcomes

Students have the ability to guide a group, to present content understandable and to develop training materials.

Courses (type, number of weekly contact hours, language — if other than German)

Ä (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 15 to 25 pages) and presentation (approx. 90 minutes), weighted 1:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Bachelor Orientation Tutorial

12-BOT-192-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

2

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

When starting their programmes, many Bachelor's degree students feel overwhelmed by the new environment, new people and completely new learning conditions. This is why the Bachelor's orientation programme (BOT) was created. Topics covered in the orientation programme:

  • Orientation at the Faculty and University

  • Structure, content and requirements of the degree programme

  • Planning your university education

  • Subject-specific learning and study techniques

  • Exam preparation including time management

Intended learning outcomes

Within the orientation program first-year student get information and assistance to both professionally, and socially to be guided through the faculty in several meetings. The aim is to deal with issues, questions and problems, which experience shows occur especially at the start of their studies, and prepare students optimally for the start of their individual studies.

Courses (type, number of weekly contact hours, language — if other than German)

T (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Presentation (approx. 5 minutes)

Assessment offered: Once a year, winter semester

Allocation of places

--

Additional information

--

Workload

60 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)


Module title

Abbreviation

Introduction to Scientific Work

12-WA-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The following topics will be covered:

  • Introduction to the subject: explanation of terms, purpose and benefits of academic writing and research

  • Stages of academic writing and research:

  • Stage 1 : orientation and planning

  • Stage 2 : collecting and evaluating material

  • Stage 3 : writing a draft

  • Stage 4 : revision and submission

  • Time management

  • Presentation

Intended learning outcomes

Students acquire knowledge of scientific methods. Many chairs and departments of the faculty recommend to participate or expect successful participation ahead of the application process for the bachelor thesis.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Written elaboration (approx. 5 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Seminar: Cross-Cultural Management 1 - Introduction to Cross-Cultural Management

12-EinCCM-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This course provides students with the necessary background knowledge and an overall understanding of culture and prepares them for the course "Wenn Kulturen aufeinander treffen - Führen zwischen den Kultu-

ren" ("When Cultures Collide -- Leading Across Cultures"). The series of courses is taught on the basis of the context of daily international business and is filled with many international business scenarios, simulations and case studies.


Outline of syllabus:

  1. Culture and its origins - the roots and routes of culture

  2. How culture is influenced by climate and religion

  3. Cultural black holes

  4. Culture and globalisation

  5. Life after September 11th

  6. The categorisation of cultures

Intended learning outcomes

Students have gained a deeper understanding and background of what culture is and where culture comes from. They have learned about their culture in order to gain insight into their own individual cultural make-up.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

35 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Cross-Cultural Management 2 - Leading Across Cultures

12-VerCCM-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This is the intermediate module of the Cross-Cultural Management series. On the surface, communication appears to be a relatively simple operation requiring two basic components -- a speaker and a listener. This module focuses mainly on the world of business and tackles head on the issues and problems of international exchanges. The series is taught on the basis of the context of daily international business and is filled with many international business scenarios, simulations and case studies. Reading includes the texts "Wenn Kulturen aufeinander treffen - Führung zwischen Kulturen" ("When Cultures Collide -- Leading Across Cultures") and "Cross-Cultu-ral Communication - Ein visueller Ansatz" ("Cross-Cultural Communication -- A visual Approach"). "For a German and a Finn, the truth is the truth. In Japan and Britain, it is all right if it doesn't rock the boat. In China, there is no absolute truth. In Italy, it is negotiable." The course will look at the link between values and communication and at how cultural messages unconsciously filter through into the language we use to influence others and how our words may have a different impact than intended which often times can lead to misunderstanding and a loss of trust and business.

Outline of syllabus:

  1. Brief review of the origins of culture

  2. Status, leadership & organisation

  3. Team building & horizons

  4. Motivating people & trust

  5. Business meetings

  6. Introduction to 80 cultures in 8 regions of the world

Intended learning outcomes

Students have continued to deepen their understanding of culture including their own personal cultural background. Students have gained a heightened awareness of the importance of cross-cultural competence and the dangers of relying on culturally bound intuitions.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--


Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

China: Business location and trading partner

12-IBL-SG-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module will discuss reasons as well as implications of the globalisation of our society, both from the point of view of private persons and from the point of view of companies. Current examples from the media will be used to illustrate the impact of globalisation on everyday life.

Intended learning outcomes

The students will know how globalization influences both, the private life of people as well as the conditions under which companies can perform their businesses. Accordingly, they will be able to discuss the issue of globalization based on advanced knowledge.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or

  3. presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

  4. term paper (approx. 20 pages)

Allocation of places

30

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 257 / 326


Bachelor' degree (1 major) Business Management and Economics (2023)



Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 258 / 326


Module title

Abbreviation

India: Business location and trading partner

12-WSI-212-m01

Module coordinator

Module offered by

holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module introduces students to the economic development as well as economic policy in India. In addition, the course will discuss the general conditions for business investments and activities in India. To illustrate the topic and provide students with more in-depth insights, the course will also address current economic issues and their backgrounds.

Intended learning outcomes

The students will be able to discuss and evaluate the economic structures of India. They will have the abilities to analyze the development of the South-Asian economy by applying adequate methods and theories. Furthermore, students will gain a good understanding of the Indian culture and its influence on business relationships.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or

  3. presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

  4. term paper (approx. 20 pages)

Allocation of places

30 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 259 / 326


Module title

Abbreviation

Intercultural Business Competence

12-IKG-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This lecture discusses challenges of globalisation from an economic point of view. Based on a basic overview of leadership in a global world, the topic of multiculturality in a business context is discussed in detail. Simulations, case studies and exercises are used to illustrate relevant issues.

Intended learning outcomes

Students have gained a comprehensive understanding of relevant topics regarding globalization in the business context. In addition, students have learned how to interact with colleagues and business partners in a cross-cul-tural environment.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Allocation of places

30 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 260 / 326


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Intercultural Management 1

12-IM1-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module offers an introduction to intercultural management. It will sensitise students to the international world of business, in which an awareness of cultural differences is essential, and will thus prepare them for entering an international labour market. Having discussed globalisation as a context of justification and having put intercultural management in the context of international management, the course will introduce students to different concepts of culture and will investigate how international operations affect corporate culture. In addition, the course will discuss special forms of international cooperation, such as sending employees abroad. The course will not only equip students with the theoretical basics of intercultural management but will also provide them with an opportunity to apply the theories in practice, working on case studies and team exercises.

Outline of syllabus:

  1. Multiculturalism: a phenomenon in a global(ised) economy

  2. The phenomenon of culture

  3. Cultural dimensions

  4. Corporate culture

  5. Typical application situations

Intended learning outcomes

Students are able to evaluate key concepts, theories and models in intercultural management and have developed an in-depth understanding of their own cultural backgrounds as well as the cultural backgrounds of others. They understand how culture influences perception, both on an individual and on a collective level, and thus also impacts processes of perception in the world of work. The course places particular emphasis on enhancing the students’ intercultural skills.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Allocation of places

30 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Intercultural Management 2

12-IM2-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module will provide students with more in-depth insights into selected topics in intercultural management from an economic point of view. Students will prepare a term paper, exploring a topic in more detail.

Intended learning outcomes

The students have gained a deeper understanding of specific issues of intercultural management and will be able to communicate this verbally and in writing.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or b) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or c) term paper (approx. 20 pages)

Allocation of places

10 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)


Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Global Systems and Intercultural Competences - Economic Aspects of Globalization. An Introduction

12-EinGS-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module introduces students to the topic of "Global Systems" from an economic point of view. In addition to imparting factual knowledge about global connections, the course also focuses on issues of intercultural management.

Intended learning outcomes

Students have acquired a basic understanding of the underlying processes of globalization and are able to recognize the resulting requirements for individuals and companies. In particular, the students are sensitized of the importance and the influence of cultural differences in the business world.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Allocation of places

10 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor' degree (1 major) Business Information Systems (2020)


Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Global Systems and Intercultural Competences - Economic Aspects of Globalization - Advanced Level

12-VerGS-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Industrial Management

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Building on introductory courses, this module will provide students with more in-depth insights into the topic of #Global Systems# from an economic point of view. Students will prepare a term paper exploring a topic in more depth and will present the contents during the seminar.

Intended learning outcomes

The students have gained a deeper understanding of specific issues of globalization and will be able to communicate this verbally and in writing.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or b) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or c) term paper (approx. 20 pages)

Allocation of places

10 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 268 / 326


Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Economic and Business Ethics

12-WUE-152-m01

Module coordinator

Module offered by

Holder of the Chair of Financial Accounting

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The aim of the seminar is to provide students with an overview of business ethics. First, basic philosophical terms are clarified and important philosophical theories such as utilitarianism or discourse ethics are introduced. The course discusses how business ethics can be justified and what purpose it can serve. The seminar focuses on the question of what ethical challenges companies face and to what extent companies are moral agents and should include ethical considerations in their actions. Afterwards, the seminar discusses the relationship between the free market and morality and the role of the state for the frame order.

Intended learning outcomes

After finishing this course, the studenst should be able by using common scientific methods to write a seminar paper dealing with a selected ethcial problem in business. They should be able to present a complex problem in an clear and understandable way and they should discuss the own position with convincing arguments with other participants in the class.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) presentation (approx. 20 minutes) and written elaboration (approx. 15 to 20 pages), weighted 1:2

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Securities Management

12-WPM-192-m01

Module coordinator

Module offered by

Holder of the Chair of Corporate Finance

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Within the framework of this module, students are familiarized with the management of an investment portfolio. Each participant has to manage a special area, for which he/she presents the most important market events in a condensed form in each session and observes the securities account positions belonging to his/her special area. A securities account provided by Castell-Bank Würzburg is managed. Each participant has to prepare his own investment proposals and take part in the general discussion. Based on group discussions, investment decisions are made to buy and sell securities within the securities account. These investment decisions are based on risk considerations as well as tax aspects, which will be introduced to the participants during the course. Furthermore, in addition to macroeconomic topics closely related to securities investment, the course also focuses on the development of the real estate sector.

Intended learning outcomes

Upon completion of the securities seminar, students will be able to


  1. independently assess securities of different asset classes with regard to their risk/reward profile, both on an individual security level and in a portfolio context

  2. and present and discuss their assessments in a target group-oriented manner.

Courses (type, number of weekly contact hours, language — if other than German)

S (4)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

Presentation (approx. 60 minutes)

Allocation of places

20 places.

  1. Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.

  2. Places on all courses of the module with a restricted number of places will be allocated in the same procedure.

  3. A waiting list will be maintained and places re-allocated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015)


Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

exchange program Business Management and Economics (2022) Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

DATEV - Introduction to DATEV-Software for Tax Accounting

12-DAT-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Taxation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module will introduce students to processes regarding accounting, taxation, financial statements and the audit of these using the DATEV software. DATEV is one of the standard systems used by tax consultants and accountants. Students will not only become familiar with the basics, they will also acquire insights into the processes and functionalities. In the theoretical part, students will acquire the necessary skills that will serve as a basis for the practical part. This practical part will present students with an opportunity to apply their newly acquired knowledge by working with a DATEV system on case studies on the model company Müller & Thurgau GmbH.

Intended learning outcomes

Students acquire practical knowledge in using the DATEV software package for daily book-keeping and for producing annual reports.

Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

10 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

SAP ERP Human Capital Management

12-SAP-152-m01

Module coordinator

Module offered by

Holder of the Chair of Human Resource Management and Organisation

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This course will familiarise students not only with basic concepts but also with the processes and functions of SAP Enterprise Resource Planning Human Capital Management. In the theoretical part of the course, students will first acquire the knowledge and skills that will serve as a basis for the practical part. This practical part will then present students with an opportunity to apply what they have learned by working with an ERP system on case studies on the model company LIVE AG.

Intended learning outcomes

Goal of this course is to give students insights in the practical application and the possibilities and limits of SAP Enterprise Resource Planning Human Capital Management covering several human capital and organisation topics.

Courses (type, number of weekly contact hours, language — if other than German)

V (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes)

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 276 / 326


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 277 / 326


Module title

Abbreviation

Managerial Problem Solving

12-MPS-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Analytics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The course provides an introduction to data-based methods for modeling and solving quantitative business problems. In particular, Microsoft Excel is used to manage, visualize, and analyze data. In addition, mathematical optimization problems are solved using Excel Solver and the fundamentals of programming with VBA are discussed.

Intended learning outcomes

  1. Prepare, visualize and analyze data sets using Excel

  2. Select and forecast different time series problems

  3. Understand simple, multiple and dummy regressions

  4. Implement and solve linear optimization problems using the Excel Solver

  5. Fundamentals of Excel VBA programming

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) portfolio: completion of exercises (approx. 12 exercise sheets, approx. 3 pages each)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

40 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 278 / 326


Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 279 / 326


Module title

Abbreviation

Basics of Supply Networks

12-GSN-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

  1. Introduction

  2. Development of supply networks

  3. Structural and methodical deficits of classic order processing

  4. Collaborative networks

  5. Supply network models

  6. Five steps towards a collaborative network

  7. Demands on SNM solutions

  8. Architecture of SNM solutions

  9. Integration of SNM, ERP and CRM

Intended learning outcomes

This course provides the bases in the area Supply of Networks (SN) for students of the economic informatics and the economics.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or c) presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

d) term paper (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 280 / 326


Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 281 / 326


Module title

Abbreviation

Management of Supply Networks

12-MSN-192-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

  1. Execution of SCM projects

  2. Critical factors for success in SCM projects

  3. Effects of SCM on business processes

  4. Supply chain performance management/measurement

  5. Supply chain risk management

  6. New demands on firms and networks

Intended learning outcomes

This course advances students of the economic informatics and economics which already orders of grounding in the area Supply of Networks (cf. moreover the basis course "bases of the Supply Network"), to the management of Supply Networks and the duties linked with it and effects.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (approx. 15 pages) and presentation (approx. 15 minutes), weighted 2:1 or

  3. Presentation (approx. 45 minutes) and term paper (approx. 10 pages), weighted 1:1 or

  4. Term paper (approx. 20 pages)

Language of assessment: German and/or English

Allocation of places

--

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 282 / 326


Module title

Abbreviation

Professional Apply

12-PWS-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

2

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will learn how to be professional when applying and interviewing for jobs. Part 1: Application documents Topic 1: Cover letter Topic 2: Curriculum vitae Topic 3: Certificates and other documents Part 2: Job interview Topic 1: Preparation Topic 2: Typical structure Topic 3: Appearance and behaviour

Intended learning outcomes

Students are able to write a professional motivational letter, as well as an ideal CV, related on their professional field. They are also familiar with the typical process of a job interview and have skills to appear properly.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 5 to 10 pages) and presentation (approx. 15 minutes), weighted 1:1

Allocation of places

--

Additional information

--

Workload

60 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Professional Presentation

12-PPR-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

2

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

In this course, students will acquire professional presentation skills. Topic 1: structuring a presentation Topic 2: visual representation (PPP) Topic 3: professional appearance Topic 4: moderating discussions

Intended learning outcomes

Students are able to structure presentations useful and to illustrate them visually. Furthermore, they have the necessary rules for professional demeanor and appearance. They are able to moderate (critical) discussions profes-sionell.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

presentation (approx. 15 to 30 minutes)

Allocation of places

--

Additional information

--

Workload

60 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Management Case Studies

12-P&Ocase-F-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The module will focus on equipping students with the skills necessary for solving a variety of case studies. These case studies will focus on the practical application of theoretical knowledge for the solution of practical problems and will provide students with an opportunity to apply the management tools they were taught. A particular emphasis will be on equipping students with skills in the areas of strategic thinking and the operational implementation of strategies. Participants will be issued a certificate of attendance.

Intended learning outcomes

Students are able to solve case studies according to international standards.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written elaboration (approx. 5 to 10 pages) and presentation (approx. 20 to 30 minutes), weighted 1:1 Language of assessment: German and/or English

Allocation of places

16 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020)

Bachelor' degree (1 major) Business Information Systems (2021)


Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Managing interactive - Business Simulation Game

12-MIU-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Consolidation of business knowledge in virtually all functional areas (procurement/logistics, human resources, investment, finance, business planning, accounting etc.).

The module should make participants aware of the fact that business decisions require joined-up thinking between the different functional areas. The companies that participants are confronted with are fictitious but very close to reality. Participants will learn to understand the complexity of these companies as well as the business solutions and techniques applied by them. For a simulated period of time, participants will be required to make

autonomous decisions (in groups).

Intended learning outcomes

Students learn to apply the necessary data for corporate management methods and tools in concrete , simulated business situations.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) term paper (approx. 10 to 15 pages) and presentation (approx. 10 minutes), weighted 2:1 or d) presentation (approx. 20 to 30 minutes) or

e) project (approx. 20 hours)

Language of assessment: German and/or English

Allocation of places

20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 287 / 326


Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Project Management

12-PM-F-152-m01

Module coordinator

Module offered by

Holder of the Chair of Business Management and Business Information Systems

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Description:

This module will acquaint students with basic concepts and methods of project management and project planning with a special focus on IT projects.


The following contents will be covered:

  • Organisational forms in projects

  • Project management tasks

  • Project team and project responsibilities

  • Project planning (structure, schedule, capacity, time and cost planning)

  • Project phases (project initiation, project planning, project execution, project close, project control)

  • Project management tools

  • Critical path methods (CPM, MPM, PERT)

  • Risk analysis

  • Project management software

Intended learning outcomes

The students recognize the economic potential of a consistent project planning and the influence on compliance of project objectives such as deadlines and costs. The students are familiar with methods and tools of project planning and may use them in work.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) term paper (approx. 10 to 15 pages) and presentation (approx. 10 minutes), weighted 2:1 or d) project (approx. 20 hours)

Language of assessment: German and/or English

creditable for bonus

Allocation of places

35 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--


Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021)

Bachelor' degree (1 major) Economathematics (2022)


Module title

Abbreviation

Career planning and professional skills for students of Business and Economics

12-CC-KPBK-222-m01

Module coordinator

Module offered by

--

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

--

--

Contents

--

Intended learning outcomes

--

Courses (type, number of weekly contact hours, language — if other than German)

S (4)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. Written examination (approx. 60 minutes) or

  2. Term paper (approx. 15 pages) or

  3. Term paper (10 to 15 pages) and presentation (approx. 10 minutes); (weighted 2:1) or

  4. oral examination (approx. 20 minutes) or

  5. Portfolio (approx. 50-75 hours)

Allocation of places

15 places, WB5

Should the number of applications exceed the number of available places, places will be allocated as follows:

  1. Places will be allocated according to the number of subject semesters independet of subject. Among applicants with the same number of subject semesters, places will be allocated by lot.

  2. A waiting list will be maintained and places re-allocated as they become available.

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Economathematics (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 291 / 326


Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 292 / 326


Module title

Abbreviation

Modern Chinese Basics 1

04-MC60-SB1-222-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Basic phonetics, grammar and writing are taught on the basis of the teaching material used. Basic sentence structures and pronunciation are practised intensively in given simple everyday situations in small groups. The vocabulary reaches the extent of approx. 400 words.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Die Studierenden sind auf der Grundlage eines Wortschatzes von ca. 400 Worten in der Lage, Lehrbuchinhalte zu beherrschen und mündlich in einfachen Sätzen zu aktivieren. Sichere Tonalität und Aussprache wird im Rahmen des bekannten Wortschatzes erreicht.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (9)

Module taught in: German and Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 90 minutes; 75%) and oral examination of one candidate each (approx. 5 minutes; 25%)

Language of assessment: German and Chinese

creditable for bonus

Allocation of places

--

Additional information

--

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013) Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 293 / 326


Bachelor's degree (1 major, 1 minor) Pedagogy (2013)

Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Nanostructure Technology (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 294 / 326


Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016) Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 295 / 326


Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Modern China (2017) Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Games Engineering (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021) Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 296 / 326


Bachelor's degree (1 major, 1 minor) Theological Studies (2021) Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022)

Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 297 / 326


Module title

Abbreviation

Modern Chinese Basics 2

04-MC60-SB2-222-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

04-MC60-SB1

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

The knowledge already acquired is expanded and deepened. Orthography is intensively trained with an expanded vocabulary. The vocabulary and sentence structures learned are transferred to further contexts in oral exercises. Oral translation exercises serve to consolidate and expand active language use. The vocabulary is expanded to approx. 600 words.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Eine sichere orthographische Kompetenz im Rahmen des bekannten Wortschatzes wird erreicht. Die aktive Nut-zung bekannter Sprachstrukturen und erschlossenen Wortschatzes wird zunehmend selbständig angewendet.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (3)

Module taught in: German and Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 45 minutes; 75%) and oral examination of one candidate each (approx. 5 minutes; 25%)

Language of assessment: German and Chinese

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013) Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 298 / 326


Bachelor's degree (1 major, 1 minor) Pedagogy (2013)

Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Nanostructure Technology (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 299 / 326


Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016) Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 300 / 326


Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Modern China (2017) Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Games Engineering (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021) Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 301 / 326


Bachelor's degree (1 major, 1 minor) Theological Studies (2021) Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022)

Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 302 / 326


Module title

Abbreviation

Modern Chinese Basics 3

04-MC60-SB3-222-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

04-MC60-SB2

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

German contents available but not translated yet.


Die Sprachausbildung wird mit dem etablierten Lehrmaterial fortgesetzt. Neuer chinesischer Wortschatz wird mittels Umschreibungen im Chinesischen eingeübt. Bisher erlernte grammatikalische Phänomene werden syste-matisierend zusammengefasst und eingeübt. Der Wortschatz wird auf ca. 800 Worte erweitert.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Die Studierenden sind in der Lage sich in einfachen, routinemäßigen Situation selbständig zu verständigen, in denen es um einen einfachen und direkten Austausch von Informationen über vertraute Dinge geht. Die Grundlagen der Grammatik werden systematisch verstanden.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (3)

Module taught in: Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 45 minutes; 75%) and oral examination of one candidate each (approx. 5 minutes; 25%)

Language of assessment: Chinese

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 303 / 326


Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)

Bachelor's degree (1 major, 1 minor) Pedagogy (2013)

Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Nanostructure Technology (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 304 / 326


Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015) Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 305 / 326


Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016) Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Modern China (2017) Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Games Engineering (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 306 / 326


Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021) Bachelor's degree (1 major, 1 minor) Theological Studies (2021)

Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022)

Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Module title

Abbreviation

Chinese Intensification 1

04-MC60-SB4-222-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

May not be combined with modules 04-MC60-SB6 through 8.

Contents

German contents available but not translated yet.


Neben der Erweiterung des Wortschatzes steht die Beherrschung weiterer grammatischer Strukturen im Fokus. Das aktive Sprechen wird themenbezogen in routinemäßigen Situationen eingeübt.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Die Studierenden können Texte mit Hilfsmitteln eigenständig erschließen. Sie können sich mündlich und im direkten Austausch von Informationen über vertraute und geläufige Dinge ausdrücken.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (3)

Module taught in: Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

oral examination of one candidate each (approx. 15 minutes)

Language of assessment: Chinese

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013) Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)


Bachelor's degree (1 major, 1 minor) Pedagogy (2013)

Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Nanostructure Technology (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 309 / 326


Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016) Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 310 / 326


Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor' degree (1 major) Modern China (2017) Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Games Engineering (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021) Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 311 / 326


Bachelor's degree (1 major, 1 minor) Theological Studies (2021) Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022)

Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Module title

Abbreviation

Chinese Intensification 2

04-MC60-SB5-172-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

May not be combined with modules 04-MC60-SB6 through 8.

Contents

In the 4th language semester in Wuerzburg, language training is intensified, leading to independent reading of texts at the intermediate to higher basic level. Oral training is continued in the first independent presentations with simple topics.

Intended learning outcomes

Deepened understanding of grammatical phenomena and independent reading and free oral articulation of prepared topics.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (3)

Module taught in: Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written examination (approx. 60 minutes) Language of assessment: Chinese creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Biology (2011)

Bachelor' degree (1 major) Chemistry (2010)

Bachelor' degree (1 major) Mathematics (2014)

Bachelor' degree (1 major) Physics (2012)

Bachelor' degree (1 major) Psychology (2010)

Bachelor' degree (1 major) Economathematics (2012)

Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2013) Bachelor's degree (1 major, 1 minor) Pedagogy (2011)

Bachelor's degree (1 major, 1 minor) Pedagogy (2009)

Bachelor's degree (1 major, 1 minor) Pedagogy (2013)

Bachelor's degree (1 major, 1 minor) French Studies (2013)

Bachelor's degree (1 major, 1 minor) History (2010)


Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2013) Bachelor's degree (1 major, 1 minor) Philosophy (2013)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2012) Bachelor's degree (1 major, 1 minor) Spanish Studies (2010)

Bachelor's degree (1 major, 1 minor) Political and Social Studies (2013) Bachelor's degree (1 major, 1 minor) English and American Studies (2010) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2008) Bachelor's degree (1 major, 1 minor) Gallo-Roman philology (2010) Bachelor's degree (1 major, 1 minor) German Language and Literature (2013) Bachelor's degree (1 major, 1 minor) German Language and Literature (2010) Bachelor's degree (1 major, 1 minor) Italian Studies (2010)

Bachelor's degree (2 majors) Classical Archaeology (2013) Bachelor's degree (2 majors) Pedagogy (2013)

Bachelor's degree (2 majors) Philosophy (2013) Bachelor's degree (2 majors) Special Education (2009) Bachelor's degree (2 majors) Digital Humanities (2012)

Bachelor's degree (2 majors) Political and Social Studies (2011) Bachelor's degree (2 majors) Russian Language and Culture (2012) Bachelor's degree (2 majors) European Ethnology (2013)

Magister Theologiae Catholic Theology (2013) Bachelor's degree (2 majors) Spanish Studies (2013) Bachelor's degree (2 majors) Spanish Studies (2009)

Bachelor's degree (2 majors) English and American Studies (2009) Bachelor's degree (2 majors) Gallo-Roman philology (2009) Bachelor's degree (2 majors) German Language and Literature (2013) Bachelor's degree (2 majors) Italian Studies (2009)

Bachelor' degree (1 major) Biology (2015)

Bachelor' degree (1 major) Chemistry (2015)

Bachelor' degree (1 major) Geography (2015) Bachelor' degree (1 major) Computer Science (2015) Bachelor' degree (1 major) Mathematics (2015)

Bachelor' degree (1 major) Musicology (2015)

Bachelor' degree (1 major) Physics (2015)

Bachelor' degree (1 major) Psychology (2015)

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Nanostructure Technology (2015)

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Biomedicine (2015)

Bachelor' degree (1 major) Human-Computer Systems (2015) Bachelor' degree (1 major) Music Education (2015)

Bachelor' degree (1 major) Computational Mathematics (2015) Bachelor' degree (1 major) Political and Social Studies (2015) Bachelor' degree (1 major) Functional Materials (2015) Bachelor' degree (1 major) Academic Speech Therapy (2015) Bachelor' degree (1 major) Indology/South Asian Studies (2015) Bachelor's degree (1 major, 1 minor) Egyptology (2015)

Bachelor's degree (1 major, 1 minor) Classical Archaeology (2015)

Bachelor's degree (1 major, 1 minor) Pedagogy (2015)

Bachelor's degree (1 major, 1 minor) History (2015)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2015) Bachelor's degree (1 major, 1 minor) Musicology (2015)

Bachelor's degree (1 major, 1 minor) Philosophy (2015)

Bachelor's degree (1 major, 1 minor) Pre- and Protohistoric Archaeology (2015)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 314 / 326


Bachelor's degree (1 major, 1 minor) Ancient World (2015)

Bachelor's degree (1 major, 1 minor) Music Education (2015) Bachelor's degree (1 major, 1 minor) Philosophy and Religion (2015) Bachelor's degree (1 major, 1 minor) Theological Studies (2015)

Bachelor's degree (1 major, 1 minor) Geography (Focus Human Geography) (2015) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2015) Bachelor's degree (1 major, 1 minor) Russian Language and Culture (2015) Bachelor's degree (1 major, 1 minor) German Language and Literature (2015) Bachelor's degree (2 majors) Egyptology (2015)

Bachelor's degree (2 majors) Classical Archaeology (2015) Bachelor's degree (2 majors) Pedagogy (2015)

Bachelor's degree (2 majors) Protestant Theology (2015)

Bachelor's degree (2 majors) History of Medieval and Modern Art (2015) Bachelor's degree (2 majors) Musicology (2015)

Bachelor's degree (2 majors) Philosophy (2015) Bachelor's degree (2 majors) Special Education (2015)

Bachelor's degree (2 majors) Pre- and Protohistoric Archaeology (2015) Bachelor's degree (2 majors) Latin Philology (2015)

Bachelor's degree (2 majors) Music Education (2015) Bachelor's degree (2 majors) Philosophy and Religion (2015) Bachelor's degree (2 majors) Theological Studies (2015) Bachelor's degree (2 majors) Digital Humanities (2015) Bachelor's degree (2 majors) Political and Social Studies (2015)

Bachelor's degree (2 majors) Russian Language and Culture (2015) Bachelor's degree (2 majors) Greek Philology (2015)

Bachelor's degree (2 majors) European Ethnology (2015) Bachelor's degree (2 majors) Indology/South Asian Studies (2015) Bachelor's degree (2 majors) Ancient Near Eastern Studies (2015) Bachelor's degree (2 majors) Geography (2015)

Bachelor's degree (2 majors) French Studies (2015) Bachelor's degree (2 majors) History (2015)

Bachelor's degree (2 majors) Sport Science (Focus on health and Pedagogics in Movement) (2015) Bachelor's degree (2 majors) German Language and Literature (2015)

Bachelor' degree (1 major) Mathematical Physics (2016) Bachelor' degree (1 major) Human-Computer Systems (2016) Bachelor's degree (2 majors) Theological Studies (2011) Bachelor's degree (1 major, 1 minor) French Studies (2016) Bachelor's degree (2 majors) French Studies (2016) Bachelor's degree (1 major, 1 minor) Italian Studies (2016) Bachelor's degree (2 majors) Italian Studies (2016) Bachelor's degree (1 major, 1 minor) Spanish Studies (2016) Bachelor's degree (2 majors) Spanish Studies (2016)

Bachelor' degree (1 major) Romanic Languages (French/Italian) (2016) Bachelor' degree (1 major) Romanic Languages (French/Spanish) (2016) Bachelor' degree (1 major) Romanic Languages (Italian/Spanish) (2016) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Games Engineering (2016)

Bachelor's degree (1 major, 1 minor) English and American Studies (2016) Bachelor's degree (2 majors) English and American Studies (2016) Bachelor' degree (1 major) Media Communication (2016)

Bachelor' degree (1 major) Food Chemistry (2016)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2016)

Bachelor' degree (1 major) Biology (2017)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 315 / 326


Bachelor's degree (1 major, 1 minor) Geography (2017)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) History of Medieval and Modern Art (2017) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2017) Bachelor' degree (1 major) Aerospace Computer Science (2017)

Bachelor's degree (1 major, 1 minor) Modern China (Minor, 2017) Bachelor' degree (1 major) Modern China (2017)

Bachelor' degree (1 major) Biochemistry (2017)

Bachelor' degree (1 major) Chemistry (2017)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2017) Bachelor' degree (1 major) Economathematics (2017)

Bachelor' degree (1 major) Games Engineering (2017) Bachelor' degree (1 major) Computer Science (2017) Bachelor' degree (1 major) Media Communication (2018) Bachelor' degree (1 major) Biomedicine (2018)

Bachelor' degree (1 major) Human-Computer Systems (2018) Bachelor's degree (2 majors) Classical Archaeology (2018) Bachelor's degree (1 major, 1 minor) Classical Archaeology (2018)

Bachelor's degree (1 major, 1 minor) Digital Humanities (2018) Bachelor's degree (2 majors) Digital Humanities (2018) Bachelor' degree (1 major) Computer Science (2019)

Bachelor's degree (1 major, 1 minor) English and American Studies (2019) Bachelor's degree (1 major, 1 minor) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Indology/South Asian Studies (2019) Bachelor's degree (1 major, 1 minor) Modern China (Minor, 2019) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor's degree (2 majors) Indology/South Asian Studies (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Modern China (2019)

Bachelor' degree (1 major) Food Chemistry (2019) Bachelor' degree (1 major) Biomedicine (2020)

Bachelor' degree (1 major) Pedagogy (2020)

Bachelor' degree (1 major) Political and Social Studies (2020) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor's degree (1 major, 1 minor) Political and Social Studies (2020) Bachelor's degree (2 majors) European Ethnology (2020)

Bachelor's degree (2 majors) Political and Social Studies (2020) Bachelor's degree (2 majors) Special Education (2020) Bachelor' degree (1 major) Physics (2020)

Bachelor' degree (1 major) Nanostructure Technology (2020) Bachelor' degree (1 major) Mathematical Physics (2020) Bachelor' degree (1 major) Aerospace Computer Science (2020)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2020) Bachelor's degree (1 major, 1 minor) Pedagogy (2020)

Bachelor's degree (2 majors) Pedagogy (2020)

Bachelor' degree (1 major) Psychology (2020)

Bachelor' degree (1 major) Biology (2021) Magister Theologiae Catholic Theology (2021) Bachelor's degree (2 majors) History (2021)

Bachelor's degree (1 major, 1 minor) History (2021) Bachelor' degree (1 major) Media Communication (2021) Bachelor's degree (2 majors) Theological Studies (2021)

Bachelor's degree (1 major, 1 minor) Theological Studies (2021)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 316 / 326


Bachelor's degree (1 major, 1 minor) English and American Studies (2021) Bachelor's degree (2 majors) English and American Studies (2021) Bachelor' degree (1 major) Functional Materials (2021)

Bachelor' degree (1 major) Computer Science und Sustainability (2021) Bachelor's degree (2 majors) Comparative Indo-European Linguistics (2021) Bachelor' degree (1 major) Food Chemistry (2021)

Bachelor' degree (1 major) Quantum Technology (2021) Bachelor's degree (2 majors) Special Education (2021) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Human-Computer Systems (2022)

Bachelor's degree (1 major, 1 minor) Museology and material culture (2022) Bachelor' degree (1 major) Biochemistry (2022)

Bachelor' degree (1 major) Biology (2022)

Bachelor' degree (1 major) Economathematics (2022) Bachelor' degree (1 major) Mathematical Data Science (2022) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022)

Bachelor' degree (1 major) Artificial Intelligence and Data Science (2022) Bachelor's degree (2 majors) Ancient Near Eastern Archaeology (2022) Bachelor's degree (1 major, 1 minor) Ancient World (2022)

Bachelor's degree (2 majors) Ancient Near Eastern Studies (2022)

Bachelor' degree (1 major) Franco-German studies: language, culture, digital competence (2022) Bachelor' degree (1 major) Midwifery (2022)

Bachelor' degree (1 major) European Law (2023)

Bachelor's degree (1 major, 1 minor) English and American Studies (2023) Bachelor's degree (2 majors) English and American Studies (2023) Bachelor' degree (1 major) Artificial Intelligence and Data Science (2023) Bachelor' degree (1 major) Mathematics (2023)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor's degree (1 major, 1 minor) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) History of Medieval and Modern Art (2023) Bachelor's degree (2 majors) Special Education (2023)

Bachelor' degree (1 major) Business Management and Economics (2023) Bachelor' degree (1 major) Geography (2023)

Bachelor's degree (2 majors) Geography (2023)

Bachelor's degree (1 major, 1 minor) Geography (2023)

Bachelor's degree (2 majors) European Ethnology/Empiric Cultural Studies (2023)


Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 317 / 326


Module title

Abbreviation

Chinese technical language 1

04-MC60-SB9-222-m01

Module coordinator

Module offered by

holder of the Chair of Contemporary Chinese Studies

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

German contents available but not translated yet.


Selbständige Erschließung und Präsentation von vorgegebenen Themenbereichen sowie freie Diskussion der erschlossenen inhaltlichen Felder. Weiterführende Lektüre zu den jeweiligen Themen anhand von mittelschweren Texten, die selbstständig bearbeitet werden. Beispiele für aktuelle Themenbereiche sind: Gesellschaftliche, poli-tische und wirtschaftliche Phänomene des zeitgenössischen China.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Mittelschwere Texte werden eigenständig erschlossen und in kommunikativen Übungen diskutiert. Die Studierenden sind in der Lage über Vorstellungen, Ziele und Ansichten begründet und kritisch darzulegen und zu dis-kutieren.

Courses (type, number of weekly contact hours, language — if other than German)

Ü (2)

Module taught in: Chinese

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

oral examination of one candidate each (approx. 15 minutes)

Language of assessment: Chinese

creditable for bonus

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor's degree (1 major, 1 minor) East Asia (Minor, 2022) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor’s with 1 major Business Information Sy-

stems (2021)

JMU Würzburg • generated 12-Mai-2023 • exam. reg. da-

ta record Bachelor (180 ECTS) Wirtschaftsinformatik - 2021

page 318 / 326


Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

Chinese Studies

04-ChinaK-152-m01

Module coordinator

Module offered by

holder of the Chair of China Business and Economics

Institute of East and South Asian Cultural Studies

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

2 semester

undergraduate

--

Contents

Introduction to the challenges in and outside China arising from the growth of the Chinese economy since the opening policy. Against the backdrop of Western reporting on China's economic growth, economic and China studies and discourses and debates are analysed.

Intended learning outcomes

German intended learning outcomes available but not translated yet.


Die Studierenden erlangen einen Zugang und ein Verständnis zur Auswertung der chinesischen wirtschaftlichen Entwicklung und werden in die Lage versetzt wirtschaftwissenschaftliche Theorien auf die Entwicklung in China zu übertragen.

Courses (type, number of weekly contact hours, language — if other than German)

S (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

term paper (approx. 15 to 20 pages) with presentation (approx. 30 minutes) and discussion (approx. 15 minutes), weighted 4:1:1

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Management and Economics (2015) Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Management and Economics (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Business Information Systems (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

General Management 1

12-GM1-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  3. oral examination (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

General Management 2

12-GM2-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

5

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  3. oral examination (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

150 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

General Management 3

12-GM3-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  3. oral examination (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Module title

Abbreviation

General Management 4

12-GM4-212-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

3

(not) successfully completed

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

This module serves the purpose of transferring credits from

  • courses taken at other German or non-German universities

  • additional courses offered on a short-term basis

  • courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)

The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.

Intended learning outcomes

As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.

Courses (type, number of weekly contact hours, language — if other than German)

V (2) + Ü (2)

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

  1. written examination (approx. 60 minutes) or

  2. term paper (approx. 10 to 15 pages) and presentation (approx. 20 minutes), weighted 2:1 or

  3. oral examination (approx. 20 minutes)

Allocation of places

--

Additional information

--

Workload

90 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2021) Bachelor' degree (1 major) Economathematics (2021)

Bachelor' degree (1 major) Business Management and Economics (2021) Bachelor' degree (1 major) Economathematics (2022)

Bachelor' degree (1 major) Business Information Systems (2023) Bachelor' degree (1 major) Economathematics (2023)

Bachelor' degree (1 major) Business Management and Economics (2023)


Thesis Area

(10 ECTS credits)


Module title

Abbreviation

Bachelor Thesis Business Information Systems

12-BA-Wiinf-152-m01

Module coordinator

Module offered by

Dean of the Faculty of Business Management and Economics

Faculty of Business Management and Economics

ECTS

Method of grading

Only after succ. compl. of module(s)

10

numerical grade

--

Duration

Module level

Other prerequisites

1 semester

undergraduate

--

Contents

Students will complete their degree with a Bachelor's thesis in which they will be required to research and write on a topic from the area of business information systems. This thesis may either take the form of an analysis and structured presentation of the existing literature on a certain topic or may, as is often the case, also include a presentation of the students' own original achievements, e. g. new algorithms developed by students, surveys, the prototypical demonstration of a concept they developed or the application and (further) development of a theoretical model. Check the websites of the chairs for further information.

Intended learning outcomes

The acquisition of specialized skills presupposes the reception of national and international (mainly english) literature. Students are able to understand relevant contributions to research and professional practice and to critically analyze and assess their relevance to their own specific questions. They can recognize and assess major lines of development and dynamics within the field of study.

Courses (type, number of weekly contact hours, language — if other than German)

No courses assigned to module

Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether module is creditable for bonus)

written thesis (approx. 40 pages)

Registration on a continuous basis as agreed upon with supervisor.

Language of assessment: German and/or English

Allocation of places

--

Additional information

Time to complete: 8 weeks.

Workload

300 h

Teaching cycle

--

Referred to in LPO I (examination regulations for teaching-degree programmes)

--

Module appears in

Bachelor' degree (1 major) Business Information Systems (2015) Bachelor' degree (1 major) Business Information Systems (2016) Bachelor' degree (1 major) Business Information Systems (2019) Bachelor' degree (1 major) Business Information Systems (2020) Bachelor' degree (1 major) Business Information Systems (2021)

Bachelor' degree (1 major) Business Information Systems (2023)

diff --git a/01_module_handbooks/bachelor_information_systems.pdf b/01_module_handbooks/bachelor_information_systems.pdf new file mode 100644 index 0000000000000000000000000000000000000000..59b21bb5b6d65e0cd537677f9383bcbcbe9b4daf --- /dev/null +++ b/01_module_handbooks/bachelor_information_systems.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bb186b0a0d75d1f82ef34a9cc395e17a77eea4a2dd6c0c5b88b43347ce8bd471 +size 15806261 diff --git a/01_module_handbooks/master_information_systems.pdf b/01_module_handbooks/master_information_systems.pdf new file mode 100644 index 0000000000000000000000000000000000000000..9f083dc416d445557f156bdb461023cc12303e03 --- /dev/null +++ b/01_module_handbooks/master_information_systems.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bd431677afbf1efbe1d533be5f2357705e93992fba97ca1d95277562a40440b3 +size 12414315 diff --git a/01_module_handbooks/master_international_economic_policy.pdf b/01_module_handbooks/master_international_economic_policy.pdf new file mode 100644 index 0000000000000000000000000000000000000000..c2a6e681fe5d8965b82ba91f65a3787247093082 --- /dev/null +++ b/01_module_handbooks/master_international_economic_policy.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c402c321942c3aad16d7ffcd325981d1bc9e4129a80b1b96036da0ba6359e3eb +size 17147808 diff --git a/01_module_handbooks/master_management.pdf b/01_module_handbooks/master_management.pdf new file mode 100644 index 0000000000000000000000000000000000000000..47d24e5cb5de23f8f634bed38f65f249a057bbab --- /dev/null +++ b/01_module_handbooks/master_management.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a1e72fec495a8fcad34c63b58a5d2f7435cc4c0511857870d75cde04ee98aaa3 +size 46696350 diff --git a/02_data_extraction/BA_MM_all_modules.xlsx b/02_data_extraction/BA_MM_all_modules.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..0144e68cfb94e13d50b6c569e5371b1997f9564d Binary files /dev/null and b/02_data_extraction/BA_MM_all_modules.xlsx differ diff --git a/02_data_extraction/__pycache__/helper_methods.cpython-38.pyc b/02_data_extraction/__pycache__/helper_methods.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e91abcb0a16144809fc13c261f93598d84da25da Binary files /dev/null and b/02_data_extraction/__pycache__/helper_methods.cpython-38.pyc differ diff --git a/02_data_extraction/data_extraction.ipynb b/02_data_extraction/data_extraction.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..ea13d8215754de48ad2b42131e15f79601f3f446 --- /dev/null +++ b/02_data_extraction/data_extraction.ipynb @@ -0,0 +1,539 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Necessary pip installs: \n", + "# pip install pandas\n", + "# pip install pdfminer.six\n", + "# pip install xlsxwriter" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# moduleCatalogue paths \n", + "\n", + "# Masters\n", + "MS_IS_all_modules = \"./module_catalogues/MS_IS_all_modules.pdf\"\n", + "\n", + "MS_MM_all_modules = \"./module_catalogues/MS_MM_all_modules.pdf\"\n", + "\n", + "\n", + "# Bachelors\n", + "BA_IS_all_modules = \"./module_catalogues/BA_IS_all_modules.pdf\"\n", + "\n", + "BA_MM_all_modules = \"./module_catalogues/BA_MM_all_modules.pdf\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import re\n", + "from pdfminer.high_level import extract_text\n", + "import pandas as pd\n", + "\n", + "# Read PDF file\n", + "text_Module_Catalogue = extract_text(BA_MM_all_modules)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "# Pattern to remove Master Information Systems\n", + "removal_patterns_MS_IS = [\n", + " r\"Module Catalogue for the Subject\\nInformation Systems\\nMaster’s with 1 major, 120 ECTS credits\",\n", + " r\"JMU\\sWürzburg\\s•\\sgenerated\\s\\d{1,2}-[A-Za-z]+-\\d{4}\\s•\\sexam\\.\\sreg\\.\\sda-\\nta\\srecord\\sMaster\\s\\(120\\sECTS\\)\\sInformation\\sSystems\\s-\\s\\d{4}\",\n", + " r\"Master’s\\s+with\\s+1\\s+major\\s+Information\\s+Systems\\s+\\(\\d{4}\\)\",\n", + " r\"page\\s+\\d+\\s+/\\s+\\d+\",\n", + " r'^\\s*$'\n", + " ]\n", + "\n", + "# Pattern to remove Bachelor Information Systems\n", + "\n", + "removal_patterns_BA_IS = [\n", + " r\"Module Catalogue for the Subject\\nBusiness Information Systems\\nBachelor’s with 1 major, 180 ECTS credits\",\n", + " r\"JMU\\sWürzburg\\s•\\sgenerated\\s\\d{1,2}-[A-Za-z]+-\\d{4}\\s•\\sexam\\.\\sreg\\.\\sda-\\nta\\srecord\\sBachelor\\s\\(180\\sECTS\\)\\sWirtschaftsinformatik\\s-\\s\\d{4}\",\n", + " r\"Bachelor’s\\s+with\\s+1\\s+major\\s+Business\\s+Information\\s+Sy-\\n+stems\\s+\\(\\d{4}\\)\",\n", + " r\"page\\s+\\d+\\s+/\\s+\\d+\",\n", + " r'^\\s*$'\n", + " ]\n", + "\n", + "# Pattern to remove Bachlor Wirtschaftswissenschaften\n", + "removal_patterns_MS_MM = [\n", + " r\"Module Catalogue for the Subject\\nManagement\\nMaster’s with 1 major, 120 ECTS credits\",\n", + " r\"JMU\\sWürzburg\\s•\\sgenerated\\s11-Mai-2023\\s•\\sexam\\.\\sreg\\.\\s\\ndata\\srecord\\sMaster\\s\\(120\\sECTS\\)\\sManagement\\s-\\s2018\",\n", + " r\"Master’s\\s+with\\s+1\\s+major\\s+Management\\s+\\(\\d{4}\\)\",\n", + " r\"page\\s+\\d+\\s+/\\s+\\d+\",\n", + " r'^\\s*$'\n", + " ]\n", + "\n", + "removal_patterns_BA_MM = [\n", + " r\"Module Catalogue for the Subject\\nBusiness Management and Economics\\nBachelor’s with 1 major, 180 ECTS credits\",\n", + " r\"JMU Würzburg • generated \\d{2}-[A-Za-z]{3}-\\d{4} • exam\\. reg\\. data re-[\\s\\S]*?Bachelor \\(180 ECTS\\) Wirtschaftswissenschaft - 2008\",\n", + " r\"Bachelor’s\\s+with\\s+1\\s+major\\s+Business\\s+Management\\s+and\\s+Economics\\s+\\(\\d{4}\\)\",\n", + " r\"page\\s+\\d+\\s+/\\s+\\d+\",\n", + " r'^\\s*$'\n", + " ]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "# regex patterns to get attributes of Master Information Systems\n", + "from enum import Enum\n", + "\n", + "class Patterns_MS_IS(Enum):\n", + " PATTERN_ENTIRE_MODULE = r\"Module title[\\s\\S]*?(?=Module title|$)\"\n", + " MODULE_TITLE = r'Module title\\s*\\n*\\s*(.*)'\n", + " ABBREVIATION = r'Abbreviation\\s*\\n*\\s*(.*)'\n", + " MODULE_OFFERED_BY = r\"^(Faculty|Institute).*\"\n", + " MODULE_COORDINATOR = r\"^(Holder|holder|Dean).*\"\n", + " ETCS = r\"^\\d{1,2}$\"\n", + " METHOD_GRADING = r\".*(not\\s)?successfully completed|numerical grade.*\"\n", + " DURATION = r\"^\\d\\ssemester$\"\n", + " MODULE_LEVEL = r\"^(?:graduate|undergraduate)$\"\n", + " CONTENTS = r'Contents([\\s\\S]*?)Intended learning outcomes'\n", + " INTENDED_LEARNING_OUTCOMES = r'Intended learning outcomes\\n\\n([\\s\\S]*?)\\n\\nCourses \\(type'\n", + " COURSES = r'if other than German\\)([\\s\\S]*?)Method of assessment'\n", + " ASSESSMENT = r'whether\\s*\\nmodule is creditable for bonus\\)([\\s\\S]*?)Allocation of places'\n", + " ALLOCATION = r'Allocation of places([\\s\\S]*?)Additional information'\n", + " ADDITIONAL_INFORMATION = r'Additional information([\\s\\S]*?)Workload'\n", + " WORKLOAD = r'Workload([\\s\\S]*?)Teaching cycle'\n", + " TEACHING_CYCLE = r'Teaching cycle([\\s\\S]*?)Referred to in LPO I'\n", + " REFERRED_LPO = r'regulations for teaching-degree programmes\\)([\\s\\S]*?)Module appears in'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "from helper_methods import extract_first_match, extract_LineMatch, clean_entries\n", + "import xlsxwriter\n", + "\n", + "# Extract modules to xlsx -> Method shall be used generically for all modules later\n", + "\n", + "def extract_modules_to_xlsx (text, patternsToRemove, file_path):\n", + "\n", + " modules = re.findall(Patterns_MS_IS.PATTERN_ENTIRE_MODULE.value, text)\n", + " modules = clean_entries(modules, patternsToRemove)\n", + "\n", + " workbook = xlsxwriter.Workbook(file_path)\n", + " worksheet = workbook.add_worksheet()\n", + "\n", + " # set columns\n", + " column_names = ['Module title', 'Abbreviation', 'Module coordinator', 'Module offered by', 'ETCS', 'Method of grading',\n", + " 'Duration', 'Module level', 'Contents', 'Intended learning outcomes', 'Courses', 'Method of assessment',\n", + " 'Allocation of places', 'Additional information', 'Workload', 'Teaching cycle', 'Referred to in LPO I']\n", + " \n", + " for i in range(len(column_names)):\n", + " worksheet.write(0, i, column_names[i])\n", + "\n", + " counter = 1\n", + " # Extract module attributes\n", + " for i in range(len(modules)):\n", + " module_attributes = []\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.MODULE_TITLE.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.ABBREVIATION.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.MODULE_OFFERED_BY.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.MODULE_COORDINATOR.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.ETCS.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.METHOD_GRADING.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.DURATION.value))\n", + " module_attributes.append(extract_LineMatch(modules[i], Patterns_MS_IS.MODULE_LEVEL.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.CONTENTS.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.INTENDED_LEARNING_OUTCOMES.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.COURSES.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.ASSESSMENT.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.ALLOCATION.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.ADDITIONAL_INFORMATION.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.WORKLOAD.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.TEACHING_CYCLE.value))\n", + " module_attributes.append(extract_first_match(modules[i], Patterns_MS_IS.REFERRED_LPO.value))\n", + " \n", + " # Write to xlsx file\n", + " for j in range(len(module_attributes)):\n", + " worksheet.write(counter, j, module_attributes[j])\n", + " \n", + " counter += 1\n", + " workbook.close()\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "# Use write to xlsx method for Master Information Systems\n", + "\n", + "extract_modules_to_xlsx(text_Module_Catalogue, removal_patterns_MS_MM, \"BA_MM_all_modules.xlsx\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Module title\n", + "\n", + "Introduction to Market-Oriented Management\n", + "\n", + "Abbreviation\n", + "\n", + "12-Mark-G-082-m01\n", + "\n", + "Module coordinator\n", + "\n", + "Module offered by\n", + "\n", + "holder of the Chair of Business Management and Marke-\n", + "ting\n", + "\n", + "Faculty of Business Management and Economics\n", + "\n", + "ECTS Method of grading\n", + "\n", + "Only after succ. compl. of module(s)\n", + "\n", + "5\n", + "\n", + "numerical grade\n", + "\n", + "--\n", + "\n", + "Duration\n", + "\n", + "Module level\n", + "\n", + "Other prerequisites\n", + "\n", + "1 semester\n", + "\n", + "undergraduate\n", + "\n", + "--\n", + "\n", + "Contents\n", + "\n", + "Description\n", + "In this module, students will acquire the theoretical foundations of market-oriented management.\n", + "\n", + "Content:\n", + "With the stakeholder approach as a starting point, the basic design of market-oriented management will be ex-\n", + "plained and exemplified in the 5 classical steps: situation analysis, objectives, strategies, tools and control-\n", + "ling. The course will focus not only on the behavioural approaches of consumer behaviour but also on industri-\n", + "al purchasing behaviour. A case study introducing students to the fundamental principles of market research ba-\n", + "sed on a conjoint analysis will provide students with deeper insights into the topic.\n", + "\n", + "Outline of syllabus:\n", + "1. Marketing, entrepreneurship and business management\n", + "2. Explanations of consumer behaviour\n", + "3. Fundamentals of market research\n", + "4. Strategic marketing; marketing tools\n", + "5. Corporate social responsibility versus creating shared value\n", + "\n", + "Reading:\n", + "Foscht, T. / Swoboda, B.: Käuferverhalten: Grundlagen -- Perspektiven -- Anwendungen, 4th revised and exp. ed.,\n", + "Wiesbaden 2011.\n", + "Homburg, Ch.: Grundlagen des Marketingmanagements: Einführung in Strategie, Instrumente, Umsetzung und\n", + "Unternehmensführung, 4th revised and exp. ed., Wiesbaden 2012.\n", + "Homburg, Ch.: Grundlagen des Marketingmanagements: Einführung in Strategie, Instrumente, Umsetzung und\n", + "Unternehmensführung, 3rd ed., Wiesbaden, 2012a.\n", + "Kroeber-Riel, W. /Weinberg, P.: Konsumentenverhalten, 9th ed., Munich 2009.\n", + "Meffert, H. / Burman, Ch / Kirchgeorg, M.: Marketing -- Grundlagen marktorientierter Unternehmensführung: Kon-\n", + "zepte -- Instrumente -- Praxisbeispiele, 11th revised and exp. ed., Wiesbaden 2012.\n", + "Meffert, H. / Burman, Ch / Becker, Ch.: Internationales Marketing-Management -- Ein markenorientierter Ansatz,\n", + "4th ed., Stuttgart 2010.\n", + "Meyer, M.: Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unternehmung,\n", + "Wiesbaden 1995.\n", + "Porter, M. E.: Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frankfurt /\n", + "New York 2014. (Original: Porter, M.: Competitive Advantage, New York 1985.)\n", + "Simon, H. / Fassnacht, M.: Preismanagement, Strategie -- Analyse -- Entscheidung -- Umsetzung, 3rd ed., Wies-\n", + "baden 2009.\n", + "\n", + "Intended learning outcomes\n", + "\n", + "The students have a basic understanding of business management and are able to classify the knowledge syste-\n", + "matically. In addition, they can use the acquired knowledge solve and identify the conventional problem fields of\n", + "business management.\n", + "\n", + "Courses (type, number of weekly contact hours, language — if other than German)\n", + "\n", + "V + Ü (no information on SWS (weekly contact hours) and course language available)\n", + "\n", + "Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether\n", + "module is creditable for bonus)\n", + "\n", + "written examination (approx. 60 minutes)\n", + "\n", + "Allocation of places\n", + "\n", + "Number of places: 405. No restrictions with regard to available places for Bachelor's students of Wirtschaftswis-\n", + "senschaft (Business Management and Economics), Wirtschaftsmathematik (Mathematics for Economics) and\n", + "Wirtschaftsinformatik (Business Information Systems). The remaining places will be allocated to students of\n", + "other subjects. Should the number of applications exceed the number of available places, places will be allo-\n", + "cated in a standardised procedure among all applicants irrespective of their subjects according to the following\n", + "quotas: Quota 1 (50% of places): total number of ECTS credits already achieved in the respective degree subject;\n", + "among applicants with the same number of ECTS credits achieved, places will be allocated by lot. Quota 2 (25%\n", + "of places): number of subject semesters of the respective applicant; among applicants with the same number of\n", + "subject semesters, places will be allocated by lot. Quota 3 (25% of places): allocation by lot. Applicants who al-\n", + "ready have successfully completed at least one module component of the respective module will be given prefe-\n", + "rential consideration. Places on all courses of the module component with a restricted number of places will be\n", + "allocated in the same procedure. A waiting list will be maintained and places re-allocated as they become availa-\n", + "ble.\n", + "\n", + "Additional information\n", + "\n", + "--\n", + "\n", + "Referred to in LPO I (examination regulations for teaching-degree programmes)\n", + "\n", + "--\n", + "\n", + "Module title\n", + "\n", + "Abbreviation\n", + "\n", + "Supply, Production and Operations Management. An Introduction\n", + "\n", + "12-BPL-G-082-m01\n", + "\n", + "Module coordinator\n", + "\n", + "Module offered by\n", + "\n", + "holder of the Chair of Business Management and Industrial\n", + "Management\n", + "\n", + "Faculty of Business Management and Economics\n", + "\n", + "ECTS Method of grading\n", + "\n", + "Only after succ. compl. of module(s)\n", + "\n", + "5\n", + "\n", + "numerical grade\n", + "\n", + "--\n", + "\n", + "Duration\n", + "\n", + "Module level\n", + "\n", + "Other prerequisites\n", + "\n", + "1 semester\n", + "\n", + "undergraduate\n", + "\n", + "--\n", + "\n", + "Contents\n", + "\n", + "This course will provide students with an overview of fundamental processes in procurement, production and lo-\n", + "gistics and the related corporate functions as well as a model-based introduction to related planning procedu-\n", + "res.\n", + "\n", + "Intended learning outcomes\n", + "\n", + "The students will be able to describe and discuss the objectives and major processes in the domains of corpo-\n", + "rate procurement, production and logistics as well as their interdependencies. Furthermore, they are capable of\n", + "developing and applying basic planning models in these fields.\n", + "\n", + "Courses (type, number of weekly contact hours, language — if other than German)\n", + "\n", + "V + Ü (no information on SWS (weekly contact hours) and course language available)\n", + "\n", + "Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether\n", + "module is creditable for bonus)\n", + "\n", + "written examination (approx. 60 minutes)\n", + "\n", + "Allocation of places\n", + "\n", + "Number of places: 405. No restrictions with regard to available places for Bachelor's students of Wirtschaftswis-\n", + "senschaft (Business Management and Economics), Wirtschaftsmathematik (Mathematics for Economics) and\n", + "Wirtschaftsinformatik (Business Information Systems). The remaining places will be allocated to students of\n", + "other subjects. Should the number of applications exceed the number of available places, places will be allo-\n", + "cated in a standardised procedure among all applicants irrespective of their subjects according to the following\n", + "quotas: Quota 1 (50% of places): total number of ECTS credits already achieved in the respective degree subject;\n", + "among applicants with the same number of ECTS credits achieved, places will be allocated by lot. Quota 2 (25%\n", + "of places): number of subject semesters of the respective applicant; among applicants with the same number of\n", + "subject semesters, places will be allocated by lot. Quota 3 (25% of places): allocation by lot. Applicants who al-\n", + "ready have successfully completed at least one module component of the respective module will be given prefe-\n", + "rential consideration. Places on all courses of the module component with a restricted number of places will be\n", + "allocated in the same procedure. A waiting list will be maintained and places re-allocated as they become availa-\n", + "ble.\n", + "\n", + "Additional information\n", + "\n", + "--\n", + "\n", + "Referred to in LPO I (examination regulations for teaching-degree programmes)\n", + "\n", + "--\n", + "\n", + "Module title\n", + "\n", + "Managerial Accounting\n", + "\n", + "Module coordinator\n", + "\n", + "holder of the Chair of Business Management and Accoun-\n", + "ting\n", + "\n", + "Abbreviation\n", + "\n", + "12-IntUR-G-082-m01\n", + "\n", + "Module offered by\n", + "\n", + "Faculty of Business Management and Economics\n", + "\n", + "ECTS Method of grading\n", + "\n", + "Only after succ. compl. of module(s)\n", + "\n", + "5\n", + "\n", + "numerical grade\n", + "\n", + "--\n", + "\n", + "Duration\n", + "\n", + "Module level\n", + "\n", + "Other prerequisites\n", + "\n", + "1 semester\n", + "\n", + "undergraduate\n", + "\n", + "--\n", + "\n", + "Contents\n", + "\n", + "Content:\n", + "This course offers an introduction to aims and methods of managerial accounting (cost accounting).\n", + "\n", + "Outline of syllabus:\n", + "1. Managerial accounting and financial accounting\n", + "2. Managerial accounting: basic terms\n", + "3. Different types of costs\n", + "4. Cost centre accounting based on total costs\n", + "5. Job costing based on total costs\n", + "6. Cost centre accounting and job costing based on direct/variable costs\n", + "7. Budgeting and cost-variance analysis\n", + "8. Cost-volume-profit analysis\n", + "9. Cost information and operating decisions\n", + "\n", + "Reading:\n", + "Coenenberg/Fischer/Günther: Kostenrechnung und Kostenanalyse, Stuttgart.\n", + "Friedl/Hofmann/Pedell: Kostenrechnung. Eine entscheidungsorientierte Einführung.\n", + "(most recent editions)\n", + "\n", + "Intended learning outcomes\n", + "\n", + "After completing the course \"Management Accounting and Control\", the students will be able to\n", + "(i) set out the responsibilities of the company's internal accounting and control;\n", + "(ii) define the central concepts of internal enterprise computing restriction and control and assign case studies\n", + "the terms;\n", + "(iii) apply the basic methods of internal corporate accounting and control on a full and cost base to idealized ca-\n", + "se studies of medium difficulty that calculate relevant costs and benefits and take on this basis a reasoned deci-\n", + "sion.\n", + "\n", + "Courses (type, number of weekly contact hours, language — if other than German)\n", + "\n", + "V + Ü (no information on SWS (weekly contact hours) and course language available)\n", + "\n", + "Method of assessment (type, scope, language — if other than German, examination offered — if not every semester, information on whether\n", + "module is creditable for bonus)\n", + "\n", + "written examination (approx. 60 minutes)\n", + "\n", + "Allocation of places\n", + "\n", + "Number of places: 640. No restrictions with regard to available places for Bachelor's students of Wirtschafts-\n", + "wissenschaft (Business Management and Economics), Wirtschaftsmathematik (Mathematics for Economics)\n", + "and Wirtschaftsinformatik (Business Information Systems). The remaining places will be allocated to students\n", + "of other subjects. Should the number of applications exceed the number of available places, places will be allo-\n", + "cated in a standardised procedure among all applicants irrespective of their subjects according to the following\n", + "quotas: Quota 1 (50% of places): total number of ECTS credits already achieved in the respective degree subject;\n", + "among applicants with the same number of ECTS credits achieved, places will be allocated by lot. Quota 2 (25%\n", + "of places): number of subject semesters of the respective applicant; among applicants with the same number of\n", + "\n", + "subject semesters, places will be allocated by lot. Quota 3 (25% of places): allocation by lot. Applicants who al-\n", + "ready have successfully completed at least one module component of the respective module will be given prefe-\n", + "rential consideration. Places on all courses of the module component with a restricted number of places will be\n", + "allocated in the same procedure. A waiting list will be maintained and places re-allocated as they become availa-\n", + "ble.\n", + "\n", + "Additional information\n", + "\n", + "--\n", + "\n", + "Referred to in LPO I (examination regulations for teaching-degree programmes)\n", + "\n", + "--\n", + "\n" + ] + } + ], + "source": [ + "modules = re.findall(Patterns_MS_IS.PATTERN_ENTIRE_MODULE.value, text_Module_Catalogue)\n", + "modules = clean_entries(modules, removal_patterns_BA_MM)\n", + "\n", + "for i in range (3):\n", + " print(modules[i])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/02_data_extraction/extract_keywords.ipynb b/02_data_extraction/extract_keywords.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b2b6c2ec432d9bc23969d6a5ceeab395789c9a2c --- /dev/null +++ b/02_data_extraction/extract_keywords.ipynb @@ -0,0 +1,246 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from keybert import KeyBERT\n", + "\n", + "pd.set_option('display.max_colwidth', None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def remove_newlines_at_start_end(df):\n", + " \"\"\"\n", + " Removes leading and trailing newlines from all columns of a pandas dataframe.\n", + " \"\"\"\n", + " # for all string columns, remove leading and trailing newlines\n", + " for col in df.select_dtypes(include=['object']).columns:\n", + " df[col] = df[col].str.strip('\\n')\n", + " return df\n", + "\n", + "df = pd.read_csv('MS_IS_all_modules.csv')\n", + "\n", + "def xlsx_to_csv(xlsx_file_path, csv_file_path):\n", + " df = pd.read_excel(xlsx_file_path)\n", + " print(df.head())\n", + " df.shape\n", + " df.to_csv(csv_file_path)\n", + "\n", + "\n", + "def extract_keywords_from_content(df):\n", + " df = remove_newlines_at_start_end(df)\n", + " kw_model = KeyBERT()\n", + " df['keywords'] = df['Contents'].apply(lambda x: ', '.join(kw[0] for kw in kw_model.extract_keywords(x, keyphrase_ngram_range=(1,2),\n", + " stop_words='english', \n", + " highlight=False,\n", + " top_n=4)))\n", + " return df\n", + "\n", + "\n", + "def extract_keywords_from_intended_learning_outcomes(df):\n", + " df = remove_newlines_at_start_end(df)\n", + " kw_model = KeyBERT()\n", + " df['keywords_learning'] = df['Intended learning outcomes'].apply(lambda x: ', '.join(kw[0] for kw in kw_model.extract_keywords(x, keyphrase_ngram_range=(1,2),\n", + " stop_words='english', \n", + " highlight=False,\n", + " top_n=4)))\n", + " return df\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('MS_IS_all_modules.csv') \n", + "\n", + "df = df.head(30)\n", + "df = extract_keywords_from_content(df) \n", + "df = extract_keywords_from_intended_learning_outcomes(df)\n", + "df[['Module title', 'keywords', 'Contents', ]].head(30)\n", + "\n", + "print(\"---------------SAME FOR INTENDED LEARNING OUTCOMES-------------------\")\n", + "\n", + "df = extract_keywords_from_intended_learning_outcomes(df) # Pass the dataframe to the function\n", + "df[['Module title', 'keywords', 'Contents', 'keywords_learning', 'Intended learning outcomes']].head(30)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Ansatz mit zugeordneten Schlagwörter (Ausblick --> erstmal verworfen) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import spacy\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "from sklearn.metrics.pairwise import cosine_similarity\n", + "\n", + "def assign_categories(dataframe):\n", + " # Define the predefined categories\n", + " categories = {\n", + " \"Artificial Intelligence\": [\"AI\", \"Machine Learning\", \"Deep Learning\", \"Neuronal Nets\"],\n", + " \"Strategy\": [\"Business Strategy\", \"Market Analysis\", \"Competitive Intelligence\"],\n", + " \"Marketing\": [\"Digital Marketing\", \"Social Media Marketing\", \"Market Research\"],\n", + " \"Optimization\": [\"Operations Optimization\", \"Process Improvement\", \"Supply Chain Optimization\"],\n", + " \"Data Science\": [\"Data Analysis\", \"Data Mining\", \"Statistical Modeling\"],\n", + " \"Software Engineering\": [\"Software Development\", \"Programming\", \"Web Development\", \"\"],\n", + " \"Society and Ethics\": [\"Ethical Issues\", \"Social Impact\", \"Sustainability\", \"Privacy\"],\n", + " \"Finance\": [\"Financial Analysis\", \"Financial Markets\", \"Accounting\", \"Financial Reporting\"],\n", + " \"Management\": [\"Leadership\", \"Project Management\", \"Team Management\", \"Change Management\"],\n", + " \"Communication\": [\"Presentation Skills\", \"Negotiation\", \"Stakeholder Management\", \"Conflict Management\"],\n", + " \"Entrepreneurship\": [\"Business Development\", \"Innovation\", \"Startups\", \"Venture Capital\"],\n", + " \"Blockchain\": [\"Distributed Ledger\", \"Smart Contracts\", \"Cryptocurrencies\", \"Decentralized Applications\"],\n", + " \"Internet of Things\": [\"IoT Devices\", \"IoT Platforms\", \"IoT Security\", \"IoT Data Management\"],\n", + " }\n", + "\n", + " # Initialize the NLP model (spacy)\n", + " nlp = spacy.load(\"en_core_web_sm\")\n", + "\n", + " # Extract the names of predefined categories\n", + " category_names = list(categories.keys())\n", + "\n", + " # Create a TF-IDF vectorizer\n", + " vectorizer = TfidfVectorizer()\n", + "\n", + " # Fit and transform the predefined category names\n", + " category_vectors = vectorizer.fit_transform(category_names)\n", + "\n", + " # Iterate over the rows in the DataFrame\n", + " assigned_categories = []\n", + " for index, row in dataframe.iterrows():\n", + " # Extract the row name\n", + " row_name = row[\"Module title\"]\n", + "\n", + " # Calculate the similarity between the row name and predefined categories\n", + " row_vector = vectorizer.transform([row_name])\n", + " similarities = cosine_similarity(row_vector, category_vectors)[0]\n", + "\n", + " # Find the index of the most similar category\n", + " max_index = similarities.argmax()\n", + "\n", + " # Assign the category based on the index, if scores are less than 0.75, assign \"Other\"\n", + " if similarities[max_index] < 0.000008:\n", + " assigned_category = \"Other\"\n", + " else:\n", + " assigned_category = category_names[max_index]\n", + " \n", + "\n", + " # Add the assigned category to the list\n", + " assigned_categories.append(assigned_category)\n", + "\n", + " # Add the assigned categories to the DataFrame\n", + " dataframe[\"Assigned Category\"] = assigned_categories\n", + "\n", + " return dataframe\n", + "\n", + "# Example usage\n", + "\n", + "df = pd.read_csv('MS_IS_all_modules.csv')\n", + "\n", + "df = pd.DataFrame(df)\n", + "df_with_categories = assign_categories(df)\n", + "#print only the columns we need\n", + "df_with_categories = df_with_categories[['Module title', 'Assigned Category']]\n", + "print(df_with_categories)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Ansatz über Zero-Shot-Classificator\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import pipeline\n", + "classifier = pipeline(\"zero-shot-classification\", model=\"facebook/bart-large-mnli\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "candidate_labels = [\n", + " \"Artificial Intelligence\",\n", + " \"Strategy\",\n", + " \"Marketing\",\n", + " \"Optimization\",\n", + " \"Data Science\",\n", + " \"Software Engineering\",\n", + " \"Society and Ethics\",\n", + " \"Finance\",\n", + " \"Management\",\n", + " \"Communication\",\n", + " \"Entrepreneurship\",\n", + " \"Internet of Things\",\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('MS_IS_all_modules.csv')\n", + "\n", + "print(df['Module title'][5])\n", + "text = df['Module title'][5]\n", + "print(text)\n", + "\n", + "output = classifier(text, candidate_labels, device=0)\n", + "df = pd.DataFrame({'label': output['labels'], 'score': output['scores']})\n", + "nr_of_results = 3\n", + "df = df.sort_values(by=['score'], ascending=False).head(nr_of_results)\n", + "print(df)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "enterpriseai2", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/02_data_extraction/helper_methods.py b/02_data_extraction/helper_methods.py new file mode 100644 index 0000000000000000000000000000000000000000..2985212a3de86086cd9af932d34b1a1614de046d --- /dev/null +++ b/02_data_extraction/helper_methods.py @@ -0,0 +1,31 @@ +# Generic methods to apply regex and clean text +import re +import csv +import os + +def extract_first_match(text, regex_pattern): + pattern = re.compile(regex_pattern) + match = pattern.search(text) + if match: + return match.group(1) + else: + return None + +def extract_LineMatch(text, regex_pattern): + pattern = re.compile(regex_pattern, re.MULTILINE) + match = pattern.search(text) + if match: + return match.group() + else: + return None + +def clean_entries(matches, patternsToRemove): + cleaned_entries = [] + for entry in matches: + cleaned_text = entry + for pattern in patternsToRemove: + cleaned_text = re.sub(pattern, "", cleaned_text, flags=re.MULTILINE) + cleaned_entries.append(cleaned_text) + + return cleaned_entries + diff --git a/02_data_extraction/module_catalogues/BA_IS_all_modules.pdf b/02_data_extraction/module_catalogues/BA_IS_all_modules.pdf new file mode 100644 index 0000000000000000000000000000000000000000..815210dda22563dd9713d69962d1ee453478da7d --- /dev/null +++ b/02_data_extraction/module_catalogues/BA_IS_all_modules.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:304162843305df6de0297f6797edc8ed9fa7d287c57fbc36135f74d80c96cfcd +size 1365797 diff --git a/02_data_extraction/module_catalogues/BA_MM_all_modules.pdf b/02_data_extraction/module_catalogues/BA_MM_all_modules.pdf new file mode 100644 index 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Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This course provides students with an in-depth overview of the structure and the application areas of business +management information systems in enterprises and public institutions. + +Outline of syllabus: +1. What is software: concepts, categories, application +2. Software life cycle: duration, phases, steps +3. As-is analysis: tasks, problems +4. To-be concept: system design, data design, dialog design, function design +5. Object orientation: paradigm shift +6. Change management: meaning, methodologies, project management +7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to +(i) understand the importance of integration in enterprises, especially in information systems; +(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require- +ments, which brings a software implementation with; +(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply +(with participation in the exercise); +(iv) understand the importance of change management and project management and know the appropriate me- +thods for specific applications.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content: +This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage- +ment. + +Outline of syllabus: +1. Organisation and distinction +2. IT strategy +3. IT organisation +4. Management of IT systems +5. Enterprise Architecture Management +6. IT project management +7. IT security +8. IT law +9. IT controlling + +Reading: + +• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden. +• Tiemeyer: Handbuch IT-Management, Munich. +• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to +1. overview the different aspects to be considered regarding a purposeful IT management; +2. understand and apply appropriate methods and tools; +3. independently perform system search and selection in a team project (only after participation in the practice + +lessons).",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content: +In small project teams of 4 to 10 members, students will spend several months actively working on a specific and +realistic problem with practical relevance. They will progress through several project stages including as-is analy- +sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen- +dently and will only receive advice and minor support from research assistants. + +Reading: +will vary according to topic","After completing the course ""Projektseminar"", students will be able to +1. analyze business tasks and requirements and generate fitting IS solutions; +2. apply project management methods; +3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution +(approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1 +Language of assessment: German, English +Creditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), +data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua- +ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me- +thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).","The students possess theoretical and practical knowledge in the area of information retrieval and have acquired +the technical know-how to create a search engine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program +quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo- +dern computer systems, as well as the measures implemented to protect against these attacks. In the course, +the following topics are discussed: + +• x86-64 instruction set architecture and assembly language +• Runtime attacks (code injection, code reuse, defenses) +• Web security +• Blockchains and smart contracts +• Side-channel attacks +• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con- +cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci- +ses allow students to gain hands-on experience with attacks and analysis of systems from an attacker's perspec- +tive.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, LR, HCI, ES. +Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,"The students possess a fundamental and applicable knowledge about advanced topics in software engineering +with a focus on modern software architectures and fundamental approaches to model-driven software enginee- +ring.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, +propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, +search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia- +bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of +measured data, planning and evaluation of simulation experiments, special random processes, possibilities and +limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation +projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of +(technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu- +lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro- +grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions +and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co- +de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis- +cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are +then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par- +allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces- +sing.","V (2) + Ü (2) +Module taught in: English","written examination (90 to 120 minutes) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for +NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) +and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite- +rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de- +tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili- +stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. +The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing mostly for English. They are able to solve problems through the methods +taught. They have gained experience in the application of text mining algorithms.","The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing. They are able to solve practical problems with the methods acquired in +class. They have gained experience in the application of text mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important +basics as well as the most recent approaches to image representation, image processing and image analysis are +taught. Actual models and methods of machine learning as well as their technical backgrounds are presented +and their respective applications in image processing are shown.","Students have fundamental knowledge of problems and techniques in the field of computer vision and are able +to independently identify and apply suitable methods for concrete problems.","V (2) + Ü (2) +Module taught in: English","Written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in- +formation systems and social media in the World Wide Web, but also for various social, economic and biologi- +cal systems. What can we learn from data that capture the interaction topology of such complex systems? What +is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do +these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most +influential actors in a social network? And how can we analyze time series data on systems with dynamic net- +work topologies? +Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts +for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to +practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari- +ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles +of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha- +stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma- +terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, +which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen +their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final +written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri- +ven modelling of complex technical, social, and biological systems. Students will understand how we can quan- +titatively model the topology of networked systems and how we can detect and characterize topological pat- +terns. Participants will learn how to use analytical methods to make statements about the expected properties of +very large networks that are generated based on different stochastic models. They further gain an analytical un- +derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree +distributions influence the robustness of systems, and how emergent network features emerge from simple ran- +dom processes.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): + +IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process +model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning +methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, +SVM), learning methods for special data types, further learning paradigms.","The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da- +ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of +the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use +or implementation of data mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE,SEC",150 h,--,-- +Business Software 1: IS-based Enterprise Management,12-GPU-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This module provides students with an overview of the structure of a business information system (SAP Business +ByDesign) in depth. +Outline of syllabus: +1. Integrated information systems: integration, standard software, system architecture +2. Working with standard business software +3. Consulting in integrated information systems: project management, project organisation, presentation skills +Description: +The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small +groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the +software, dealing with a wide variety of business processes. +If you would like to register for this course, please submit an application to the consultants (cover letter, CV, cer- +tificates; please also specify your degree programme and student ID number).","After completing the course ""Business Software 1"", students will be able to +(i) understand an ERP system in its depth; +(ii) understand the interaction of business processes; +(iii) execute business tasks and processes in an ERP system independently (after participation in the practice +lessons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +c) Term paper (15 to 20 pages) or +Creditable for bonus +Language of assessment: German and/or English +Assessment offered: Once a year, winter semester","20 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Software 2: Enterprise Resource Planning Systems,12-M-ERP-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This module provides students with an overview of the structure of business information systems in width as +well as the selection and implementation of business information systems in organisations. + +Outline of syllabus: +1. Integrated information systems: integration, standard software, system architectures, operating models +2. Selection of integrated information systems: methods, cost-benefit analysis +3. Implementation of integrated information systems: project management, project organisation, project marke- + +ting + +The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small +groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the +software, dealing with a wide variety of business processes.","After completing the course ""Business Software 2"", students will be able to +1. differentiate between system architectures and -philosophies; +2. understand the interaction of business processes; +3. come to a selection decision for an ERP system using a structured approach and compare different ERP sy- + +stems; + +4. execute business tasks and processes in an ERP system independently (after participation in the practice les- + +sons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +c) Term paper (15 to 20 pages) or +Creditable for bonus +Language of assessment: German and/or English +Assessment offered: Once a year, summer semester","20 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Advanced Seminar: Enterprise Systems,12-M-ES-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the fields of informati- +on systems and enterprise systems. + +Reading: +will vary according to topic","After completing the course ""Enterprise Systems"", students will be able to +1. understand the fundamentals of scientific literature reviews; +2. integrate elaborated content in a scientific thesis; +3. create presentations independently.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Decision Support Systems,12-M-DSS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course discusses advanced approaches for modelling and solving decision problems in business settings. +The acquired insights are used to design and implement decision support systems using standard software tools +(Python).","After successfully completing the course, students should be able to + +• Understand the structure of classic business decision problems +• Isolate key elements from general problem descriptions and convert them to quantitative decision models +• Solve different classes of optimization problems (linear, network, integer, multi-objective, non-linear, + +stochastic) + +• Implement decision support systems",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Analytical Information Systems,12-BI-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course provides an overview of the structure and applications of analytical information systems. A special fo- +cus is on individual quantitative methods of data analysis. On the one hand, methods from the areas of data pre- +paration and data manipulation as well as their practical application are introduced. On the other hand, an intro- +duction to methods and the application of machine learning methods for predictive analytics, in particular neural +networks and deep learning, is given.","The module provides students with knowledge of: + +• Data Manipulation +• Data Engineering +• Descriptive Analytics +• Predictive Analytics and Data Mining +• Supervised Learning +• Unsupervised Learning +• Neural Networks and Deep Learning +• Text Mining +• Big Data Technologies",V (2) + Ü (2),"Written examination (approx. 60 Minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +WM1: +Should the number of applications exceed the number of available places, places will be allocated as follows: +1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Analytics,12-M-BUA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the field of business +management decision models and methods and their application in the development of decision-support sy- +stems as well as analytical information systems and quantitative methods of data analysis. + +Students work on current topics using methods from machine learning, mathematical optimization and simulati- +on.","The module provides students with knowledge of: + +• Scientific literature +• Implementation of methods in code +• Integration of developed results in scientific papers +• Creating presentations and lectures",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +E-Business Strategies,12-M-IBS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of strategic implications of digital technologies at the level of organisations, +industries and value networks. To this end, concepts and frameworks from strategic technology management are +applied to digital innovations and illustrated with numerous examples. In the accompanying exercise, case stu- +dies of well-known digital companies and their business models are analysed and discussed.","- Understand theoretical concepts of strategy development and implementation in the context of digital techno- +logies. + +- Apply different frames of reference and understand their strengths and weaknesses in the context of practical +application. + +- Transfer the concepts to real business situations",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Mobile and Ubiquitous Systems,12-M-MUS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of technologies and business applications of mobile & ubiquitous computing. +Concepts and applications are illustrated using numerous examples from mobile telecommunications to the In- +ternet of Things. In the accompanying exercise, corresponding case study texts are analysed and discussed.","- Understand the technological basics of mobile & ubiquitous computing. + +- Analysing business applications in processes, products/services and business models + +- Apply the concepts learned to real-life problems in a business context",Ü (2) + V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Seminar: E-Business Strategies,12-M-SEBS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the fields of web-ba- +sed platforms (electronic markets, Web 2.0 etc.) and strategic management of a company.","- Academic literature review + +- Integration of developed results in scientific papers + +- Creating presentations and talks",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Corporate Entrepreneurship,12-M-UGF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This module is a theory-led and practice-oriented primer on corporate entrepreneurship. It provides you with +knowledge useful for anyone aiming at working (or researching) in the field of corporate innovation and entrepre- +neurship or at pursuing an ‘intrapreneurial’ or entrepreneurial career. + +(1) Introduction to corporate entrepreneurship + +(2) Antecedents and forms of corporate entrepreneurship + +(3) Corporate strategy and corporate entrepreneurship + +(4) Organizational structure and corporate entrepreneurship + +(5) Human resource management and corporate entrepreneurship + +(6) Building supportive organizational cultures + +(7) Entrepreneurial control systems + +(8) Entrepreneurial leadership + +(9) The corporate entrepreneur as a champion and diplomat + +(10) The pay-off from corporate entrepreneurship + +(11) Corporate venture capital + +(12) Corporate entrepreneurship in nonprofit and government organizations + +(13) Universities and academic spin-offs + +(14) Wrap-up and Q&A","Educational aims + +• Clarify the role of corporate entrepreneurship +• Explain theoretical concepts and mechanisms behind corporate entrepreneurship +• Enable students to critically appraise alternative approaches to corporate entrepreneurship +• Enable students to evaluate the boundaries and risks of corporate entrepreneurship + +Learning outcomes + +On successful completion of this module students will be able to: + +• Create and evaluate concepts related to corporate entrepreneurship +• Assess the role of corporate entrepreneurship for creating and sustaining competitive advantage +• Make judgements about the organizational and managerial implications of corporate entrepreneurship +• Systematically choose between different routes of action","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of +one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, +groups of 3 approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Digital Entrepreneurship,12-M-UGF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This module provides an introduction into digital entrepreneurship and digital transformation. (1) Introduction +(2) Digital business models (3) Identifying and exploiting opportunities for digital entrepreneurship (4) Strategies +for creating competitive advantage in digital entrepreneurship (5) Digital marketing for entrepreneurs (6) Crowd- +funding for entrepreneurs (7) Design thinking (8) Lean startup (9) Platform ecosystems and online communities +(10) Digital strategy and digital transformation (11) The agile organization (12) Crowdsourcing (13) Cyberfraud (14) +Wrap-up and Q&A","Educational aims: Clarify the role of digital entrepreneurship and digital transformation. Explain theoretical con- +cepts and mechanisms behind digital entrepreneurship and digital transformation. Enable students to critically +appraise alternative approaches to digital entrepreneurship and digital transformation. Enable students to eva- +luate the boundaries and risks of digital entrepreneurship and digital transformation +Learning outcomes: On successful completion of this module students will be able to (1) Assess the role of di- +gital entrepreneurship and digital transformation for creating and sustaining competitive advantage, (2) Crea- +te and evaluate concepts related to digital entrepreneurship and digital transformation, (3) Make judgements +about the organizational and managerial implications of digital entrepreneurship and digital transformation, (4) +Systematically choose between different routes of action.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) log (15 to 20 pages) or c) oral examination (one candida- +te each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation +and present the key insights from their work.","Educational aims + +• Enable students to position their research +• Enable students to critically review a substantial body of literature in short time +• Enable students to develop a sound theoretical framework +• Enable students to create a research paper fully meeting academic standards + +Learning outcomes + +On successful completion of this module students will be able to: + +• Differentiate their research from previous work +• Adopt theoretical perspectives to understand complex phenomena +• Engage in comprehensive academic reasoning +• Articulate abstract and complex phenomena and relationships in written and oral form",S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Global Logistics & Supply Chain Management,12-M-GLSC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Global Logistics & Supply Chain Management"" acquaints students with advanced methods for the +planning of global production networks and demonstrates the application of these with the help of multiple case +studies.","After completing this course students can +(i) analyze and evaluate global production networks; +(ii) develop and apply appropriate methods to plan production networks; +(iii) evaluate the consequences of uncertainties in processes and apply concepts and methods to plan uncertain +processes.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Advanced Operations & Logistics Management,12-M-AOLM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Advanced Operations & Logistics Management"" acquaints students with advanced methods for the +planning of integrated production and logistics systems and demonstrates the application of these with the help +of multiple case studies","After completing this course students can +(i) analyze and evaluate integrated production and logistics systems; +(ii) develop and apply appropriate methods to plan complex production and logistics systems; +(iii) evaluate the consequences of uncertainties in processes, and +(iv) apply concepts and methods to plan uncertainties processes.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Seminar: Operations Management,12-M-SN-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"With the help of topics from the area of ""Operations Management"", this course will provide students with know- +ledge and skills that will enable them to prepare a well-structured term paper and to present the key results of +their work.","Students will learn how to convince a critical audience by giving a presenation regarding a topic from the area +of Operations Management. By developing and giving a presentation as well as by answering questions the stu- +dents will practice their skills to deal with difficult communication situations and to argument for and against a +certain topic.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English",--,--,300 h,--,-- +Adaption and Continuous System Engineering,12-ACSE-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Business Suite: The constantly changing environment with its organisational and IT-oriented developments +forces companies to adapt their standard business software solutions. With the help of dynamic adaptation +(Continuous System Engineering), this process of change can be supported effectively and efficiently. This mo- +dule discusses both the systematic implementation of adaptation steps (so-called customising) using the exam- +ple of the mySAP Business Suite and the concept of Continuous System Engineering using various practical ex- +amples. Business Apps: The course combines theory and practice in the area of cloud computing and ERP. Par- +ticipants gain an insight into the architecture of the ByDesign platform and are presented with an opportunity to +gain practical experience working with the corresponding software development kit. + +Content: + +• Fundamentals of cloud computing +• Cloud business solutions +• Architecture of the SAP Business ByDesign platform +• Platform adaption and extensibility +• Basics of software development in SAP Cloud Applications Studio +• Hands-on SDK: independently designing and developing a demo app","Business Suite: Students learn about the various ways of adapting a standard business software solution to the +special requirements of a company. They also develop a fundamental understanding of the dynamic adaptation +of business software libraries. Based on selected examples from the SAP Business Suite that the acquired know- +ledge will be deepened by using case studies. Business Apps: The course imparts knowledge and delivers skills +in cloud computing for businesses, ERP systems architecture and software development at the example of the +SAP Business ByDesign platform. The independent planning, implementation and documentation of a business +app trains important core competencies of technology-oriented Business Informatics.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) oral examination (one can- +didate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Business Service Platforms 2,12-AGP2-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The next generation of business service platforms leads to a transformation of traditional industrial enterprises +into service businesses that generate a large proportion of value in developed economies. New ICT technologies +such as cloud computing, the Internet of Things and semantic technologies will contribute to the success of the- +se businesses in a similar way as ERP contributed to the success of industrial enterprises. But we are still at the +beginning of the evolution of business service platforms, which will have to become more adaptable to support +special business models and allow differentiating customer service processes. +The course will discuss different case studies on services businesses. The digital transformation of the software +industry into a service industry is the most prominent of these case.","Be aware of the growing economic importance of the service sector. Understand that services businesses in are +facing a special productivity problem, which could not be adressed by the same processes applied in the ma- +nufacturing industries. Understand the new ICT technologies we have at hand today to deliver smart solutions +for this problem. Be aware of the diversity of services business today where we have no evidence that a general +standard can be found applicable to most subsectors similar to the standardization achieved for the manufactu- +ring industries after twenty years of research.",V (2),"Written examination (approx. 60 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,"-- + +_x000C_" +Business Service Platforms 1,12-BSA-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"A next generation of enterprise systems called business service platforms is emerging using new disruptive tech- +nologies such as cloud computing, big data and mobility. These business service platforms apply the concept of +product platforms to software. They will +1. be services based +2. be offered as a service in the cloud +3. address new classes of users and types of business especially in the service business +4. allow for a high degree of business adaptability and extensibility. +5. be supplemented by a broad offer of partner add-ons supporting accelerated innovation. +These new business service platforms will play a key role in the digital transformation of the software industry.","Be aware of the big business productivity progress enabled by BIS in the last 50 years. Understand the limitati- +ons of these systems in spite of the digital transformation of the software industry ahead. Be able to critically as- +sess the business potential of new IC technologies. Understand the business demand for change. Understand +the necessary organizational learning needed to leverage new technology for business change management.",V (2),"Written examination (approx. 60 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Abbreviation,"Business Processes Organisation, Business Software and Process Industries",Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"ERP systems have become key elements of successful companies. Business processes in companies can no lon- +ger be managed without using such ERP systems. In financial departments of companies, such systems have be- +en used for a long time, but business processes e. g. for logistical tasks have so far not been supported by ERP +solutions. This module explains how this issue could be resolved as well as what constraints and what depen- +dencies have to be considered.","After completing this module, students should be able to +(i) know about actual business processes in companies; +(ii) understand selected problems in the organization and design of logistical business processes and work out +solutions; +(iii) know and design basic data structures and data flows of an ERP system; +(iv) map businesss processes within an ERP system; +(v) consider the specifics of a certain industry (e. g. the process industry) when organizing business processes; +(vi) map the core business processes within an ERP system.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Work and Information,12-ITA-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This module discusses relevant principles, concepts and applications of business information processing and its +impact on organisational and process structures in today's business world.","The expertise gained from other modules related to business management issues can be interpreted and clas- +sified in a certain way by participating in this module. For decisions in regards to human resources planning, in- +vestment, and a company's strategy, the students will get to know all the relevant concepts and interdependen- +cies, which come with taking information processing into account as the so called ""fourth"" factor of production.",V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Work Order Planning for Automated Manufacturing,12-M-AGAF-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The idea of integration of business information systems is primarily practiced and developed as an ERP system +in terms of business application areas, their temporal overlap (data warehouse), their spatial relationship (sup- +ply network) and connection of legal tasks (eGovernment). However, linking the commercial view of incoming cu- +stomer orders with the logistic or more technical view of the scheduling of production orders and the resulting +consequences for the processes is a critical success factor.","Linking research and lectures of the Institute of Robotics and Telematics as well as the orientation of the Chair of +Business Integration allows students a conceptual as well as practical insight into the challenges of this in the +future essential part of the operational automation development.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Topics in Business Information Systems 1,12-M-ATW1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer- +sity of Wuerzburg.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap- +prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: +approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Business Information Systems 2,12-M-ATW2-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer- +sity of Wuerzburg.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap- +prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: +approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Information systems research,12-M-ISR-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The course provides an overview of theoretical scientific foundations, theories, research topics and methods of +international research in business informatics.","The module provides students with knowledge of: +(i) Exploration of classical themes of WI / IS research; +(ii) Getting to know the relevant paradigms, theories and methods; +(iii) Recognition of the interfaces to other areas of business administration and management practice; +(iv) Gain experience in finding and evaluation of scientific literature",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 15 to 20 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Databases 2,10-I=DB2-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Data warehouses and data mining; web databases; introduction to Datalog.,"The students have advanced knowledge about relational databases, XML and data mining.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, HCI.",150 h,--,-- +Compiler Construction,10-I=CB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Lexical analysis, syntactic analysis, semantics, compiler generators, code generators, code optimisation.","The students possess knowledge in the formal description of programming languages and their compilation. +They are able to perform transformations between them with the help of finite automata, push-down automata +and compiler generators.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,GE",150 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), +data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua- +ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me- +thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).","The students possess theoretical and practical knowledge in the area of information retrieval and have acquired +the technical know-how to create a search engine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,HCI,GE",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, +propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, +search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI",150 h,--,-- +Artificial Intelligence 2,10-I=KI2-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Planning, probabilistic closure and Bayesian networks, utility theory and decidability problems, learning from +observations, knowledge while learning, neural networks and statistical learning methods, reinforcement lear- +ning, processing of natural language.","The students possess theoretical and practical knowledge about artificial intelligence in the area of probabilistic +closure, learning and language processing and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI,GE",150 h,--,-- +E-Learning,10-I=EL-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Learning paradigms, learning system types, author systems, learning platforms, standards for learning systems, +intelligent tutoring systems, student models, didactics, problem-oriented learning and case-based training sy- +stems, adaptive tutoring systems, computer-supported cooperative learning, evaluation of learning systems.","The students possess a theoretical and practical knowledge about eLearning and are able to assess possible ap- +plications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program +quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IS,ES,GE",150 h,--,-- +Professional Project Management,10-I=PM-182-m01,Institute of Computer Science,holder of the Chair of Computer Science III,5,numerical grade,1 semester,graduate,"Project goals, project assignment, project success criteria, business plan, environment analysis and stakeholder +management, initialisation, definition, planning, execution/control, finishing of projects, reporting, project com- +munication and marketing, project organisation, team building and development, opportunity and risk manage- +ment; conflict and crisis management, change and claim management; contract and procurement management, +quality management, work techniques, methods and tools; leadership and social skills in project management, +program management, multiproject management, project portfolio management, PMOs; peculiarities of software +projects; agile project management/SCRUM, combination of classic and agile methods.","The students possess practically relevant knowledge about the topics of production management and/or pro- +fessional project management. They are familiar with the critical success criteria and are able to initiate, define, +plan, control and review projects.",V (4),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IT, IS, ES, LR, HCI, GE.",150 h,--,-- +Algorithms for Geographic Information Systems,10-I=AGIS-161-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Algorithmic foundations of geographic information systems and their application in selected problems of acqui- +sition, processing, analysis and presentation of spatial information. Processes of discrete and continuous opti- +misation. Applications such as the creation of digital height models, working with GPS trajectories, tasks of spa- +tial planning as well as cartographic generalisation.","The students are able to formalise algorithmic problems in the field of geographic information systems as well as +to select and improve suitable approaches to solving these problems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IS,HCI",150 h,--,-- +Real-Time Interactive Systems,10-HCI=RIS-182-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"This course provides an introduction into the requirements, concepts, and engineering art of highly interactive +human-computer systems. Such systems are typically found in perceptual computing, Virtual, Augmented, Mixed +Reality, computer games, and cyber-physical systems. Lately, these systems are often termed Real-Time Interac- +tive Systems (RIS) due to their common aspects. +The course covers theoretical models derived from the requirements of the application area as well as common +hands-on and novel solutions necessary to tackle and fulfill these requirements. The first part of the course will +concentrate on the conceptual principles characterizing real-time interactive systems. Questions answered are: +What are the main requirements? How do we handle multiple modalities? How do we define the timeliness of +RIS? Why is it important? What do we have to do to assure timeliness? The second part will introduce a concep- +tual model of the mission-critical aspects of time, latencies, processes, and events necessary to describe a sy- +stem's behavior. The third part introduces the application state, it's requirements of distribution and coherence, +and the consequences these requirements have on decoupling and software quality aspects in general. The last +part introduces some potential solutions to data redundancy, distribution, synchronization, and interoperability. +Along the way, typical and prominent state-of-the-art approaches to reoccurring engineering tasks are discussed. +This includes pipeline systems, scene graphs, application graphs (aka field routing), event systems, entity and +component models, and others. Novel concepts like actor models and ontologies will be covered as alternative +solutions. The theoretical and conceptual discussions will be put into a practical context of today's commercial +and research systems, e.g., X3D, instant reality, Unity3d, Unreal Engine 4, and Simulator X.","After the course, the students will have a solid understanding of the boundary conditions defined by both, the +physiological and psychological characteristics of the human users as well as by the architectures and technolo- +gical characteristics of today's computer systems. Participants will gain a solid understanding about what they +can expect from today's technological solutions. They will be able to choose the appropriate approach and tools +to solve a given engineering task in this application area and they will have a well-founded basis enabling them +to develop alternative approaches for future real-time interactive systems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): HCI. +Cf. Section 3 Subsection 3 Sentence 8 FSB (subject-specific provisions).",150 h,--,-- +Logic Programming,10-I=LP-172-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Logic-relational programming paradigm, top-down evaluation with SLD(NF) resolution. Introduction to the logic +programming language Prolog: recursion, predicate-oriented programming, backtracking, cut, side effects, ag- +gregations. Connection to (deductive) databases. Comparison with Datalog, short introduction of advanced con- +cepts like constraint logic programming.","The students have fundamental and practicable knowledge of logic programming. They are able to implement +compact and declarative programs in Prolog, and to compare this approach to the traditional imperative pro- +gramming paradigm.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +SE, IT, IS.",150 h,--,-- +Machine Learning for Natural Language Processing,10-I=NLP-182-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture conveys advanced knowledge about methods in computational text processing. To this end, it pres- +ents state of the art models and techniques in the area of machine learning, as well as their technical back- +ground, and their respective applications in Natural Language Processing. As one important building block of +almost all modern NLP-models, different techniques for learning representations of words, so called Word Em- +beddings, are presented. Starting from this we cover, among others, models from the area of Deep Learning, li- +ke CNNs, RNNs and Sequence-to-Sequence architectures. The theoretical foundations of these models, like their +training with Backpropagation, are also covered in depth. For all models presented in the lecture, we show their +application to problems like sentiment analysis, text generation and machine translation in practice.","The participants have solid knowledge on problems and methods in the area of computational text processing +and are able to identify and apply suitable methods for a specific task.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IS, HCI.",150 h,--,-- +Medical Informatics,10-I=MI-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Electronic patient folder, coding of medical data, hospital information systems, operation of computers in infir- +mary and functional units, medical decision making and assistance systems, statistics and data mining in medi- +cal research, case-based training systems in medical training.","The students possess theoretical and practical knowledge about the application of computer science methods in +medicine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,HCI,GE",150 h,--,-- +Performance Engineering & Benchmarking of Computer Systems,10-I=PEB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Introduction to performance engineering of commercial software systems, performance measurement techni- +ques, benchmarking of commercial software systems, modelling for performance prediction, case studies.","The students possess a fundamental and applicable knowledge in the areas of performance metrics, measure- +ment techniques, multi-factorial variance analysis, data analysis with R, benchmark approaches, modelling with +queue networks, modelling methods, resource demand approximation, petri nets.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Programming with neural nets,10-I=PNN-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for +NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) +and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite- +rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IT, IS, HCI, GE.",150 h,--,-- +Robotics 1,10-I=RO1-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VII,8,numerical grade,1 semester,graduate,"History, applications and properties of robots, direct kinematics of manipulators: coordinate systems, rotations, +homogenous coordinates, axis coordinates, arm equation. Inverse kinematics: solution properties, end effec- +tor configuration, numerical and analytical approaches, examples of different robots for analytical approaches. +Workspace analysis and trajectory planning, dynamics of manipulators: Lagrange-Euler model, direct and inver- +se dynamics. Mobile robots: direct and inverse kinematics, propulsion system, tricycle, Ackermann steering, ho- +lonomes and non-holonome restrictions, kinematic classification of mobile robots, posture kinematic model. +Movement control and path planning: roadmap methods, cell decomposition methods, potential field methods. +Sensors: position sensors, speed sensors, distance sensors.","The students master the fundamentals of robot manipulators and vehicles and are, in particular, familiar with +their kinematics and dynamics as well as the planning of paths and task execution.","V (4) + Ü (2) +Module taught in: English","written examination (approx. 60 to 90 minutes) +Separate written examination for Master's students. +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IS, +ES, LR, HCI, GE.",240 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo- +dern computer systems, as well as the measures implemented to protect against these attacks. In the course, +the following topics are discussed: + +• x86-64 instruction set architecture and assembly language +• Runtime attacks (code injection, code reuse, defenses) +• Web security +• Blockchains and smart contracts +• Side-channel attacks +• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con- +cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci- +ses allow students to gain hands-on experience with attacks and analysis of systems from an attacker's perspec- +tive.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, LR, HCI, ES. +Basic programming knowledge in C is required.",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia- +bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of +measured data, planning and evaluation of simulation experiments, special random processes, possibilities and +limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation +projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of +(technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu- +lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,ES,GE",240 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,"The students possess a fundamental and applicable knowledge about advanced topics in software engineering +with a focus on modern software architectures and fundamental approaches to model-driven software enginee- +ring.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de- +tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili- +stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. +The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing mostly for English. They are able to solve problems through the methods +taught. They have gained experience in the application of text mining algorithms.","The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing. They are able to solve practical problems with the methods acquired in +class. They have gained experience in the application of text mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IT, HCI.",150 h,--,-- +Project - Current Topics in Computer Science,10-I=PRJAK-162-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Completion of a project task (in Teams).,The project allows participants to work on a problem in computer science in teams.,P (4),"project report (10 to 15 pages) and presentation of project (15 to 30 minutes) +Each project is offered one time only. The project will not be repeated; there will not be another project with the +same topic. Assessment can, therefore, only be offered for the project offered in the respective semester. +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +International Marketing,12-M-IMM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +The module builds on the knowledge acquired during the Bachelor's degree programme or the Grundstudium +(stage I studies). It provides a systematic introduction to strategic marketing decisions in global and internatio- +nal contexts. These are explained mainly by Porter's diamond and cluster models. Another focus is on internatio- +nalisation strategies, which require country analyses and decisions on the selection of national markets as well +as a timing of the countries market development. In addition, the module discusses different strategies for mar- +ket entry and market development. + +Outline of syllabus: +1. Internationalisation of the economy and regional integration processes + +• Globalisation +• Competitiveness of countries, industries and companies in an international context + +2. International strategic marketing decisions + +• Market entry forms +• Market development strategies +• Timing strategies +• International organisation structures + +3. Theories and strategies of internationalisation + +• Foreign trade theory +• Multinational enterprise +• Internationalisation strategies + +Reading: +Meffert, H. / Burmann C. / Becker, C.: Internationales Marketing-Management, Stuttgart etc. (most recent editi- +on). +Berndt, R. / Fantapié-Altobelli C. / Sander M.: Internationales Marketing-Management, Berlin etc. (most recent +edition).","Students acquire in-depth skills in the field of strategic and operational management with particular attention to +the international context. Students achieve particular expertise in the analysis, assessment and implementation +of international business decisions and gain skills thus guiding the execution of marketing and management po- +sitions in globally-active companies.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Brand Management & Market Research,12-M-MM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +At the beginning of the 21st century, marketing - until then interpreted as a market-oriented corporate manage- +ment approach - was further developed to be seen as the entrepreneurial task of creating ""shared value"" for the +organisation on the one hand and - broadly speaking - for society on the other hand. This idea leads to high re- +quirements regarding the strategic sustainable positioning of the brand as well as brand management itself. + +Outline of syllabus: +1. Brand leadership and brand assessment +2. Brand leadership, identity and relevance according to David Aaker's approach +3. Brand strategies +4. Consumer behaviour +5. Market research methods and the development of brand strategies +6. Market research methods","Based on the theories of Meffert and Aaker, students will gain a profound understanding for brand leadership, +which will be deepened by many pracital implications and examples. Provided by cases studies and market re- +search tools, it's the defined goal of this lecture to convey an in-depth knowledge for consumer behavior and su- +stainable brand management.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Strategic Networks in Industry,12-M-MS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"The primary object of this course is to gain a detailed understanding of strategic networks and of the phenome- +non of clustering in the industrial industry. The example of the international automotive industry is used for clari- +fication of the theoretical contents. +The focus is on marketing in industrial companies and also on CSR - CSR is considered the ""driver"" of sustaina- +ble innovations - as well as the different strategy types of sustainable innovations. +Outline of syllabus: +1. Strategic networks and clusters in industrial industries such as the automotive industry +2. Transaction types of Williamson as well as strategic cooperation between automobile manufacturers and sup- + +pliers + +3. Management of business types, in particular the business of suppliers in the automotive industry +4. Cluster and entrepreneurship activities +5. Sustainable innovation strategies","By the end of the course, students gain a profound understanding above the basics of network research. Further- +more students will aquire sectoral knowledge of the automotive industry as well as detailed cluster skills.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Strategic Marketing,12-M-SM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +The module raises awareness in students of the relevance and necessity of strategic management in a competiti- +ve and dynamical competitive process. + +Content: +Based on the marketing strategies as well as the stakeholder and entrepreneurship approaches, this module +discusses the roots of the concept of strategy in marketing based on Drucker, Porter, Ansoff and Mintzberg. The +focus of the module is on thinking in competitive advantages, which is directly related to responsible leadership. + +Outline of syllabus: +1. Competitive dynamics requires strategy and leadership +2. Marketing strategies, stakeholder management and entrepreneurship +3. Objectives and tasks of corporate governance in management practice +4. Competitive forces, strategies and benefits according to Michael Porter +5. Growth strategies and marketing myths +6. Future technologies, new businesses and dynamic capabilities +7. Nature and principles of responsible management + +Reading: +Barnard, CI (1938): The Functions of the Executive, Harvard University Press, Cambridge, Massachusetts. +Eschenbach, R.; Eschenbach, S.; Kunesch, H. (2008): Strategische Konzepte: Management-Ansätze von Ansoff +bis Ulrich, 5th ed., Schäffer-Poeschel Stuttgart. +Freeman, RE (2010): Strategic Management: A Stakeholder Approach, Cambridge University Press. +Grant, R. M.; Nippa, M. (2006): Strategisches Management: Analyse, Entwicklung und Implementierung von Un- +ternehmensstrategien, 5th ed., Pearson Munich. +Hinterhuber, H. H. (2011): Strategische Unternehmensführung -- I. Strategisches Denken, 8th ed., Erich Schmidt +Verlag, Berlin. +Hungenberg, H. (2012): Strategisches Management in Unternehmen: Ziele -- Prozesse -- Verfahren, 7th ed., +Gabler, Wiesbaden. +Johnson, G.; Scholes, K.; Whittington, R. (2009): Fundamentals of Strategy, 1st ed., Financial Times and Prentice +Hall Harlow. +Kotler, P.; Berger, R.; Bickhoff, N. (2010): The Quintessence of Strategic Management, Springer, Heidelberg. +Laasch, O.; Conaway RN (2014): The Principles of Responsible Management: Global Sustainability, Responsibili- +ty, and Ethics, Cengage Stamford. +Meffert, H.; Burmannn, C.; Kirchgeorg, M. (2012): Marketing -- Grundlagen marktorientierter Unternehmensfüh- +rung, 11th ed., Gabler, Wiesbaden. +Meyer, M. (1995): Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unter- +nehmung, Gabler, Wiesbaden. +Müller-Stewens, G.; Lechner, C. (2011): Strategisches Management -- Wie strategische Initiativen zum Wandel +führen, 4th ed., Schäffer-Poeschel Stuttgart. +Porter, M. (1999): Wettbewerb und Strategie, Econ Munich. (Original: Porter, M.: On Competition, Boston, 1998.) +Porter, M. (2014): Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frank- +furt / New York. (Original: Porter, M.: Competitive Advantage, New York, 1985) + +Porter, M. (2013): Wettbewerbsstrategie -- Methoden zur Analyse von Branchen und Konkurrenten, 12th ed., +Campus, Frankfurt / New York. (Original: Porter, M.: Competitive Strategy, New York, 1980) +Welge, M. K.; Al-Laham, A. (2012): Strategisches Management: Grundlagen -- Prozesse -- Implementierung, 6th +ed., Springer Wiesbaden.","The students have a deeper understanding of the sustainable corporate management and have the basics of the +competitive process and competitive dynamics available. In addition, they can use the acquired knowledge, whi- +le taking into account the conventional problems of the strategic and sustainable management, to solve busi- +ness case studys on their own.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Industrial Management 4,12-M-BE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This course will develop the objectives, principles and structure of electronically supported procurement proces- +ses with a special focus on catalogue-based procurement systems, electronic tendering systems, electronic (re- +verse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management sy- +stems.","The students will be able to describe and evaluate both the potentials and goals of electronic supported pro- +curement systens and will be able to design appropriate systems for real-life applications. Students will get in- +sight into the essentials of operational procurement management, especially e-procurement with a focus on ca- +talog-based procurement systems, electronic tendering systems, electronic (reverse) auctions, e-marketplaces, +supplier relationship management systems and eSupply chain management systems. After completing this mo- +dule, students can define and analyze the related tasks and processes and show or develop theory-based and +application-oriented possible solutions at a high professional level.",V (2) + Ü (2),"a) Written examination (approx. 40 to 60 minutes) or +b) Presentation (approx. 20 Minutes) and term paper (15 to 20 pages), weighted 1:1 or +c) Term paper (30 to 40 pages) or +d) entirely or partly computerised written examination (approx. 60 minutes) or +e) Portfolio (approx. 20 pages) +Creditable for bonus +Language of assessment: German and/or English","20 places. +(1) A total of 15 places will be allocated to students of the Master's degree programmes Management as well as +International Economic Policy. +Should the number of applications exceed 15, these places will be allocated by lot. A waiting list will be maintai- +ned and places re-allocated by lot as they become available. +(2) A total of 5 places will be allocated to students of the Master's degree programme Information Systems. +Should the number of applications exceed 5, these places will be allocated by lot. A waiting list will be maintai- +ned and places re-allocated by lot as they become available. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.","Module can be taught in form of E Learning course, seminar, workshop etc.",150 h,--,-- +Industrial Management 2,12-M-LA-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module analyses and classifies approaches of production planning and control. In addition, it develops +methods and models of lot sizing and scheduling. The focus is on the determination of optimal production and +transport volumes as well as the planning of orders and manufacturing orders.","Students learn essential concepts, principles and methods of production planning and control with emphasis on +the determination of optimal production and transport volumes as well as the planning of production and order +sequences. Then, based on this expertise related knowledge broadening and deepening, essential competen- +cies are conveyed, which allow the imaging of realistic situations and problems using mathematical and quanti- +tative models for the derivation and assessment of alternative courses of action. After completion of the modu- +le students can answer, analyze and structure questions of production planning and control, goal-oriented. They +can also arrange the planning areas in the overall business context and have an in-depth overview of the produc- +tion planning and control.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Industrial Management 1,12-M-SBM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"The course addresses central issues of strategic supply management. The supply function of the company +(purchasing, materials management, procurement logistics) and its strategic importance is analysed and basic +methods are developed that are relevant in this area.","Students learn the principles of performance-oriented optimization of all procurement activities to develop long- +term, competitively sensitive potential for success. After completion of the module students are able to prepa- +re structured, to goal-oriented analyze and to respond to performance-oriented issues of strategic procurement +based on key instruments. Students are able to accurately classify the tasks of the procurement and to describe +and discuss their strategic importance and dominate essential methods and procedures used in this area to ap- +ply.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Industrial Management 3,12-M-SPM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module will discuss contents and procedures of strategic production management and, in particular, plan- +ning and control concepts. +Students will become familiar with the essentials of strategic production management. Theoretical and analyti- +cal models will be used for analysing both economic and ecological issues. In addition, the module will discuss +principles of value structure optimisation and will develop competences regarding the development of integra- +ted mathematical models.","After completion of the module students are able to process, to analyze and answer questions of operations +strategy structured and goal-oriented in a global context using appropriate methods. Furthermore, they know +the main strategic tasks and objectives in production management and evaluate and apply planning and control +concepts for the production in realistic application situations.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Legal Foundations of Risk Management and Compliance,12-M-RM1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,2,numerical grade,1 semester,graduate,"Content: This module analyses the presentation of opportunities and risks in financial reports, i. e. annual or in- +terim reports, in conjunction with selected value-based management and profitability analysis approaches. + +Outline of syllabus: +1. Basics of financial reporting and risk management; +2. Practice of risk reporting; +3. Profitability analysis according to Penman; +4. Value-based management and risk management; +5. Residual income and business valuation; +6. Analysis of equity risk; +7. Analysis of credit risk; +8. Risk management monitoring by audit committees and auditors. + +Reading list to be provided in class.","After completing the course, the students will be able +1. to present the relation between risk management and financial reporting; +2. to analyze and solve independently complex problems with respect to the presentation of opportunities and + +risk in financial reports based on national and international standards; + +3. to identify the relation between risks and value-based management; +4. to evaluate independently selected research results concerning risk reporting and desing own research- or + +practice-oriented projects.",V (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus","30 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,60 h,--,-- +Financial Statement Analysis and Business Valuation,12-M-UA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,5,numerical grade,1 semester,graduate,"Fundamental investing involves valuation, and much of the information for valuation is contained in financial +statements. This module provides a basic understanding of financial statement analysis, particularly on how to +extract value-relevant information from financial statements, carry out financial statement analysis, and use fi- +nancial data to value corporations. The module also provides the necessary tools to gain insights into what ge- +nerates value in a corporation.","Students can understand publicly traded companies' financial statements (US GAAP/IFRS), identify value-rele- +vant information in financial statements, and use this information for valuation. They know the relevant techni- +ques to evaluate financial statements and understand the fundamental role of financial information in the valua- +tion process. Students can apply valuation technics to real-world cases and recommend investment decisions.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Philosophy of Science and Ethics in Business Management and Economics,12-M-WEW-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,10,numerical grade,1 semester,graduate,"This module will take the form of a seminar. Participants will independently work on a problem in economic poli- +cy or will review an important publication on a topic in economics.",Students are able to present the status of a current project in a talk as well as to discuss and defend it.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Risk Management - Concepts and Systems,12-RM-KS-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Accoun-,5,numerical grade,1 semester,graduate,"Concepts: The course will provide students with an overview of the main goals, contents, methods and instru- +ments of opportunity and risk management in industrial and commercial enterprises. Systems: The course will +provide students with an overview of the design and functionality of essential information systems for risk mana- +gement.","Concepts: After completion of the module students have a sound understanding of basic concepts, processes, +methods and tools of risk management. They are able to justify the duties and functions of risk management in +the company in theory and practice. They can also evaluate proposed solutions for the design of a risk manage- +ment system, analyze selected issues of risk management and building on that, develop their own solutions. Sy- +stems: After completing this module, students can +(i) judge legal, organizational and methodological requirements for the implementation of risk management pro- +cesses in a risk management information system (RMIS); +(ii) understand the technical basis for RMIS; +(iii) estimate the different characteristics of various information systems for the RM; +(iv) understand the workings of RMIS.",V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus","25 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Discounted Cashflow,12-M-CF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The module covers discounted cash flow (DCF) methods under certainty as well as uncertainty in the context of +the valuation of unlevered and levered companies. Furthermore, tax aspects as well as their influence on the +company value are considered. + +Syllabus: + +1. Introduction +2. DCF Theory under certainty + +1. NPV without taxes +2. NPV with personal taxes +3. NPV with corporate taxes +3. DCF Theory under uncertainty + +1. DCF basics +2. Valuation of unlevered companies +3. Valuation of levered companies + +4. Practice of DCF methods","After completion of this module, the students will know a variety of discounted cashflow techniques and are able +to apply properly them in order to evaluate projects or firms.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Portfolio and Capital Market Theory,12-M-CF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module conveys profound knowledge of individual portfolio choices and on this basis the most important +capital market theory (namely capital asset pricing model) is introduced, including its assumptions, implications +and extensions. + +Syllabus: + +1. Modern Portfolio Selection + +1. 2 Asset-Case +2. Multiple-Asset-Case +3. Critique of Portfolio Theory + +2. Capital Asset Pricing Model + +1. Assumptions and Derivation +2. Implications + +3. Empirical Aspects, Extensions and Alternatives","This module enables the students + +(i) to explain and to determine the optimal capital market position of an investor given the different investment +opportunities and individual utility function; + +(ii) to understand and use the central CAPM propositions for valuating risky assets.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Risk Management and Corporate Finance,12-M-CF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module deals with the valuation and use of classical derivatives in financial markets. In particular, futures, +swaps and options are considered as well as their possible applications in the context of financial risk manage- +ment. In particular, students will be introduced to the theory involved in pricing options, as well as important va- +luation parameters. In addition, some established risk measures such as value-at-risk are discussed. +1. Introduction +2. Futures & Forwards +3. Swaps +4. Options +5. Measures of risk","Upon completion of this module students will be able to, + +(i) independently determine the fair value of the derivatives discussed, as well as + +(ii) to understand and evaluate common capital market hedging strategies.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Risk measurement and risk valuation: Concepts and applications for banks,12-M-CF5-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The course augments the usual consideration of symmetric risk metrics by introducing metrics for downside risks +and the concept of risk as a capital requirement. The focus for applications in banks lies in the treatment of risks +with regard of supervisory regulations.","After completing the course “Risk measurement and risk valuation: Concepts and applications for banks” the +students are able +1. to judge the appropriateness and problems of asymmetric risk measures, +2. to address essential risks in banks and to understand their handling by supervisory regulations as well as +3. to realize the concept of risk as a capital requirement being the systematic base for these aspects in the ban- + +king sector.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Economics of Tax Planning,12-M-SP-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This course deals with tax effects on fundamental economic decisions. Taxes are integrated into standard mo- +dels for investment decisions, financing decisions, firm valuation, dividend policy and remuneration of employ- +ees. Therefore, the interaction of corporate and personal income taxes is analysed. +A reading list in English is available on request.","This course enables students to +(i) combine their knowledge of tax law with microeconomic analyses in the areas of corporate and personal fi- +nance; +(ii) analyze the effect of taxes on fundamental economic decisions, e.g. investment and financing decisions, eva- +luation of investment, financial assets, forms of remuneration for employees including managing and assessing; +(iii) read and discuss research and policy papers in the field of taxation.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one +candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Tax Accounting,12-M-STB-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This module introduces the various methods of income recognition in the German Income Tax Code (Einkommen- +steuergesetz, EStG). It discusses the main reporting and valuation provisions as well as the specific problems +and techniques of income calculation for partnerships.","Students have in-depth knowledge of tax accounting of companies and are able to solve moderate to complex +problems of tax accounting in particular of sole proprietorships and partnerships using legal source.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one +candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Incentives in Organizations,12-M-AO-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"Based on the classical principal-agent theory, this course discusses methodological and empirical aspects of in- +centives in organisations. It uses contents from advanced text books and original (mainly empirical) research ar- +ticles. + +Outline of syllabus + +1. Principal-agent theory + +2. Do top managers earn too much? (application) + +3. Performance-based payment + +4. Implementation of performance-based payment in companies (application) + +5. Seniority payment (with application) + +6. Financial incentives to work after retirement (with application) + +7. Efficiency wages (with case study) + +8. Team incentives (with case study)","Students acquire a working knowledge of key incentive models models, selected empirical applications and the +necessary econometric background. This enables them to identify the advantages and disadvantages of different +incentive systems that are applied in the enterprise context, to make informed management analyses and to cri- +tically evaluate current controversies and developments as well as to conduct their own research.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Human Resource Management and Industrial Relations,12-M-HRM-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"The lecture ""Human Resource Management and Industrial Relations"" introduces advanced theories, estimation +techniques and empirical results from the areas of human resources management and institutional frameworks +such as ithe different actors in ndustrial relations. + +Syllabus + +Introduction: Human Resource Management & Industrial Relationships + +Chapter 1: The employment contract [formal model] + +Chapter 2: Motivation [formal model] + +Chapter 3: Employee resistance against reorganisations [empirical study] + +Chapter 4: The role of works councils [formal model] + +Chapter 5: Works councils and the employer wage structure [empirical study] + +Chapter 6: The behaviour of labour unions [formal model] + +Chapter7: Learning process of employers [formal model and empirical study] + +Chapter8: Demographic challenges of HRM [formal model and empirical study]","The aim of the lectures is to enable students to understand and apply advanced theories, estimation techniques +and empirical results in the area human resource management and industrial relations on the basis of scientifc +literature.",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) Term paper (approx. 15 pages) +Language of assessment: German and/or English","There are no restrictions with regard to available places for students of the Master's degree programmes Mana- +gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo- +mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca- +ted to students of other subjects; should the number of applications exceed the number of available places, the- +se places will be allocated by lot.",--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation +and present the key insights from their work.","Educational aims + +• Enable students to position their research +• Enable students to critically review a substantial body of literature in short time +• Enable students to develop a sound theoretical framework +• Enable students to create a research paper fully meeting academic standards + +Learning outcomes + +On successful completion of this module students will be able to: + +• Differentiate their research from previous work +• Adopt theoretical perspectives to understand complex phenomena +• Engage in comprehensive academic reasoning +• Articulate abstract and complex phenomena and relationships in written and oral form",S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Corporate Strategy,12-M-UGF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This theory-led and application-oriented module provides you with critical knowledge and skills related to cor- +porate strategy—essential for anyone aspiring to take on leadership roles in their future career, may it be in the +private or public sector. The module goes beyond basic knowledge about strategic management provided by ba- +chelor-level modules. + +(1) Developing strategies in pursuit of competitive advantage + +(2) Corporate diversification + +(3) Vertical integration and outsourcing + +(4) Mergers & acquisitions + +(5) Dynamic strategies + +(6) Cooperative strategies + +(7) Corporate spin-offs and spin-outs + +(8) Internationalization strategies (I) + +(9) Internationalization strategies (II) + +(10) Strategic change + +(11) Corporate strategies and new technologies + +(12) Corporate governance and corporate social responsibility + +(13) Corporate communication and crisis management + +(14) Wrap-up and Q&A","Educational aims + +• Clarify the role of corporate strategy +• Explain theoretical concepts and mechanisms behind corporate strategy +• Enable students to critically appraise alternative approaches to corporate strategy +• Enable students to evaluate the boundaries and risks of corporate strategy + +Learning outcomes + +On successful completion of this module students will be able to: + +• Assess the role of corporate strategy for creating and sustaining competitive advantage +• Create and evaluate concepts related to corporate strategy +• Make judgements about the organizational and managerial implications of corporate strategy + +• Systematically choose between different routes of action","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of +one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, +groups of 3 approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Change Management,12-M-CHA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly +analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis- +cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa- +tion is a universal principle. The module covers projects like merging two departments, restarting a department +with team building, conducting an employee survey, or developing a new mission statement. The majority of the +projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive +emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in- +struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles +in these processes and are able to use their knowledge for own future projects as well as to create their own so- +lutions in change processes.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Accounting in the Company Management,12-M-CIU-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly +analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis- +cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa- +tion is a universal principle. The module covers projects like merging two departments, restarting a department +with team building, conducting an employee survey, or developing a new mission statement. The majority of the +projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive +emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in- +struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles +in these processes and are able to use their knowledge for own future projects as well as to create their own so- +lutions in change processes.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Strategic Managerial Accounting,12-M-INST-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on accounting instruments, which are applied in the context of strategic management of +enterprises. First, it addresses important drivers of strategic decisions from a microeconomic perspective, such +as the emergence of cost and quality advantages in competition as well as scale and experience curve effects. +Second, the module covers analytical and heuristic techniques of planning and control. In the context of these +techniques, instruments of target costing, life cycle cost analysis, benchmarking and business wargaming are +discussed with regard to their theoretical foundation and fields of application.","Initially, knowledge about fundamental requirements concerning instruments of decision-making and behavior +control within enterprises is acquired. What is more, the module conveys obtaining knowledge about the strengt- +hs and weaknesses and therewith fields of application and limits of prevalent instruments of strategic corporate +management used by practitioners.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +"Coordination, Budgeting and Incentives in Organizations",12-M-KOBO-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"This module focuses on accounting-based instruments to control behavior in decentralized enterprises. The +course first discusses the role of accounting in the context of decision-making and behavioral controlling as well +as informational analyses. Afterwards, the most common instruments of behavioral controlling (budgeting, va- +lue-oriented management, transfer prices) are discussed with regard to theory and practice.","This module aims to provide knowledge in the context of behavioral control in enterprises. Knowledge about re- +quirements on instruments used for behavioral control are discussed and competences for deployment, struc- +ture and development of coordination tools are provided.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Project Management and Control,12-M-PROM-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on the discussion and critical examination of instruments and methods used in the context +of project management and control within enterprises. Both classic and agile approaches to project manage- +ment are considered. It covers characteristic features and structures of projects, their possible success factors, +methods and instruments of control and management of projects in various project phases. The theoretical basis +as well as potential applications of these instruments are discussed.","Initially, knowledge about fundamental requirements concerning instruments of project management and con- +trol is acquired. What is more, the module conveys knowledge about strengths and weaknesses and therewith +fields of application and limits of commonly used instruments and methods of practitioners. Competences wi- +thin the configuration and development of the project management and control as well as skills within the practi- +cal use are obtained.",S (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Accounting and Capital Markets,12-M-REKA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on financial and management accounting, their functions, possible configurations as well +as their impact on internal and external recipients under consideration of the institutional setting. In this con- +text, an economic perspective has priority over detailed legal arrangements and regulations by the standard set- +ters. Based on the theoretical foundations of information economics as well as decision-making and balance +sheet theories, typical issues concerning cost and managerial accounting as well as financial accounting and pu- +blicity are discussed.","Initially, a fundamental knowledge about the conception and impact of management and financial accounting +as information systems is acquired. In the following, the module mainly sharpens the understanding of the eco- +nomic impacts of the configuration of management and financial accounting. What is more, extensive knowled- +ge about possible impacts of changes in institutional general frameworks is covered. For example, changes in +valuation standards, publicity rules or regulations about the distribution of profits in enterprises and on capital +markets are considered.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Analytics & Decision Making,12-M-MADM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Managerial Analytics & Decision Making"" discusses quantitative methods to structure and solve +a diverse set of management problems and demonstrates the application of modern methods with the help of +multiple case studies.","After completing this course students can +(i) better understand and structure problems; +(ii) apply important theoretical and empirical frameworks to practical problems that evaluate good and bad deci- +sion making; +(iii) implement advanced analytical methods to support decision making under risk.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Strategic Management of Global Supply Chains,12-M-SMGS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"Description: +In the course ""Strategic Management of Global Supply Chains"", students will become familiar with the basic +principles of building an efficient global supply chain and will apply what they have learned working on multiple +case studies.","After completing this course students +(i) can apply the basic methods and concepts of supply chain management to practical settings and evaluate the +results, and +(ii) understand the effects of global value chains onto strategic company decisions.","V (2) + Ü (2) +Module taught in: English","written examination (approx 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Strategic Decisions and Competition,12-M-SDC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"1. Strategic situations and decision making + +2. Analyzing strategic situations with game theory + +1. Noncooperative simultaneous move games +2. Nash equilibrium +3. Models of oligopoly markets + +3. Dynamic Games + +1. Two(-multi) stage games and subgame perfect equilibrium +2. Role of commitment in dynamic situations +3. Models of advertising +4. Wage bargaining and unions + +4. Repeated Games + +1. Emergence of coordination in long interactions +2. Collusion between competing firms +3. Time consistent monetary policy + +5. Static games of incomplete Information + +1. Bayesian Nash equilibrium +2. Auctions + +6. Dynamic games of incomplete information + +1. Moral hazard and nonlinear pricing +2. Perfect Bayesian equilibrium +3. Signalling games +4. Job-market signalling +5. Corporate investment and capital structure","After successful completion of this class, the students should be familiar with economic models that can be +used to shape managerial strategy and aid in making decisions in strategic situations. Especially, by making use +of simple two stage games, they should be able to formulate dynamic policies in a wide variety of strategic situa- +tions. The students will acquire an intuitive understanding of the underlying economic mechanisms which emer- +ge from the analysis of game theoretic models for a wide variety of strategic situations arising in industrial eco- +nomics, marketing, organization, finance, trade and labor. Moreover, they will acquire skills which enable them +to make predictions in strategic situations by making use of simple mathematical models. By means of comple- +ting case based exercises, they will learn to transform real life business situations to an appropriate economic +model. Based on an analysis of this model, they will be able to devise optimal strategies and derive the corre- +sponding managerial implications. + +The course will be taught in English.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Theory of Industrial Organization,12-M-TI1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Theory of industrial organisation: +1. Monopoly pricing + +• Nonlinear pricing and mechanism design +• Dynamic pricing: experience goods, durable goods + +2. Oligopoly pricing + +• Static price and quantity competition in homogeneous and differentiated goods markets +• Comparative statics +• Equilibrium market structure + +3. Dynamic competition in oligopoly markets + +• Subgame perfect equilibrium and models of dynamic competition +• Repeated games and collusion +4. Strategic behaviour by incumbent firms +• Entry deterrence and predation +• Signalling and reputation + +5. Behavioral Industrial Organization + +• Reference Dependent Preferences and Framing Effects +• Time inconsistent behavior + +The course will be taught in English.","Students which complete this class will acquire a working knowledge of advanced theoretical models of compe- +tition in oligopoly markets as well as sophisticated pricing techniques in monopoly markets. They will learn the +conditions under which the predictions of these models are valid. They will become familiar with applications of +advanced game theoretic tools, such as dynamic models of competition, for studying interactions between firms +in markets. By means of comprehensive exercises, they will apply the methods they learn in class to practical- +ly relevant problems. They will be in a position to read academic papers on related topics, assess the strengths +and weaknesses of an approach, summarize and comment on these papers and suggest possible extensions.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +European Competition Policy,12-M-WPE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Outline of syllabus: +1. Legal environment, competition laws +2. Market definition + +• Qualitative methods +• Simple quantitative methods +• Hypothetical monopoly test + +3. Horizontal agreements and collusion: repeated games and factors affecting likelihood of collusion +4. Horizontal mergers and collusion + +• Economic theory +• Efficiency effects +• Coordinated effects + +5. Vertical relations and contracts + +• Economic analysis of contracts +• ""More economic approach"" + +6. Abuse of dominant position + +• Classification of abusive conduct +• Economic analysis of abusive conduct and theory of harm + +The course will be taught in English.","After completion of the module students can use the advanced concepts introduced in the lecture of competiti- +on policy, including the legal framework, the trace models and methods for the study of competition policy issu- +es, as well as understand the approach of European competition policy in high profile cases. When they are con- +fronted with practical problems, they can refer to these cases, and the same logic to practical examples apply by +draining the relevant economic theories that identify variables to be measured and methodologies for assessing, +and based on that adequate conclusions for appropriate cases. They will sufficiently understand the subject in +order to open up that build upon literature in journals and being able to think critically.","V (2) +Module taught in: English","a) Written examination (approx. 60 to 120minutes) or +b) Term paper (15 to 20 pages) +Creditable for bonus +Language of assessment: English","There are no restrictions with regard to available places for students of the Master's degree programmes Mana- +gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo- +mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca- +ted to students of other subjects; should the number of applications exceed the number of available places, the- +se places will be allocated by lot.",--,150 h,--,-- +Econometrics 1,12-M-OE1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Econometrics,5,numerical grade,1 semester,graduate,"Description: +This module deals with the basic concept and methodology of the ordinary least squares (OLS) regression mo- +del. In particular, model assumptions and properties are discussed and formally motivated. In addition, the mo- +dule examines linear restrictions on the model's explanatory variables as well as dummy variables and introdu- +ces tests to verify simple and multiple linear restrictions. + +Linear algebra is used as formal aid. + +Outline of syllabus: +1. Random variables +2. Important distributions +3. Point estimates +4. Simple linear regression model +5. Model assumptions +6. Model properties +7. Simple hypothesis tests +8. Multiple linear regression model +9. Linear restrictions +10. Dummy variables +11. Multiple hypothesis tests","The students acquire knowledge of the basics, concepts and methods used in the classical linear regression mo- +del and understand the role of econometrics in science and data analysis. In particular, they learn how to analy- +tically derive, calculate and interpret the coefficients, standard errors and p-values of a classic regression output +of the multiple regression model. Furthermore, they are able to formally state and motivate the assumptions and +properties of OLS and know how to deal with transformed and dummy variables. Additionally, students will be +able to test multiple linear restrictions on the parameters and will be able to apply these tests to real economic, +business and social science questions. +The competences acquired in this course serve as a prerequisite for ""Econometrics II"", ""Econometrics III"", ""Micro- +econometrics"" und ""Financial Econometrics"".","V (2) + Ü (2) +Module taught in: German (winter semester), English (summer semester)","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Advanced Microeconomics,12-M-AM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Contract Theory and Information Eco-,5,numerical grade,1 semester,graduate,"In a nutshell, microeconomic theory considers the behavior of individual economic agents and builds from this +foundation to a theory of aggregate economic outcomes, which then can be applied for conducting welfare ana- +lysis and giving policy advice. This lecture addresses the core building block of this thought complex: individu- +al decision making and behavior. Specifically, students will come to understand in detail the standard models of +riskless consumer choice, choice under risk and intertemporal choice and learn about the empirical challenges +and limitations of these models. + +Throughout the lecture, we will work with precise mathematical formalizations of the ideas that we want to think +and talk about. In consequence, a solid understanding of the mathematical toolbox of standard microeconomics +(e.g., differential calculus and constrained optimization; basic set theory; integration by parts) will be helpful as +it will allow to focus on the underlying economic intuition. However, every required mathematical concept will be +introduced and explained along the way, such that a strong interest in formal economic analysis is more import- +ant than an advanced mathematical background. + +The exposition is primarily based on the standard graduate textbooks + +• Mas-Colell, Whinston and Green (1995): “Microeconomic Theory” +• Jehle and Reny (2001): “Advanced Microeconomic Theory”","After completing the course students will be able to + +• explain essential findings of microeconomic theory, +• apply the involved methods to given stylized examples on their own, +• recognize in which real life situations and how the results can be applied.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Management and Economics 1,12-M-APW1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical +methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or presentation (approx. 30 to 45 +minutes) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Management and Economics 2,12-M-APW2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical +methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or d) presentation (approx. 30 to 45 +minutes) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 1,12-M-AWI1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi- +ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration +(approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of +2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination +(approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 2,12-M-AWI2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi- +ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration +(approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of +2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination +(approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Digital Marketing I,12-M-DM1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Digitalization is rapidly changing our lives, including all types of business relationships. Therefore, new opportu- +nities and approaches have emerged in all areas of the marketing mix: Managers can choose from a wide variety +of new communication channels, such as social media networks, blogs, or messengers, and can engage in influ- +encer marketing and search engine optimization. They increasingly rely on online customer co-creation or crowd- +sourcing and create a wide variety of new digital products and services, often related to completely new busi- +ness models. Through price crawlers and price setting tools customers‘ price search behaviors have significant- +ly changed, requiring new price setting techniques. Artificial intelligence enables managers to automize and op- +timize many of these marketing processes, thus offering new opportunities and challenges for companies. Over- +all, digital marketing offers a tremendous variety of concepts and approaches to seize respective opportunities +and deal with related challenges, which will be largely highlighted and discussed in this course.","This course provides a broad overview about these new approaches of digital marketing. It explains the underly- +ing concepts of digital marketing and illustrates these approaches and concepts along numerous case studies. +After attending this course, students will have a broad as well as in-depth understanding of digital marketing +and its tools. Morever, they will understand of how to implement these tools successfully in business practice.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Digital Marketing II,12-M-DM2-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Students are required to put themselves in the following business situation: + +A large corporation has just recruited you and your team members as the new heads of the marketing depart- +ment in one of the firm’s divisions in order to manage its general and digital marketing activities. Specifically, +it is your task to manage the corporation’s digital product portfolio, segmentation and positioning as well as its +marketing mix strategy over a period of 10 years. + +Structure of the class: + +• Long-term business simulation game (details see below) that students will play in groups +• Lectures and discussion rounds on strategic approaches to succeed over a duration of 10 periods","Studierende lernen in diesem Kurs, zentrale Konzepte des Online- und Offline-Marketings gezielt und bezogen +auf die jeweilige Unternehmenssituation anzuwenden. Der Kurs bildet somit die Brücke zwischen Theorievermitt- +lung und entsprechende Anwendung in der Unternehmenspraxis.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +E-Commerce I,12-M-EC1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches +and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in- +dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat- +egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti- +ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre- +sentations where the students (in groups) will either apply selected lecture topics to real-world business cases +or present the core aspects of research articles dealing with e-commerce topics in general.","This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as- +sessing business strategies.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +E-Commerce II,12-M-EC2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches +and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in- +dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat- +egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti- +ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre- +sentations where the students (in groups) will either apply selected lecture topics to real-world business cases +or present the core aspects of research articles dealing with e-commerce topics in general.","This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as- +sessing business strategies.","V (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Real-Time Process Analytics,12-M-RTP-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The course teaches advanced approaches to process analytics. Students will learn to model and measure pro- +cesses and process execution based on past and present data.","After successfully completing the course, students should be able to +• Understand process modeling and process execution in an SOA +• OLAP analysis in a process warehouse +• Business Rules for BPM +• Complex Event Processing +• Event-driven BPM using CEP and Business Rules","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Data Science,12-M-TDS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"Data science is concerned with extracting knowledge and valuable insights from data assets. It is an emerging +field that is currently in high demand in both academia and industry. This course provides a practical introducti- +on to the full spectrum of data science techniques spanning data acquisition and processing, data visualization +and presentation, creation and evaluation of machine learning models. + +The course focuses on the practical aspects of data science, with emphasis on the implementation and use of +the above techniques. Students will complete programming homework assignments that emphasize practical +understanding of the methods described in the course.","Topics covered include: + +• Data acquisition and processing +• graph and network models +• text analysis +• working with geospatial data +• Usage of machine learning models (supervised and unsupervised)","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Information Systems 1,12-M-TIF1-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; +groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Information Systems 2,12-M-TIF2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; +groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Stochastic Models for Risk Analysis,12-RM-RA-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Point and interval estimation for the value at risk Point and interval estimation for the conditional value at risk +Prediction of value at risk in time series Risk of forecasts in time series, in particular exponential smoothing un- +der covariates Conditional heteroscedasticity: ARCH, GARCH, EGARCH, DVEC, BEKK, DCC Aggregated losses and +their empirical analysis Empirical analysis of statistical distributions Nonparametric bounds for the value at risk +and conditional value at risk Empirical estimation of nonparametric bounds for value at risk and conditional va- +lue at risk Market model: definition, derivation, parameters, empirical analysis Capital asset pricing model: de- +finition, parameters, empirical analysis Asset portfolios: definition, risk parameters Estimation of portfolio para- +meters: variance, value at risk, conditional value at risk, shortfall Optimum portfolios: concepts, theory, numeri- +cal analysis","The student is able to estimate risk measures and the parameters of risk models from data. In particular, the stu- +dent knows software packages and routines which enable empirical risk evaluation in a business context.",Ü (2) + V (2),Written examination (approx. 60 minutes),"30 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Stochastic Models for Risk Assessment,12-RM-RW-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Etymological background of the risk concept Definitions of risk Basic concepts and terminology of stochastic risk +modelling: risk phenomenon, risk object, risk variable, risk source, risk factor, risk cause, direct peril, indirect +peril, loss under risk, profit under risk, loss variable, profit variable, risk distribution, risk indicator, risk parame- +ter Classification of business risks Risk policy, risk management Risk analysis: risk identification, risk descrip- +tion, risk exploration, risk-relevant measurements, risk evaluation, risk assessment, risk modelling Risk mana- +gement: risk minimisation, risk protection, risk avoidance, risk mitigation, bearing of risk, risk prevention Risk +control, risk monitoring Norms and standards of risk management: ISO 31000, ONR 49000 -- 49004, IEC/ISO +31010, COSO II, AIRMIC, IRM, ALARM FMEA (Failure Mode and Effect Analysis) as a tool of risk analysis and risk +assessment: historical and thematic background, methodology, discussion of the FMEA assessment methodo- +logy Risk matrix, risk diagram Score diagram Stochastic risk parameters and risk measures as distribution para- +meters Probability distributions: Gaussian, Laplace, Student's t, extreme value, logistic, exponential, Weibull, +gamma, negative Gaussian, Burr, hyperbolic, generalised hyperbolic Elementary stochastic risk measures: va- +riance, standard deviation, signal-to-noise ratio, coefficient of variation, Sharpe ratio, nonconformance probabi- +lity, expected shortfall, shortfall probability, risk parameters under reference values, Stone family Value at Risk +and Conditional Value at Risk: definition, formal representations, values under special probability distributions +Axioms of risk measures: distribution invariance, subadditivity, superadditivity, additivity, comonotonous additi- +vity, nonnegative homogeneity, translation invariance, convexity, continuity, coherence","The student knows the schemes and concepts of risk analysis, risk assessment, risk measurement, and the +theoretical background. The student knows the concepts of advanced stochastic risk modeling. In a practical +business situation, the student is able to identify an appropriate scheme of risk assessment and corresponding +meaningful risk measures.",V (2) + Ü (2),Written examination (approx. 60 minutes),"30 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Communication in Business and Economics,12-M-BUC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"The lecture names introductory relevant communication models. Furthermore, the theoretical models of PR are +discussed. The added value of communication for companies, business, politics, and science is explained. The +discrepancy between journalism and PR is discussed, as well as the basic elements, instruments, goals, and +forms of PR. The preparation and implementation of press meetings, conferences, campaigns, and events will +be systematically explained, and the central aspects of corporate communications will be outlined. The exerci- +se deals with the practical implementation of journalistic styles in the various media and provides an overview of +the possibilities and concepts of PR work across different media and target groups.","After participating in the module courses, students are able to understand and apply PR and its forms, elements +as well as methods and in a holistic context. Students learn professional competencies in the field of (business) +communication with regard to reflection, argumentation, and exchange as a PR consultant in different areas. In +addition, students will be able to apply concrete PR instruments in practice and prepare them professionally.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 minutes) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +"Business Communication in Print, Online and Social Media",12-M-ECC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"This module focuses on the relationship of offer characteristics with benefit aspects for the end consumer and +the business models on the part of the providers. Starting from the basics of editorial work and professional text +management, the new forms of communication management in social networks are presented. The focus of the +lecture is on the use of social media in campaigns (Facebook, Twitter, Instagram, Tiktok). There will also be exer- +cises on various Web 2.0 applications (e.g. online social networks) and on the collection and interpretation of +online market research data. However, crisis communication of companies will also be covered in particular opi- +nion-makers on the web as well as protest culture on the web.","By participating in the module courses, students acquire job-specific skills in research and interviewing. Stu- +dents are able to collect and organize information according to criteria of topicality and relevance. In addition, +students are taught journalistic expertise so that they are able to recognize the forms of presentation of news, re- +ports, and background reports with their media characteristics and communicative functions in different media +genres and create them themselves. Students will be able to prototype and design a social media campaign, de- +scribe the editorial and technical approach including feedback, response, and customer engagement. In additi- +on, students will be able to design counter-strategies for corporate communication crises.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Practice Lectures,12-M-VGP-202-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"In this lecture, we invite board members of publicly listed companies, SMEs and Startups to discuss contempo- +rary challenges of corporate management. + +Students gain sustainable insights into current management practices, challenges of corporate management in +various industries, and discuss pressing managerial issues with C-level executives. In individual and group as- +signments, students are required to connect management theories with the managerial challenges of the spea- +kers. + +Managers of the different companies are required to address the following questions that will foster a detailed +discussion at the end of each lecture: + +- What are the current challenges facing your company? + +- Which strategies do you employ to respond to these challenges? + +- How have leadership concepts and approaches changed in your company?","After participating in this module, students should be able to combine theoretical approaches with current chal- +lenges in management. The students obtain a realistic insight into a cross-section of the German economy. +Through discussions reports and group presentations students’ social skills are trained in addition to professio- +nal skills.",S (2),"portfolio (approx. 15 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Advanced Topics in Data Science,12-M-ATDS-211-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"In this course, students work on advanced data science projects. The course covers the entire data science work- +flow from data collection to data preparation to modeling, evaluation and deployment. By following a top-down +teaching approach, students are enabled to apply complex machine learning models from the beginning.","As part of the course work, students will acquire knowledge and skills in the following areas: +1. Becoming familiar with the principles and frameworks in the research area of Data Science. +2. Apply machine learning and deep learning frameworks to structured and unstructured data +3. Design, implementation and evaluation of key algorithms within an end-to-end workflow in the field of Data + +Science + +4. Application of Jupyter notebooks and their infrastructure (collection, storage, retrieval, and analysis of data) +5. Understanding of a data-driven & analytical approach to decision problems","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or +b) term paper (approx. 15 pages) +Language of assessment: German and/or English +Assessment offered: Only when announced in the semester in which the courses are offered +creditable for bonus",--,--,150 h,--,-- +International Marketing Strategy,12-M-IMS-211-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The objective of this simulation course is to develop hands-on skills of how to make international marketing de- +cisions. Emphasis is put on the computer simulation game Country Manager which focuses on the managerial is- +sues arising when companies plan and execute market entry into new countries. This exercise allows students to +experience the challenges pertaining to corresponding decisions by playing the role of a responsible manager for +a major consumer products company. Students have to decide on the countries to enter, the mode of entry, the +segments to target, and every aspect of the marketing mix (price, promotion, place and product) and will get im- +mediate feedback on the consequences of their actions.","After completion of the course, participants should have gained a broad appreciation of critical decisions in in- +ternational marketing.",S (2),"a) written examination (40 to 60 minutes) or +b) term paper (15 to 20 pages) and presentation (approx. 20 minutes) (weighted 2:1) or +c) term paper (30 to 40 pages) or +d) portfolio (approx. 20 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Economist Practice Lectures,12-M-VWP-211-m01,Faculty of Business Management and Economics,"Holder of the Senior Professorship for Economics, Money",5,numerical grade,1 semester,graduate,"The content of the seminar is the active participation in as well as the follow-up of the lectures of economists +from different national and international fields of activity, which are organized for the event. + +The invitation of speakers from practice strengthens the practical orientation of the scientifically founded and at +the same time internationally oriented education at the faculty of economics of the University of Würzburg. + +In this way, students will gain lasting insights into the fields of activity of economists, gain an insight into prac- +tical activities, discuss these with high-ranking economists and combine them with theoretical economic know- +ledge gained during their studies.","By participating in the seminar, Master's students of the faculty of economics and business administration +should get to know the different fields of activity of economists and the questions that determine the daily work +of the speakers in the course of the lectures. + +In addition, the participants of the seminar will have the opportunity to apply the knowledge of economics they +have acquired during their studies. For this purpose, in addition to a discussion with the speakers following the +respective lecture, a debating workshop is offered to the participants of the seminar, in which the students are to +learn economic argumentation and debate management. The learned contents and competencies will be tested +at the end of the semester.",S (2),"a) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +b) term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1) or +c) written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Enterprise AI,12-M-EAI-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) term paper (approx. 15 pages) or +c) oral examination of one candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Information Systems and Artificial Intelligence 1,12-M-KI1-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) or +c) term paper (approx. 15 to 20 pages) +Language of assessment: German and/or English +Assessment offered: In the semester in which the course is offered +creditable for bonus",--,--,150 h,--,-- +Information Systems and Artificial Intelligence 2,12-M-KI2-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) or +c) term paper (approx. 15 to 20 pages) +Language of assessment: German and/or English +Assessment offered: In the semester in which the course is offered +creditable for bonus",--,--,150 h,--,-- +Vertical Storytelling,12-M-VS-221-m01,Faculty of Business Management and Economics,nan,10,numerical grade,1 semester,nan,--,--,S (2),"portfolio (approx. 5 pages) +Assessment offered: every year, summer semester",--,--,300 h,--,-- +Organizational Economics and Digital Transformation,12-M-OEDT-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Policy Evaluation Methods,12-M-PEM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Labor Economics,5,numerical grade,1 semester,graduate,"This course offers an introduction to the fundamentals of causal inference and to widely used research desi- +gns in the social sciences. In the first part a framework for understanding causality is introduced. Specifically, +the epistemological differences between association, intervention and counterfactuals are explained. Then it is +shown why experiments are paramount in generating causal knowledge and which assumptions are needed for +which level of the causal hierarchy. Finally, we will discuss two widely used approaches to causality in the social +sciences, i.e. potential outcomes and directed acyclic graphs. + +The second part is devoted to the research designs regressions analysis, difference-in-differences, instrumen- +tal variables, and regression discontinuity. The emphasis is how these research designs are for example applied +to answer important questions in labour economics such as the effects of a minimum wage increase on employ- +ment or the effect of children on female labour supply and wages. + +The assumptions each research design requires in order to identify a causal effect will be at center stage of the +lecture. Therefore the emphasis is to teach students what one needs to estimate in order to answer a given que- +stion. Further, the research designs are discussed such that students will be able to evaluate and apply these re- +search designs to other questions and fields.","At the end of the course, students should be able to understand basic concepts and methods of causal infe- +rence, as well as read, interpret, and assess the credibility of scientific publications. In addition, the course ser- +ves as preparation for advanced statistics and econometrics courses.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +creditable for bonus",--,Research track module in Master's programme IEP,150 h,--,-- +Topics in Empirical Economics,12-M-TE-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","portfolio (approx. 50 hours) +Prüfungssprache: Englisch +Creditable for bonus","12 *WA1(1) Should the number of applications exceed the number of available places, places will be allocated by +lot among all applicants irrespective of their subjects. +(2) Places on all courses of the module with a restricted number of places will be allocated in the same procedu- +re. +(3) A waiting list will be maintained and places re-allocated by lot as they become available.",--,150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important +basics as well as the most recent approaches to image representation, image processing and image analysis are +taught. Actual models and methods of machine learning as well as their technical backgrounds are presented +and their respective applications in image processing are shown.","Students have fundamental knowledge of problems and techniques in the field of computer vision and are able +to independently identify and apply suitable methods for concrete problems.","V (2) + Ü (2) +Module taught in: English","Written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in- +formation systems and social media in the World Wide Web, but also for various social, economic and biologi- +cal systems. What can we learn from data that capture the interaction topology of such complex systems? What +is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do +these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most +influential actors in a social network? And how can we analyze time series data on systems with dynamic net- +work topologies? +Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts +for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to +practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari- +ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles +of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha- +stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma- +terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, +which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen +their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final +written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri- +ven modelling of complex technical, social, and biological systems. Students will understand how we can quan- +titatively model the topology of networked systems and how we can detect and characterize topological pat- +terns. Participants will learn how to use analytical methods to make statements about the expected properties of +very large networks that are generated based on different stochastic models. They further gain an analytical un- +derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree +distributions influence the robustness of systems, and how emergent network features emerge from simple ran- +dom processes.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): + +IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process +model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning +methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, +SVM), learning methods for special data types, further learning paradigms.","The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da- +ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of +the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use +or implementation of data mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE,SEC",150 h,--,-- +Master Thesis Information Systems,12-WI-MA-192-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,30,numerical grade,1 semester,graduate,"Students will complete their degree with a Master's thesis in which they will be required to independently rese- +arch and write on a topic in the area of business management and economics, drawing on the subject-specific +knowledge they have acquired and adhering to the principles of good scientific practice. This thesis may either +take the form of an analysis and structured presentation of the existing literature on a certain topic or may, as is +often the case, also include a presentation of the students' own original achievements, e. g. new algorithms de- +veloped by students, surveys, the prototypical demonstration of a concept they developed or the application and +(further) development of a theoretical model.","In the master thesis students prove that they can plan and carry out a science-based work to solve a particular +problem within a specified period autonomously and to document the results in accordance with the professio- +nal scientific standards in writing. Students are able to understand relevant contributions to research and pro- +fessional practice, critically analyze and assess the relevance to their own specific questions. They can assess +and recognize major lines of development and dynamics of the subject and therefore also the need to retrain +continuously.",--,"Master's thesis (approx. 60 to 80 pages) +Language of assessment: German and/or English",--,Time to complete: 6 months,900 h,--,-- diff --git a/03_extracted_final_modules/MS_IS_all_modules.xlsx b/03_extracted_final_modules/MS_IS_all_modules.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..a00295f6bdf315d318a01a0d3638c95a4a3ef45d Binary files /dev/null and b/03_extracted_final_modules/MS_IS_all_modules.xlsx differ diff --git a/03_extracted_final_modules/MS_IS_all_modules_cleaned.xlsx b/03_extracted_final_modules/MS_IS_all_modules_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..7db4e5687af724304634d37efc3d15acdcef8e9e Binary files /dev/null and b/03_extracted_final_modules/MS_IS_all_modules_cleaned.xlsx differ diff --git a/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.csv b/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.csv new file mode 100644 index 0000000000000000000000000000000000000000..e2435730cbbfa2c11e3552758e7d7d9ee6b28e4c --- /dev/null +++ b/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.csv @@ -0,0 +1,16 @@ +Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I +Information Processing within Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of the structure and the application areas of business management information systems in enterprises and public institutions.Outline of syllabus:1. What is software: concepts, categories, application2. Software life cycle: duration, phases, steps3. As-is analysis: tasks, problems4. To-be concept: system design, data design, dialog design, function design5. Object orientation: paradigm shift6. Change management: meaning, methodologies, project management7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to(i) understand the importance of integration in enterprises, especially in information systems;(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require-ments, which brings a software implementation with;(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply (with participation in the exercise);(iv) understand the importance of change management and project management and know the appropriate me-thods for specific applications.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage-ment.Outline of syllabus:1. Organisation and distinction2. IT strategy3. IT organisation4. Management of IT systems5. Enterprise Architecture Management6. IT project management7. IT security8. IT law9. IT controllingReading:• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden.• Tiemeyer: Handbuch IT-Management, Munich.• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to1. overview the different aspects to be considered regarding a purposeful IT management;2. understand and apply appropriate methods and tools;3. independently perform system search and selection in a team project (only after participation in the practice lessons).",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content:In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analy-sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen-dently and will only receive advice and minor support from research assistants.Reading:will vary according to topic","After completing the course ""Projektseminar"", students will be able to1. analyze business tasks and requirements and generate fitting IS solutions;2. apply project management methods;3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1Language of assessment: German, EnglishCreditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua-ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me-thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).",The students possess theoretical and practical knowledge in the area of information retrieval and have acquired the technical know-how to create a search engine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo-dern computer systems, as well as the measures implemented to protect against these attacks. In the course, the following topics are discussed:• x86-64 instruction set architecture and assembly language• Runtime attacks (code injection, code reuse, defenses)• Web security• Blockchains and smart contracts• Side-channel attacks• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con-cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci-ses allow students to gain hands-on experience with attacks and analysis of systems from an attackers perspec-tive.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, LR, HCI, ES.Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,The students possess a fundamental and applicable knowledge about advanced topics in software engineering with a focus on modern software architectures and fundamental approaches to model-driven software enginee-ring.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia-bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of measured data, planning and evaluation of simulation experiments, special random processes, possibilities and limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of (technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu-lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro-grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co-de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis-cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par-allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces-sing.",V (2) + Ü (2)Module taught in: English,written examination (90 to 120 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de-tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili-stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing mostly for English. They are able to solve problems through the methods taught. They have gained experience in the application of text mining algorithms.",The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing. They are able to solve practical problems with the methods acquired in class. They have gained experience in the application of text mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important basics as well as the most recent approaches to image representation, image processing and image analysis are taught. Actual models and methods of machine learning as well as their technical backgrounds are presented and their respective applications in image processing are shown.",Students have fundamental knowledge of problems and techniques in the field of computer vision and are able to independently identify and apply suitable methods for concrete problems.,V (2) + Ü (2)Module taught in: English,"Written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- diff --git a/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx b/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..2ff8fc7f77bae9d402716a2f65c5695fc6c69f27 Binary files /dev/null and b/03_extracted_final_modules/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx differ diff --git a/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.csv b/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.csv new file mode 100644 index 0000000000000000000000000000000000000000..367d9840612cbaec55eea23a48b558e98a55b08c --- /dev/null +++ b/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.csv @@ -0,0 +1,121 @@ +Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I +Information Processing within Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of the structure and the application areas of business management information systems in enterprises and public institutions.Outline of syllabus:1. What is software: concepts, categories, application2. Software life cycle: duration, phases, steps3. As-is analysis: tasks, problems4. To-be concept: system design, data design, dialog design, function design5. Object orientation: paradigm shift6. Change management: meaning, methodologies, project management7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to(i) understand the importance of integration in enterprises, especially in information systems;(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require-ments, which brings a software implementation with;(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply (with participation in the exercise);(iv) understand the importance of change management and project management and know the appropriate me-thods for specific applications.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage-ment.Outline of syllabus:1. Organisation and distinction2. IT strategy3. IT organisation4. Management of IT systems5. Enterprise Architecture Management6. IT project management7. IT security8. IT law9. IT controllingReading:• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden.• Tiemeyer: Handbuch IT-Management, Munich.• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to1. overview the different aspects to be considered regarding a purposeful IT management;2. understand and apply appropriate methods and tools;3. independently perform system search and selection in a team project (only after participation in the practice lessons).",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content:In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analy-sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen-dently and will only receive advice and minor support from research assistants.Reading:will vary according to topic","After completing the course ""Projektseminar"", students will be able to1. analyze business tasks and requirements and generate fitting IS solutions;2. apply project management methods;3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1Language of assessment: German, EnglishCreditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua-ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me-thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).",The students possess theoretical and practical knowledge in the area of information retrieval and have acquired the technical know-how to create a search engine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo-dern computer systems, as well as the measures implemented to protect against these attacks. In the course, the following topics are discussed:• x86-64 instruction set architecture and assembly language• Runtime attacks (code injection, code reuse, defenses)• Web security• Blockchains and smart contracts• Side-channel attacks• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con-cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci-ses allow students to gain hands-on experience with attacks and analysis of systems from an attackers perspec-tive.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, LR, HCI, ES.Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,The students possess a fundamental and applicable knowledge about advanced topics in software engineering with a focus on modern software architectures and fundamental approaches to model-driven software enginee-ring.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia-bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of measured data, planning and evaluation of simulation experiments, special random processes, possibilities and limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of (technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu-lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro-grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co-de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis-cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par-allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces-sing.",V (2) + Ü (2)Module taught in: English,written examination (90 to 120 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de-tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili-stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing mostly for English. They are able to solve problems through the methods taught. They have gained experience in the application of text mining algorithms.",The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing. They are able to solve practical problems with the methods acquired in class. They have gained experience in the application of text mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important basics as well as the most recent approaches to image representation, image processing and image analysis are taught. Actual models and methods of machine learning as well as their technical backgrounds are presented and their respective applications in image processing are shown.",Students have fundamental knowledge of problems and techniques in the field of computer vision and are able to independently identify and apply suitable methods for concrete problems.,V (2) + Ü (2)Module taught in: English,"Written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: German and/or English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in-formation systems and social media in the World Wide Web, but also for various social, economic and biologi-cal systems. What can we learn from data that capture the interaction topology of such complex systems? What is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most influential actors in a social network? And how can we analyze time series data on systems with dynamic net-work topologies?Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari-ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha-stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma-terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri-ven modelling of complex technical, social, and biological systems. Students will understand how we can quan-titatively model the topology of networked systems and how we can detect and characterize topological pat-terns. Participants will learn how to use analytical methods to make statements about the expected properties of very large networks that are generated based on different stochastic models. They further gain an analytical un-derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree distributions influence the robustness of systems, and how emergent network features emerge from simple ran-dom processes.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: German and/or English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, SVM), learning methods for special data types, further learning paradigms.",The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da-ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use or implementation of data mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE,SEC",150 h,--,-- +Business Software 1: IS-based Enterprise Management,12-GPU-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This module provides students with an overview of the structure of a business information system (SAP Business ByDesign) in depth.Outline of syllabus:1. Integrated information systems: integration, standard software, system architecture2. Working with standard business software3. Consulting in integrated information systems: project management, project organisation, presentation skillsDescription:The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the software, dealing with a wide variety of business processes.If you would like to register for this course, please submit an application to the consultants (cover letter, CV, cer-tificates; please also specify your degree programme and student ID number).","After completing the course ""Business Software 1"", students will be able to(i) understand an ERP system in its depth;(ii) understand the interaction of business processes;(iii) execute business tasks and processes in an ERP system independently (after participation in the practice lessons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orc) Term paper (15 to 20 pages) orCreditable for bonusLanguage of assessment: German and/or EnglishAssessment offered: Once a year, winter semester","20 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Software 2: Enterprise Resource Planning Systems,12-M-ERP-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This module provides students with an overview of the structure of business information systems in width as well as the selection and implementation of business information systems in organisations.Outline of syllabus:1. Integrated information systems: integration, standard software, system architectures, operating models2. Selection of integrated information systems: methods, cost-benefit analysis3. Implementation of integrated information systems: project management, project organisation, project marke-tingThe lecture will be accompanied by an exercise that will present students with an opportunity to access, in small groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the software, dealing with a wide variety of business processes.","After completing the course ""Business Software 2"", students will be able to1. differentiate between system architectures and -philosophies;2. understand the interaction of business processes;3. come to a selection decision for an ERP system using a structured approach and compare different ERP sy-stems;4. execute business tasks and processes in an ERP system independently (after participation in the practice les-sons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orc) Term paper (15 to 20 pages) orCreditable for bonusLanguage of assessment: German and/or EnglishAssessment offered: Once a year, summer semester","20 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Advanced Seminar: Enterprise Systems,12-M-ES-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the fields of informati-on systems and enterprise systems.Reading:will vary according to topic","After completing the course ""Enterprise Systems"", students will be able to1. understand the fundamentals of scientific literature reviews;2. integrate elaborated content in a scientific thesis;3. create presentations independently.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Decision Support Systems,12-M-DSS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,The course discusses advanced approaches for modelling and solving decision problems in business settings. The acquired insights are used to design and implement decision support systems using standard software tools (Python).,"After successfully completing the course, students should be able to• Understand the structure of classic business decision problems• Isolate key elements from general problem descriptions and convert them to quantitative decision models• Solve different classes of optimization problems (linear, network, integer, multi-objective, non-linear, stochastic)• Implement decision support systems",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)Creditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Analytical Information Systems,12-BI-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course provides an overview of the structure and applications of analytical information systems. A special fo-cus is on individual quantitative methods of data analysis. On the one hand, methods from the areas of data pre-paration and data manipulation as well as their practical application are introduced. On the other hand, an intro-duction to methods and the application of machine learning methods for predictive analytics, in particular neural networks and deep learning, is given.",The module provides students with knowledge of:• Data Manipulation• Data Engineering• Descriptive Analytics• Predictive Analytics and Data Mining• Supervised Learning• Unsupervised Learning• Neural Networks and Deep Learning• Text Mining• Big Data Technologies,V (2) + Ü (2),Written examination (approx. 60 Minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.WM1:Should the number of applications exceed the number of available places, places will be allocated as follows:1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Analytics,12-M-BUA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the field of business management decision models and methods and their application in the development of decision-support sy-stems as well as analytical information systems and quantitative methods of data analysis.Students work on current topics using methods from machine learning, mathematical optimization and simulati-on.",The module provides students with knowledge of:• Scientific literature• Implementation of methods in code• Integration of developed results in scientific papers• Creating presentations and lectures,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +E-Business Strategies,12-M-IBS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of strategic implications of digital technologies at the level of organisations, industries and value networks. To this end, concepts and frameworks from strategic technology management are applied to digital innovations and illustrated with numerous examples. In the accompanying exercise, case stu-dies of well-known digital companies and their business models are analysed and discussed.",- Understand theoretical concepts of strategy development and implementation in the context of digital techno-logies.- Apply different frames of reference and understand their strengths and weaknesses in the context of practical application.- Transfer the concepts to real business situations,V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orCreditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Mobile and Ubiquitous Systems,12-M-MUS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of technologies and business applications of mobile & ubiquitous computing. Concepts and applications are illustrated using numerous examples from mobile telecommunications to the In-ternet of Things. In the accompanying exercise, corresponding case study texts are analysed and discussed.","- Understand the technological basics of mobile & ubiquitous computing.- Analysing business applications in processes, products/services and business models- Apply the concepts learned to real-life problems in a business context",Ü (2) + V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Seminar: E-Business Strategies,12-M-SEBS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the fields of web-ba-sed platforms (electronic markets, Web 2.0 etc.) and strategic management of a company.",- Academic literature review- Integration of developed results in scientific papers- Creating presentations and talks,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Corporate Entrepreneurship,12-M-UGF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,This module is a theory-led and practice-oriented primer on corporate entrepreneurship. It provides you with knowledge useful for anyone aiming at working (or researching) in the field of corporate innovation and entrepre-neurship or at pursuing an ‘intrapreneurial’ or entrepreneurial career.(1) Introduction to corporate entrepreneurship(2) Antecedents and forms of corporate entrepreneurship(3) Corporate strategy and corporate entrepreneurship(4) Organizational structure and corporate entrepreneurship(5) Human resource management and corporate entrepreneurship(6) Building supportive organizational cultures(7) Entrepreneurial control systems(8) Entrepreneurial leadership(9) The corporate entrepreneur as a champion and diplomat(10) The pay-off from corporate entrepreneurship(11) Corporate venture capital(12) Corporate entrepreneurship in nonprofit and government organizations(13) Universities and academic spin-offs(14) Wrap-up and Q&A,Educational aims• Clarify the role of corporate entrepreneurship• Explain theoretical concepts and mechanisms behind corporate entrepreneurship• Enable students to critically appraise alternative approaches to corporate entrepreneurship• Enable students to evaluate the boundaries and risks of corporate entrepreneurshipLearning outcomesOn successful completion of this module students will be able to:• Create and evaluate concepts related to corporate entrepreneurship• Assess the role of corporate entrepreneurship for creating and sustaining competitive advantage• Make judgements about the organizational and managerial implications of corporate entrepreneurship• Systematically choose between different routes of action,V (2) + Ü (2)Module taught in: English,"a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, groups of 3 approx. 30 minutes)Language of assessment: English",--,--,150 h,--,-- +Digital Entrepreneurship,12-M-UGF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,This module provides an introduction into digital entrepreneurship and digital transformation. (1) Introduction (2) Digital business models (3) Identifying and exploiting opportunities for digital entrepreneurship (4) Strategies for creating competitive advantage in digital entrepreneurship (5) Digital marketing for entrepreneurs (6) Crowd-funding for entrepreneurs (7) Design thinking (8) Lean startup (9) Platform ecosystems and online communities (10) Digital strategy and digital transformation (11) The agile organization (12) Crowdsourcing (13) Cyberfraud (14) Wrap-up and Q&A,"Educational aims: Clarify the role of digital entrepreneurship and digital transformation. Explain theoretical con-cepts and mechanisms behind digital entrepreneurship and digital transformation. Enable students to critically appraise alternative approaches to digital entrepreneurship and digital transformation. Enable students to eva-luate the boundaries and risks of digital entrepreneurship and digital transformationLearning outcomes: On successful completion of this module students will be able to (1) Assess the role of di-gital entrepreneurship and digital transformation for creating and sustaining competitive advantage, (2) Crea-te and evaluate concepts related to digital entrepreneurship and digital transformation, (3) Make judgements about the organizational and managerial implications of digital entrepreneurship and digital transformation, (4) Systematically choose between different routes of action.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) log (15 to 20 pages) or c) oral examination (one candida-te each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: English,--,--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation and present the key insights from their work.",Educational aims• Enable students to position their research• Enable students to critically review a substantial body of literature in short time• Enable students to develop a sound theoretical framework• Enable students to create a research paper fully meeting academic standardsLearning outcomesOn successful completion of this module students will be able to:• Differentiate their research from previous work• Adopt theoretical perspectives to understand complex phenomena• Engage in comprehensive academic reasoning• Articulate abstract and complex phenomena and relationships in written and oral form,S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Global Logistics & Supply Chain Management,12-M-GLSC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Global Logistics & Supply Chain Management"" acquaints students with advanced methods for the planning of global production networks and demonstrates the application of these with the help of multiple case studies.",After completing this course students can(i) analyze and evaluate global production networks;(ii) develop and apply appropriate methods to plan production networks;(iii) evaluate the consequences of uncertainties in processes and apply concepts and methods to plan uncertain processes.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Advanced Operations & Logistics Management,12-M-AOLM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Advanced Operations & Logistics Management"" acquaints students with advanced methods for the planning of integrated production and logistics systems and demonstrates the application of these with the help of multiple case studies","After completing this course students can(i) analyze and evaluate integrated production and logistics systems;(ii) develop and apply appropriate methods to plan complex production and logistics systems;(iii) evaluate the consequences of uncertainties in processes, and(iv) apply concepts and methods to plan uncertainties processes.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Seminar: Operations Management,12-M-SN-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"With the help of topics from the area of ""Operations Management"", this course will provide students with know-ledge and skills that will enable them to prepare a well-structured term paper and to present the key results of their work.",Students will learn how to convince a critical audience by giving a presenation regarding a topic from the area of Operations Management. By developing and giving a presentation as well as by answering questions the stu-dents will practice their skills to deal with difficult communication situations and to argument for and against a certain topic.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English",--,--,300 h,--,-- +Adaption and Continuous System Engineering,12-ACSE-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Business Suite: The constantly changing environment with its organisational and IT-oriented developments forces companies to adapt their standard business software solutions. With the help of dynamic adaptation (Continuous System Engineering), this process of change can be supported effectively and efficiently. This mo-dule discusses both the systematic implementation of adaptation steps (so-called customising) using the exam-ple of the mySAP Business Suite and the concept of Continuous System Engineering using various practical ex-amples. Business Apps: The course combines theory and practice in the area of cloud computing and ERP. Par-ticipants gain an insight into the architecture of the ByDesign platform and are presented with an opportunity to gain practical experience working with the corresponding software development kit.Content:• Fundamentals of cloud computing• Cloud business solutions• Architecture of the SAP Business ByDesign platform• Platform adaption and extensibility• Basics of software development in SAP Cloud Applications Studio• Hands-on SDK: independently designing and developing a demo app","Business Suite: Students learn about the various ways of adapting a standard business software solution to the special requirements of a company. They also develop a fundamental understanding of the dynamic adaptation of business software libraries. Based on selected examples from the SAP Business Suite that the acquired know-ledge will be deepened by using case studies. Business Apps: The course imparts knowledge and delivers skills in cloud computing for businesses, ERP systems architecture and software development at the example of the SAP Business ByDesign platform. The independent planning, implementation and documentation of a business app trains important core competencies of technology-oriented Business Informatics.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) oral examination (one can-didate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Business Service Platforms 2,12-AGP2-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The next generation of business service platforms leads to a transformation of traditional industrial enterprises into service businesses that generate a large proportion of value in developed economies. New ICT technologies such as cloud computing, the Internet of Things and semantic technologies will contribute to the success of the-se businesses in a similar way as ERP contributed to the success of industrial enterprises. But we are still at the beginning of the evolution of business service platforms, which will have to become more adaptable to support special business models and allow differentiating customer service processes.The course will discuss different case studies on services businesses. The digital transformation of the software industry into a service industry is the most prominent of these case.","Be aware of the growing economic importance of the service sector. Understand that services businesses in are facing a special productivity problem, which could not be adressed by the same processes applied in the ma-nufacturing industries. Understand the new ICT technologies we have at hand today to deliver smart solutions for this problem. Be aware of the diversity of services business today where we have no evidence that a general standard can be found applicable to most subsectors similar to the standardization achieved for the manufactu-ring industries after twenty years of research.",V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,--_x000C_ +Business Service Platforms 1,12-BSA-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"A next generation of enterprise systems called business service platforms is emerging using new disruptive tech-nologies such as cloud computing, big data and mobility. These business service platforms apply the concept of product platforms to software. They will1. be services based2. be offered as a service in the cloud3. address new classes of users and types of business especially in the service business4. allow for a high degree of business adaptability and extensibility.5. be supplemented by a broad offer of partner add-ons supporting accelerated innovation.These new business service platforms will play a key role in the digital transformation of the software industry.",Be aware of the big business productivity progress enabled by BIS in the last 50 years. Understand the limitati-ons of these systems in spite of the digital transformation of the software industry ahead. Be able to critically as-sess the business potential of new IC technologies. Understand the business demand for change. Understand the necessary organizational learning needed to leverage new technology for business change management.,V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +"Business Processes Organisation, Business Software and Process Industries",12-GLP-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"ERP systems have become key elements of successful companies. Business processes in companies can no lon-ger be managed without using such ERP systems. In financial departments of companies, such systems have be-en used for a long time, but business processes e. g. for logistical tasks have so far not been supported by ERP solutions. This module explains how this issue could be resolved as well as what constraints and what depen-dencies have to be considered.","After completing this module, students should be able to(i) know about actual business processes in companies;(ii) understand selected problems in the organization and design of logistical business processes and work out solutions;(iii) know and design basic data structures and data flows of an ERP system;(iv) map businesss processes within an ERP system;(v) consider the specifics of a certain industry (e. g. the process industry) when organizing business processes;(vi) map the core business processes within an ERP system.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Work and Information,12-ITA-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This module discusses relevant principles, concepts and applications of business information processing and its impact on organisational and process structures in todays business world.","The expertise gained from other modules related to business management issues can be interpreted and clas-sified in a certain way by participating in this module. For decisions in regards to human resources planning, in-vestment, and a companys strategy, the students will get to know all the relevant concepts and interdependen-cies, which come with taking information processing into account as the so called ""fourth"" factor of production.",V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Work Order Planning for Automated Manufacturing,12-M-AGAF-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The idea of integration of business information systems is primarily practiced and developed as an ERP system in terms of business application areas, their temporal overlap (data warehouse), their spatial relationship (sup-ply network) and connection of legal tasks (eGovernment). However, linking the commercial view of incoming cu-stomer orders with the logistic or more technical view of the scheduling of production orders and the resulting consequences for the processes is a critical success factor.",Linking research and lectures of the Institute of Robotics and Telematics as well as the orientation of the Chair of Business Integration allows students a conceptual as well as practical insight into the challenges of this in the future essential part of the operational automation development.,V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Topics in Business Information Systems 1,12-M-ATW1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Topics in Business Information Systems 2,12-M-ATW2-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Information systems research,12-M-ISR-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The course provides an overview of theoretical scientific foundations, theories, research topics and methods of international research in business informatics.","The module provides students with knowledge of:(i) Exploration of classical themes of WI / IS research;(ii) Getting to know the relevant paradigms, theories and methods;(iii) Recognition of the interfaces to other areas of business administration and management practice;(iv) Gain experience in finding and evaluation of scientific literature",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 15 to 20 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)Creditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Databases 2,10-I=DB2-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Data warehouses and data mining; web databases; introduction to Datalog.,"The students have advanced knowledge about relational databases, XML and data mining.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, HCI.",150 h,--,-- +Compiler Construction,10-I=CB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Lexical analysis, syntactic analysis, semantics, compiler generators, code generators, code optimisation.","The students possess knowledge in the formal description of programming languages and their compilation. They are able to perform transformations between them with the help of finite automata, push-down automata and compiler generators.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,GE",150 h,--,-- +Artificial Intelligence 2,10-I=KI2-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Planning, probabilistic closure and Bayesian networks, utility theory and decidability problems, learning from observations, knowledge while learning, neural networks and statistical learning methods, reinforcement lear-ning, processing of natural language.","The students possess theoretical and practical knowledge about artificial intelligence in the area of probabilistic closure, learning and language processing and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI,GE",150 h,--,-- +E-Learning,10-I=EL-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Learning paradigms, learning system types, author systems, learning platforms, standards for learning systems, intelligent tutoring systems, student models, didactics, problem-oriented learning and case-based training sy-stems, adaptive tutoring systems, computer-supported cooperative learning, evaluation of learning systems.",The students possess a theoretical and practical knowledge about eLearning and are able to assess possible ap-plications.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,HCI,GE",150 h,--,-- +Professional Project Management,10-I=PM-182-m01,Institute of Computer Science,holder of the Chair of Computer Science III,5,numerical grade,1 semester,graduate,"Project goals, project assignment, project success criteria, business plan, environment analysis and stakeholder management, initialisation, definition, planning, execution/control, finishing of projects, reporting, project com-munication and marketing, project organisation, team building and development, opportunity and risk manage-ment; conflict and crisis management, change and claim management; contract and procurement management, quality management, work techniques, methods and tools; leadership and social skills in project management, program management, multiproject management, project portfolio management, PMOs; peculiarities of software projects; agile project management/SCRUM, combination of classic and agile methods.","The students possess practically relevant knowledge about the topics of production management and/or pro-fessional project management. They are familiar with the critical success criteria and are able to initiate, define, plan, control and review projects.",V (4),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +Algorithms for Geographic Information Systems,10-I=AGIS-161-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Algorithmic foundations of geographic information systems and their application in selected problems of acqui-sition, processing, analysis and presentation of spatial information. Processes of discrete and continuous opti-misation. Applications such as the creation of digital height models, working with GPS trajectories, tasks of spa-tial planning as well as cartographic generalisation.",The students are able to formalise algorithmic problems in the field of geographic information systems as well as to select and improve suitable approaches to solving these problems.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,IS,HCI",150 h,--,-- +Real-Time Interactive Systems,10-HCI=RIS-182-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"This course provides an introduction into the requirements, concepts, and engineering art of highly interactive human-computer systems. Such systems are typically found in perceptual computing, Virtual, Augmented, Mixed Reality, computer games, and cyber-physical systems. Lately, these systems are often termed Real-Time Interac-tive Systems (RIS) due to their common aspects.The course covers theoretical models derived from the requirements of the application area as well as common hands-on and novel solutions necessary to tackle and fulfill these requirements. The first part of the course will concentrate on the conceptual principles characterizing real-time interactive systems. Questions answered are: What are the main requirements? How do we handle multiple modalities? How do we define the timeliness of RIS? Why is it important? What do we have to do to assure timeliness? The second part will introduce a concep-tual model of the mission-critical aspects of time, latencies, processes, and events necessary to describe a sy-stems behavior. The third part introduces the application state, its requirements of distribution and coherence, and the consequences these requirements have on decoupling and software quality aspects in general. The last part introduces some potential solutions to data redundancy, distribution, synchronization, and interoperability.Along the way, typical and prominent state-of-the-art approaches to reoccurring engineering tasks are discussed. This includes pipeline systems, scene graphs, application graphs (aka field routing), event systems, entity and component models, and others. Novel concepts like actor models and ontologies will be covered as alternative solutions. The theoretical and conceptual discussions will be put into a practical context of todays commercial and research systems, e.g., X3D, instant reality, Unity3d, Unreal Engine 4, and Simulator X.","After the course, the students will have a solid understanding of the boundary conditions defined by both, the physiological and psychological characteristics of the human users as well as by the architectures and technolo-gical characteristics of todays computer systems. Participants will gain a solid understanding about what they can expect from todays technological solutions. They will be able to choose the appropriate approach and tools to solve a given engineering task in this application area and they will have a well-founded basis enabling them to develop alternative approaches for future real-time interactive systems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): HCI.Cf. Section 3 Subsection 3 Sentence 8 FSB (subject-specific provisions).",150 h,--,-- +Logic Programming,10-I=LP-172-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Logic-relational programming paradigm, top-down evaluation with SLD(NF) resolution. Introduction to the logic programming language Prolog: recursion, predicate-oriented programming, backtracking, cut, side effects, ag-gregations. Connection to (deductive) databases. Comparison with Datalog, short introduction of advanced con-cepts like constraint logic programming.","The students have fundamental and practicable knowledge of logic programming. They are able to implement compact and declarative programs in Prolog, and to compare this approach to the traditional imperative pro-gramming paradigm.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, SE, IT, IS.",150 h,--,-- +Machine Learning for Natural Language Processing,10-I=NLP-182-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture conveys advanced knowledge about methods in computational text processing. To this end, it pres-ents state of the art models and techniques in the area of machine learning, as well as their technical back-ground, and their respective applications in Natural Language Processing. As one important building block of almost all modern NLP-models, different techniques for learning representations of words, so called Word Em-beddings, are presented. Starting from this we cover, among others, models from the area of Deep Learning, li-ke CNNs, RNNs and Sequence-to-Sequence architectures. The theoretical foundations of these models, like their training with Backpropagation, are also covered in depth. For all models presented in the lecture, we show their application to problems like sentiment analysis, text generation and machine translation in practice.",The participants have solid knowledge on problems and methods in the area of computational text processing and are able to identify and apply suitable methods for a specific task.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IS, HCI.",150 h,--,-- +Medical Informatics,10-I=MI-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Electronic patient folder, coding of medical data, hospital information systems, operation of computers in infir-mary and functional units, medical decision making and assistance systems, statistics and data mining in medi-cal research, case-based training systems in medical training.",The students possess theoretical and practical knowledge about the application of computer science methods in medicine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,HCI,GE",150 h,--,-- +Performance Engineering & Benchmarking of Computer Systems,10-I=PEB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Introduction to performance engineering of commercial software systems, performance measurement techni-ques, benchmarking of commercial software systems, modelling for performance prediction, case studies.","The students possess a fundamental and applicable knowledge in the areas of performance metrics, measure-ment techniques, multi-factorial variance analysis, data analysis with R, benchmark approaches, modelling with queue networks, modelling methods, resource demand approximation, petri nets.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Programming with neural nets,10-I=PNN-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IT, IS, HCI, GE.",150 h,--,-- +Robotics 1,10-I=RO1-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VII,8,numerical grade,1 semester,graduate,"History, applications and properties of robots, direct kinematics of manipulators: coordinate systems, rotations, homogenous coordinates, axis coordinates, arm equation. Inverse kinematics: solution properties, end effec-tor configuration, numerical and analytical approaches, examples of different robots for analytical approaches. Workspace analysis and trajectory planning, dynamics of manipulators: Lagrange-Euler model, direct and inver-se dynamics. Mobile robots: direct and inverse kinematics, propulsion system, tricycle, Ackermann steering, ho-lonomes and non-holonome restrictions, kinematic classification of mobile robots, posture kinematic model. Movement control and path planning: roadmap methods, cell decomposition methods, potential field methods. Sensors: position sensors, speed sensors, distance sensors.","The students master the fundamentals of robot manipulators and vehicles and are, in particular, familiar with their kinematics and dynamics as well as the planning of paths and task execution.",V (4) + Ü (2)Module taught in: English,written examination (approx. 60 to 90 minutes)Separate written examination for Masters students.Language of assessment: Englishcreditable for bonus,--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IS, ES, LR, HCI, GE.",240 h,--,-- +Project - Current Topics in Computer Science,10-I=PRJAK-162-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Completion of a project task (in Teams).,The project allows participants to work on a problem in computer science in teams.,P (4),"project report (10 to 15 pages) and presentation of project (15 to 30 minutes)Each project is offered one time only. The project will not be repeated; there will not be another project with the same topic. Assessment can, therefore, only be offered for the project offered in the respective semester.Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +International Marketing,12-M-IMM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:The module builds on the knowledge acquired during the Bachelors degree programme or the Grundstudium(stage I studies). It provides a systematic introduction to strategic marketing decisions in global and internatio-nal contexts. These are explained mainly by Porters diamond and cluster models. Another focus is on internatio-nalisation strategies, which require country analyses and decisions on the selection of national markets as well as a timing of the countries market development. In addition, the module discusses different strategies for mar-ket entry and market development.Outline of syllabus:1. Internationalisation of the economy and regional integration processes• Globalisation• Competitiveness of countries, industries and companies in an international context2. International strategic marketing decisions• Market entry forms• Market development strategies• Timing strategies• International organisation structures3. Theories and strategies of internationalisation• Foreign trade theory• Multinational enterprise• Internationalisation strategiesReading:Meffert, H. / Burmann C. / Becker, C.: Internationales Marketing-Management, Stuttgart etc. (most recent editi-on).Berndt, R. / Fantapié-Altobelli C. / Sander M.: Internationales Marketing-Management, Berlin etc. (most recent edition).","Students acquire in-depth skills in the field of strategic and operational management with particular attention to the international context. Students achieve particular expertise in the analysis, assessment and implementation of international business decisions and gain skills thus guiding the execution of marketing and management po-sitions in globally-active companies.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Brand Management & Market Research,12-M-MM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:At the beginning of the 21st century, marketing - until then interpreted as a market-oriented corporate manage-ment approach - was further developed to be seen as the entrepreneurial task of creating ""shared value"" for the organisation on the one hand and - broadly speaking - for society on the other hand. This idea leads to high re-quirements regarding the strategic sustainable positioning of the brand as well as brand management itself.Outline of syllabus:1. Brand leadership and brand assessment2. Brand leadership, identity and relevance according to David Aakers approach3. Brand strategies4. Consumer behaviour5. Market research methods and the development of brand strategies6. Market research methods","Based on the theories of Meffert and Aaker, students will gain a profound understanding for brand leadership, which will be deepened by many pracital implications and examples. Provided by cases studies and market re-search tools, its the defined goal of this lecture to convey an in-depth knowledge for consumer behavior and su-stainable brand management.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Strategic Networks in Industry,12-M-MS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"The primary object of this course is to gain a detailed understanding of strategic networks and of the phenome-non of clustering in the industrial industry. The example of the international automotive industry is used for clari-fication of the theoretical contents.The focus is on marketing in industrial companies and also on CSR - CSR is considered the ""driver"" of sustaina-ble innovations - as well as the different strategy types of sustainable innovations.Outline of syllabus:1. Strategic networks and clusters in industrial industries such as the automotive industry2. Transaction types of Williamson as well as strategic cooperation between automobile manufacturers and sup-pliers3. Management of business types, in particular the business of suppliers in the automotive industry4. Cluster and entrepreneurship activities5. Sustainable innovation strategies","By the end of the course, students gain a profound understanding above the basics of network research. Further-more students will aquire sectoral knowledge of the automotive industry as well as detailed cluster skills.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Strategic Marketing,12-M-SM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:The module raises awareness in students of the relevance and necessity of strategic management in a competiti-ve and dynamical competitive process.Content:Based on the marketing strategies as well as the stakeholder and entrepreneurship approaches, this module discusses the roots of the concept of strategy in marketing based on Drucker, Porter, Ansoff and Mintzberg. The focus of the module is on thinking in competitive advantages, which is directly related to responsible leadership.Outline of syllabus:1. Competitive dynamics requires strategy and leadership2. Marketing strategies, stakeholder management and entrepreneurship3. Objectives and tasks of corporate governance in management practice4. Competitive forces, strategies and benefits according to Michael Porter5. Growth strategies and marketing myths6. Future technologies, new businesses and dynamic capabilities7. Nature and principles of responsible managementReading:Barnard, CI (1938): The Functions of the Executive, Harvard University Press, Cambridge, Massachusetts.Eschenbach, R.; Eschenbach, S.; Kunesch, H. (2008): Strategische Konzepte: Management-Ansätze von Ansoff bis Ulrich, 5th ed., Schäffer-Poeschel Stuttgart.Freeman, RE (2010): Strategic Management: A Stakeholder Approach, Cambridge University Press.Grant, R. M.; Nippa, M. (2006): Strategisches Management: Analyse, Entwicklung und Implementierung von Un-ternehmensstrategien, 5th ed., Pearson Munich.Hinterhuber, H. H. (2011): Strategische Unternehmensführung -- I. Strategisches Denken, 8th ed., Erich Schmidt Verlag, Berlin.Hungenberg, H. (2012): Strategisches Management in Unternehmen: Ziele -- Prozesse -- Verfahren, 7th ed., Gabler, Wiesbaden.Johnson, G.; Scholes, K.; Whittington, R. (2009): Fundamentals of Strategy, 1st ed., Financial Times and Prentice Hall Harlow.Kotler, P.; Berger, R.; Bickhoff, N. (2010): The Quintessence of Strategic Management, Springer, Heidelberg.Laasch, O.; Conaway RN (2014): The Principles of Responsible Management: Global Sustainability, Responsibili-ty, and Ethics, Cengage Stamford.Meffert, H.; Burmannn, C.; Kirchgeorg, M. (2012): Marketing -- Grundlagen marktorientierter Unternehmensfüh-rung, 11th ed., Gabler, Wiesbaden.Meyer, M. (1995): Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unter-nehmung, Gabler, Wiesbaden.Müller-Stewens, G.; Lechner, C. (2011): Strategisches Management -- Wie strategische Initiativen zum Wandel führen, 4th ed., Schäffer-Poeschel Stuttgart.Porter, M. (1999): Wettbewerb und Strategie, Econ Munich. (Original: Porter, M.: On Competition, Boston, 1998.)Porter, M. (2014): Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frank-furt / New York. (Original: Porter, M.: Competitive Advantage, New York, 1985)Porter, M. (2013): Wettbewerbsstrategie -- Methoden zur Analyse von Branchen und Konkurrenten, 12th ed., Campus, Frankfurt / New York. (Original: Porter, M.: Competitive Strategy, New York, 1980)Welge, M. K.; Al-Laham, A. (2012): Strategisches Management: Grundlagen -- Prozesse -- Implementierung, 6th ed., Springer Wiesbaden.","The students have a deeper understanding of the sustainable corporate management and have the basics of the competitive process and competitive dynamics available. In addition, they can use the acquired knowledge, whi-le taking into account the conventional problems of the strategic and sustainable management, to solve busi-ness case studys on their own.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Industrial Management 4,12-M-BE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This course will develop the objectives, principles and structure of electronically supported procurement proces-ses with a special focus on catalogue-based procurement systems, electronic tendering systems, electronic (re-verse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management sy-stems.","The students will be able to describe and evaluate both the potentials and goals of electronic supported pro-curement systens and will be able to design appropriate systems for real-life applications. Students will get in-sight into the essentials of operational procurement management, especially e-procurement with a focus on ca-talog-based procurement systems, electronic tendering systems, electronic (reverse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management systems. After completing this mo-dule, students can define and analyze the related tasks and processes and show or develop theory-based and application-oriented possible solutions at a high professional level.",V (2) + Ü (2),"a) Written examination (approx. 40 to 60 minutes) orb) Presentation (approx. 20 Minutes) and term paper (15 to 20 pages), weighted 1:1 orc) Term paper (30 to 40 pages) ord) entirely or partly computerised written examination (approx. 60 minutes) ore) Portfolio (approx. 20 pages)Creditable for bonusLanguage of assessment: German and/or English","20 places.(1) A total of 15 places will be allocated to students of the Masters degree programmes Management as well as International Economic Policy.Should the number of applications exceed 15, these places will be allocated by lot. A waiting list will be maintai-ned and places re-allocated by lot as they become available.(2) A total of 5 places will be allocated to students of the Masters degree programme Information Systems. Should the number of applications exceed 5, these places will be allocated by lot. A waiting list will be maintai-ned and places re-allocated by lot as they become available.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.","Module can be taught in form of E Learning course, seminar, workshop etc.",150 h,--,-- +Industrial Management 2,12-M-LA-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module analyses and classifies approaches of production planning and control. In addition, it develops methods and models of lot sizing and scheduling. The focus is on the determination of optimal production and transport volumes as well as the planning of orders and manufacturing orders.","Students learn essential concepts, principles and methods of production planning and control with emphasis on the determination of optimal production and transport volumes as well as the planning of production and order sequences. Then, based on this expertise related knowledge broadening and deepening, essential competen-cies are conveyed, which allow the imaging of realistic situations and problems using mathematical and quanti-tative models for the derivation and assessment of alternative courses of action. After completion of the modu-le students can answer, analyze and structure questions of production planning and control, goal-oriented. They can also arrange the planning areas in the overall business context and have an in-depth overview of the produc-tion planning and control.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Industrial Management 1,12-M-SBM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"The course addresses central issues of strategic supply management. The supply function of the company (purchasing, materials management, procurement logistics) and its strategic importance is analysed and basic methods are developed that are relevant in this area.","Students learn the principles of performance-oriented optimization of all procurement activities to develop long-term, competitively sensitive potential for success. After completion of the module students are able to prepa-re structured, to goal-oriented analyze and to respond to performance-oriented issues of strategic procurement based on key instruments. Students are able to accurately classify the tasks of the procurement and to describe and discuss their strategic importance and dominate essential methods and procedures used in this area to ap-ply.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Industrial Management 3,12-M-SPM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module will discuss contents and procedures of strategic production management and, in particular, plan-ning and control concepts.Students will become familiar with the essentials of strategic production management. Theoretical and analyti-cal models will be used for analysing both economic and ecological issues. In addition, the module will discuss principles of value structure optimisation and will develop competences regarding the development of integra-ted mathematical models.","After completion of the module students are able to process, to analyze and answer questions of operations strategy structured and goal-oriented in a global context using appropriate methods. Furthermore, they know the main strategic tasks and objectives in production management and evaluate and apply planning and control concepts for the production in realistic application situations.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Legal Foundations of Risk Management and Compliance,12-M-RM1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,2,numerical grade,1 semester,graduate,"Content: This module analyses the presentation of opportunities and risks in financial reports, i. e. annual or in-terim reports, in conjunction with selected value-based management and profitability analysis approaches.Outline of syllabus:1. Basics of financial reporting and risk management;2. Practice of risk reporting;3. Profitability analysis according to Penman;4. Value-based management and risk management;5. Residual income and business valuation;6. Analysis of equity risk;7. Analysis of credit risk;8. Risk management monitoring by audit committees and auditors.Reading list to be provided in class.","After completing the course, the students will be able1. to present the relation between risk management and financial reporting;2. to analyze and solve independently complex problems with respect to the presentation of opportunities and risk in financial reports based on national and international standards;3. to identify the relation between risks and value-based management;4. to evaluate independently selected research results concerning risk reporting and desing own research- or practice-oriented projects.",V (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,"30 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,60 h,--,-- +Financial Statement Analysis and Business Valuation,12-M-UA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,5,numerical grade,1 semester,graduate,"Fundamental investing involves valuation, and much of the information for valuation is contained in financial statements. This module provides a basic understanding of financial statement analysis, particularly on how to extract value-relevant information from financial statements, carry out financial statement analysis, and use fi-nancial data to value corporations. The module also provides the necessary tools to gain insights into what ge-nerates value in a corporation.","Students can understand publicly traded companies financial statements (US GAAP/IFRS), identify value-rele-vant information in financial statements, and use this information for valuation. They know the relevant techni-ques to evaluate financial statements and understand the fundamental role of financial information in the valua-tion process. Students can apply valuation technics to real-world cases and recommend investment decisions.",V (2) + Ü (2),written examination (approx. 60 to 120 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Philosophy of Science and Ethics in Business Management and Economics,12-M-WEW-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,10,numerical grade,1 semester,graduate,This module will take the form of a seminar. Participants will independently work on a problem in economic poli-cy or will review an important publication on a topic in economics.,Students are able to present the status of a current project in a talk as well as to discuss and defend it.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Risk Management - Concepts and Systems,12-RM-KS-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Accoun-,5,numerical grade,1 semester,graduate,"Concepts: The course will provide students with an overview of the main goals, contents, methods and instru-ments of opportunity and risk management in industrial and commercial enterprises. Systems: The course will provide students with an overview of the design and functionality of essential information systems for risk mana-gement.","Concepts: After completion of the module students have a sound understanding of basic concepts, processes, methods and tools of risk management. They are able to justify the duties and functions of risk management in the company in theory and practice. They can also evaluate proposed solutions for the design of a risk manage-ment system, analyze selected issues of risk management and building on that, develop their own solutions. Sy-stems: After completing this module, students can(i) judge legal, organizational and methodological requirements for the implementation of risk management pro-cesses in a risk management information system (RMIS);(ii) understand the technical basis for RMIS;(iii) estimate the different characteristics of various information systems for the RM;(iv) understand the workings of RMIS.",V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,"25 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Discounted Cashflow,12-M-CF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The module covers discounted cash flow (DCF) methods under certainty as well as uncertainty in the context of the valuation of unlevered and levered companies. Furthermore, tax aspects as well as their influence on the company value are considered.Syllabus:1. Introduction2. DCF Theory under certainty1. NPV without taxes2. NPV with personal taxes3. NPV with corporate taxes3. DCF Theory under uncertainty1. DCF basics2. Valuation of unlevered companies3. Valuation of levered companies4. Practice of DCF methods","After completion of this module, the students will know a variety of discounted cashflow techniques and are able to apply properly them in order to evaluate projects or firms.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Portfolio and Capital Market Theory,12-M-CF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module conveys profound knowledge of individual portfolio choices and on this basis the most important capital market theory (namely capital asset pricing model) is introduced, including its assumptions, implications and extensions.Syllabus:1. Modern Portfolio Selection1. 2 Asset-Case2. Multiple-Asset-Case3. Critique of Portfolio Theory2. Capital Asset Pricing Model1. Assumptions and Derivation2. Implications3. Empirical Aspects, Extensions and Alternatives",This module enables the students(i) to explain and to determine the optimal capital market position of an investor given the different investment opportunities and individual utility function;(ii) to understand and use the central CAPM propositions for valuating risky assets.,V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Risk Management and Corporate Finance,12-M-CF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module deals with the valuation and use of classical derivatives in financial markets. In particular, futures, swaps and options are considered as well as their possible applications in the context of financial risk manage-ment. In particular, students will be introduced to the theory involved in pricing options, as well as important va-luation parameters. In addition, some established risk measures such as value-at-risk are discussed.1. Introduction2. Futures & Forwards3. Swaps4. Options5. Measures of risk","Upon completion of this module students will be able to,(i) independently determine the fair value of the derivatives discussed, as well as(ii) to understand and evaluate common capital market hedging strategies.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Risk measurement and risk valuation: Concepts and applications for banks,12-M-CF5-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,The course augments the usual consideration of symmetric risk metrics by introducing metrics for downside risks and the concept of risk as a capital requirement. The focus for applications in banks lies in the treatment of risks with regard of supervisory regulations.,"After completing the course “Risk measurement and risk valuation: Concepts and applications for banks” the students are able1. to judge the appropriateness and problems of asymmetric risk measures,2. to address essential risks in banks and to understand their handling by supervisory regulations as well as3. to realize the concept of risk as a capital requirement being the systematic base for these aspects in the ban-king sector.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Economics of Tax Planning,12-M-SP-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This course deals with tax effects on fundamental economic decisions. Taxes are integrated into standard mo-dels for investment decisions, financing decisions, firm valuation, dividend policy and remuneration of employ-ees. Therefore, the interaction of corporate and personal income taxes is analysed.A reading list in English is available on request.","This course enables students to(i) combine their knowledge of tax law with microeconomic analyses in the areas of corporate and personal fi-nance;(ii) analyze the effect of taxes on fundamental economic decisions, e.g. investment and financing decisions, eva-luation of investment, financial assets, forms of remuneration for employees including managing and assessing;(iii) read and discuss research and policy papers in the field of taxation.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Tax Accounting,12-M-STB-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This module introduces the various methods of income recognition in the German Income Tax Code (Einkommen-steuergesetz, EStG). It discusses the main reporting and valuation provisions as well as the specific problems and techniques of income calculation for partnerships.",Students have in-depth knowledge of tax accounting of companies and are able to solve moderate to complex problems of tax accounting in particular of sole proprietorships and partnerships using legal source.,V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Incentives in Organizations,12-M-AO-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"Based on the classical principal-agent theory, this course discusses methodological and empirical aspects of in-centives in organisations. It uses contents from advanced text books and original (mainly empirical) research ar-ticles.Outline of syllabus1. Principal-agent theory2. Do top managers earn too much? (application)3. Performance-based payment4. Implementation of performance-based payment in companies (application)5. Seniority payment (with application)6. Financial incentives to work after retirement (with application)7. Efficiency wages (with case study)8. Team incentives (with case study)","Students acquire a working knowledge of key incentive models models, selected empirical applications and the necessary econometric background. This enables them to identify the advantages and disadvantages of different incentive systems that are applied in the enterprise context, to make informed management analyses and to cri-tically evaluate current controversies and developments as well as to conduct their own research.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Human Resource Management and Industrial Relations,12-M-HRM-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"The lecture ""Human Resource Management and Industrial Relations"" introduces advanced theories, estimation techniques and empirical results from the areas of human resources management and institutional frameworks such as ithe different actors in ndustrial relations.SyllabusIntroduction: Human Resource Management & Industrial RelationshipsChapter 1: The employment contract [formal model]Chapter 2: Motivation [formal model]Chapter 3: Employee resistance against reorganisations [empirical study]Chapter 4: The role of works councils [formal model]Chapter 5: Works councils and the employer wage structure [empirical study]Chapter 6: The behaviour of labour unions [formal model]Chapter7: Learning process of employers [formal model and empirical study]Chapter8: Demographic challenges of HRM [formal model and empirical study]","The aim of the lectures is to enable students to understand and apply advanced theories, estimation techniques and empirical results in the area human resource management and industrial relations on the basis of scientifc literature.",V (2) + Ü (2),a) Written examination (approx. 60 minutes) orb) Term paper (approx. 15 pages)Language of assessment: German and/or English,"There are no restrictions with regard to available places for students of the Masters degree programmes Mana-gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo-mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca-ted to students of other subjects; should the number of applications exceed the number of available places, the-se places will be allocated by lot.",--,150 h,--,-- +Corporate Strategy,12-M-UGF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This theory-led and application-oriented module provides you with critical knowledge and skills related to cor-porate strategy—essential for anyone aspiring to take on leadership roles in their future career, may it be in the private or public sector. The module goes beyond basic knowledge about strategic management provided by ba-chelor-level modules.(1) Developing strategies in pursuit of competitive advantage(2) Corporate diversification(3) Vertical integration and outsourcing(4) Mergers & acquisitions(5) Dynamic strategies(6) Cooperative strategies(7) Corporate spin-offs and spin-outs(8) Internationalization strategies (I)(9) Internationalization strategies (II)(10) Strategic change(11) Corporate strategies and new technologies(12) Corporate governance and corporate social responsibility(13) Corporate communication and crisis management(14) Wrap-up and Q&A",Educational aims• Clarify the role of corporate strategy• Explain theoretical concepts and mechanisms behind corporate strategy• Enable students to critically appraise alternative approaches to corporate strategy• Enable students to evaluate the boundaries and risks of corporate strategyLearning outcomesOn successful completion of this module students will be able to:• Assess the role of corporate strategy for creating and sustaining competitive advantage• Create and evaluate concepts related to corporate strategy• Make judgements about the organizational and managerial implications of corporate strategy• Systematically choose between different routes of action,V (2) + Ü (2)Module taught in: English,"a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, groups of 3 approx. 30 minutes)Language of assessment: English",--,--,150 h,--,-- +Change Management,12-M-CHA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis-cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa-tion is a universal principle. The module covers projects like merging two departments, restarting a department with team building, conducting an employee survey, or developing a new mission statement. The majority of the projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in-struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles in these processes and are able to use their knowledge for own future projects as well as to create their own so-lutions in change processes.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Accounting in the Company Management,12-M-CIU-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis-cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa-tion is a universal principle. The module covers projects like merging two departments, restarting a department with team building, conducting an employee survey, or developing a new mission statement. The majority of the projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in-struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles in these processes and are able to use their knowledge for own future projects as well as to create their own so-lutions in change processes.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Managerial Accounting,12-M-INST-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on accounting instruments, which are applied in the context of strategic management of enterprises. First, it addresses important drivers of strategic decisions from a microeconomic perspective, such as the emergence of cost and quality advantages in competition as well as scale and experience curve effects. Second, the module covers analytical and heuristic techniques of planning and control. In the context of these techniques, instruments of target costing, life cycle cost analysis, benchmarking and business wargaming are discussed with regard to their theoretical foundation and fields of application.","Initially, knowledge about fundamental requirements concerning instruments of decision-making and behavior control within enterprises is acquired. What is more, the module conveys obtaining knowledge about the strengt-hs and weaknesses and therewith fields of application and limits of prevalent instruments of strategic corporate management used by practitioners.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +"Coordination, Budgeting and Incentives in Organizations",12-M-KOBO-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"This module focuses on accounting-based instruments to control behavior in decentralized enterprises. The course first discusses the role of accounting in the context of decision-making and behavioral controlling as well as informational analyses. Afterwards, the most common instruments of behavioral controlling (budgeting, va-lue-oriented management, transfer prices) are discussed with regard to theory and practice.","This module aims to provide knowledge in the context of behavioral control in enterprises. Knowledge about re-quirements on instruments used for behavioral control are discussed and competences for deployment, struc-ture and development of coordination tools are provided.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Management and Control,12-M-PROM-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on the discussion and critical examination of instruments and methods used in the context of project management and control within enterprises. Both classic and agile approaches to project manage-ment are considered. It covers characteristic features and structures of projects, their possible success factors, methods and instruments of control and management of projects in various project phases. The theoretical basis as well as potential applications of these instruments are discussed.","Initially, knowledge about fundamental requirements concerning instruments of project management and con-trol is acquired. What is more, the module conveys knowledge about strengths and weaknesses and therewith fields of application and limits of commonly used instruments and methods of practitioners. Competences wi-thin the configuration and development of the project management and control as well as skills within the practi-cal use are obtained.",S (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Accounting and Capital Markets,12-M-REKA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on financial and management accounting, their functions, possible configurations as well as their impact on internal and external recipients under consideration of the institutional setting. In this con-text, an economic perspective has priority over detailed legal arrangements and regulations by the standard set-ters. Based on the theoretical foundations of information economics as well as decision-making and balance sheet theories, typical issues concerning cost and managerial accounting as well as financial accounting and pu-blicity are discussed.","Initially, a fundamental knowledge about the conception and impact of management and financial accounting as information systems is acquired. In the following, the module mainly sharpens the understanding of the eco-nomic impacts of the configuration of management and financial accounting. What is more, extensive knowled-ge about possible impacts of changes in institutional general frameworks is covered. For example, changes in valuation standards, publicity rules or regulations about the distribution of profits in enterprises and on capital markets are considered.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Analytics & Decision Making,12-M-MADM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Managerial Analytics & Decision Making"" discusses quantitative methods to structure and solve a diverse set of management problems and demonstrates the application of modern methods with the help of multiple case studies.",After completing this course students can(i) better understand and structure problems;(ii) apply important theoretical and empirical frameworks to practical problems that evaluate good and bad deci-sion making;(iii) implement advanced analytical methods to support decision making under risk.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Management of Global Supply Chains,12-M-SMGS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"Description:In the course ""Strategic Management of Global Supply Chains"", students will become familiar with the basic principles of building an efficient global supply chain and will apply what they have learned working on multiple case studies.","After completing this course students(i) can apply the basic methods and concepts of supply chain management to practical settings and evaluate the results, and(ii) understand the effects of global value chains onto strategic company decisions.",V (2) + Ü (2)Module taught in: English,written examination (approx 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Decisions and Competition,12-M-SDC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,1. Strategic situations and decision making2. Analyzing strategic situations with game theory1. Noncooperative simultaneous move games2. Nash equilibrium3. Models of oligopoly markets3. Dynamic Games1. Two(-multi) stage games and subgame perfect equilibrium2. Role of commitment in dynamic situations3. Models of advertising4. Wage bargaining and unions4. Repeated Games1. Emergence of coordination in long interactions2. Collusion between competing firms3. Time consistent monetary policy5. Static games of incomplete Information1. Bayesian Nash equilibrium2. Auctions6. Dynamic games of incomplete information1. Moral hazard and nonlinear pricing2. Perfect Bayesian equilibrium3. Signalling games4. Job-market signalling5. Corporate investment and capital structure,"After successful completion of this class, the students should be familiar with economic models that can be used to shape managerial strategy and aid in making decisions in strategic situations. Especially, by making use of simple two stage games, they should be able to formulate dynamic policies in a wide variety of strategic situa-tions. The students will acquire an intuitive understanding of the underlying economic mechanisms which emer-ge from the analysis of game theoretic models for a wide variety of strategic situations arising in industrial eco-nomics, marketing, organization, finance, trade and labor. Moreover, they will acquire skills which enable them to make predictions in strategic situations by making use of simple mathematical models. By means of comple-ting case based exercises, they will learn to transform real life business situations to an appropriate economic model. Based on an analysis of this model, they will be able to devise optimal strategies and derive the corre-sponding managerial implications.The course will be taught in English.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Theory of Industrial Organization,12-M-TI1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Theory of industrial organisation:1. Monopoly pricing• Nonlinear pricing and mechanism design• Dynamic pricing: experience goods, durable goods2. Oligopoly pricing• Static price and quantity competition in homogeneous and differentiated goods markets• Comparative statics• Equilibrium market structure3. Dynamic competition in oligopoly markets• Subgame perfect equilibrium and models of dynamic competition• Repeated games and collusion4. Strategic behaviour by incumbent firms• Entry deterrence and predation• Signalling and reputation5. Behavioral Industrial Organization• Reference Dependent Preferences and Framing Effects• Time inconsistent behaviorThe course will be taught in English.","Students which complete this class will acquire a working knowledge of advanced theoretical models of compe-tition in oligopoly markets as well as sophisticated pricing techniques in monopoly markets. They will learn the conditions under which the predictions of these models are valid. They will become familiar with applications of advanced game theoretic tools, such as dynamic models of competition, for studying interactions between firms in markets. By means of comprehensive exercises, they will apply the methods they learn in class to practical-ly relevant problems. They will be in a position to read academic papers on related topics, assess the strengths and weaknesses of an approach, summarize and comment on these papers and suggest possible extensions.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +European Competition Policy,12-M-WPE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Outline of syllabus:1. Legal environment, competition laws2. Market definition• Qualitative methods• Simple quantitative methods• Hypothetical monopoly test3. Horizontal agreements and collusion: repeated games and factors affecting likelihood of collusion4. Horizontal mergers and collusion• Economic theory• Efficiency effects• Coordinated effects5. Vertical relations and contracts• Economic analysis of contracts• ""More economic approach""6. Abuse of dominant position• Classification of abusive conduct• Economic analysis of abusive conduct and theory of harmThe course will be taught in English.","After completion of the module students can use the advanced concepts introduced in the lecture of competiti-on policy, including the legal framework, the trace models and methods for the study of competition policy issu-es, as well as understand the approach of European competition policy in high profile cases. When they are con-fronted with practical problems, they can refer to these cases, and the same logic to practical examples apply by draining the relevant economic theories that identify variables to be measured and methodologies for assessing, and based on that adequate conclusions for appropriate cases. They will sufficiently understand the subject in order to open up that build upon literature in journals and being able to think critically.",V (2)Module taught in: English,a) Written examination (approx. 60 to 120minutes) orb) Term paper (15 to 20 pages)Creditable for bonusLanguage of assessment: English,"There are no restrictions with regard to available places for students of the Masters degree programmes Mana-gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo-mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca-ted to students of other subjects; should the number of applications exceed the number of available places, the-se places will be allocated by lot.",--,150 h,--,-- +Econometrics 1,12-M-OE1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Econometrics,5,numerical grade,1 semester,graduate,"Description:This module deals with the basic concept and methodology of the ordinary least squares (OLS) regression mo-del. In particular, model assumptions and properties are discussed and formally motivated. In addition, the mo-dule examines linear restrictions on the models explanatory variables as well as dummy variables and introdu-ces tests to verify simple and multiple linear restrictions.Linear algebra is used as formal aid.Outline of syllabus:1. Random variables2. Important distributions3. Point estimates4. Simple linear regression model5. Model assumptions6. Model properties7. Simple hypothesis tests8. Multiple linear regression model9. Linear restrictions10. Dummy variables11. Multiple hypothesis tests","The students acquire knowledge of the basics, concepts and methods used in the classical linear regression mo-del and understand the role of econometrics in science and data analysis. In particular, they learn how to analy-tically derive, calculate and interpret the coefficients, standard errors and p-values of a classic regression output of the multiple regression model. Furthermore, they are able to formally state and motivate the assumptions and properties of OLS and know how to deal with transformed and dummy variables. Additionally, students will be able to test multiple linear restrictions on the parameters and will be able to apply these tests to real economic, business and social science questions.The competences acquired in this course serve as a prerequisite for ""Econometrics II"", ""Econometrics III"", ""Micro-econometrics"" und ""Financial Econometrics"".","V (2) + Ü (2)Module taught in: German (winter semester), English (summer semester)",a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Advanced Microeconomics,12-M-AM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Contract Theory and Information Eco-,5,numerical grade,1 semester,graduate,"In a nutshell, microeconomic theory considers the behavior of individual economic agents and builds from this foundation to a theory of aggregate economic outcomes, which then can be applied for conducting welfare ana-lysis and giving policy advice. This lecture addresses the core building block of this thought complex: individu-al decision making and behavior. Specifically, students will come to understand in detail the standard models of riskless consumer choice, choice under risk and intertemporal choice and learn about the empirical challenges and limitations of these models.Throughout the lecture, we will work with precise mathematical formalizations of the ideas that we want to think and talk about. In consequence, a solid understanding of the mathematical toolbox of standard microeconomics (e.g., differential calculus and constrained optimization; basic set theory; integration by parts) will be helpful as it will allow to focus on the underlying economic intuition. However, every required mathematical concept will be introduced and explained along the way, such that a strong interest in formal economic analysis is more import-ant than an advanced mathematical background.The exposition is primarily based on the standard graduate textbooks• Mas-Colell, Whinston and Green (1995): “Microeconomic Theory”• Jehle and Reny (2001): “Advanced Microeconomic Theory”","After completing the course students will be able to• explain essential findings of microeconomic theory,• apply the involved methods to given stylized examples on their own,• recognize in which real life situations and how the results can be applied.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Management and Economics 1,12-M-APW1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or presentation (approx. 30 to 45 minutes)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Management and Economics 2,12-M-APW2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or d) presentation (approx. 30 to 45 minutes)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Information Systems 1,12-M-AWI1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi-ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration (approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 2,12-M-AWI2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi-ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration (approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Digital Marketing I,12-M-DM1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Digitalization is rapidly changing our lives, including all types of business relationships. Therefore, new opportu-nities and approaches have emerged in all areas of the marketing mix: Managers can choose from a wide variety of new communication channels, such as social media networks, blogs, or messengers, and can engage in influ-encer marketing and search engine optimization. They increasingly rely on online customer co-creation or crowd-sourcing and create a wide variety of new digital products and services, often related to completely new busi-ness models. Through price crawlers and price setting tools customers‘ price search behaviors have significant-ly changed, requiring new price setting techniques. Artificial intelligence enables managers to automize and op-timize many of these marketing processes, thus offering new opportunities and challenges for companies. Over-all, digital marketing offers a tremendous variety of concepts and approaches to seize respective opportunities and deal with related challenges, which will be largely highlighted and discussed in this course.","This course provides a broad overview about these new approaches of digital marketing. It explains the underly-ing concepts of digital marketing and illustrates these approaches and concepts along numerous case studies. After attending this course, students will have a broad as well as in-depth understanding of digital marketing and its tools. Morever, they will understand of how to implement these tools successfully in business practice.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Digital Marketing II,12-M-DM2-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Students are required to put themselves in the following business situation:A large corporation has just recruited you and your team members as the new heads of the marketing depart-ment in one of the firm’s divisions in order to manage its general and digital marketing activities. Specifically, it is your task to manage the corporation’s digital product portfolio, segmentation and positioning as well as its marketing mix strategy over a period of 10 years.Structure of the class:• Long-term business simulation game (details see below) that students will play in groups• Lectures and discussion rounds on strategic approaches to succeed over a duration of 10 periods","Studierende lernen in diesem Kurs, zentrale Konzepte des Online- und Offline-Marketings gezielt und bezogen auf die jeweilige Unternehmenssituation anzuwenden. Der Kurs bildet somit die Brücke zwischen Theorievermitt-lung und entsprechende Anwendung in der Unternehmenspraxis.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +E-Commerce I,12-M-EC1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in-dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat-egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti-ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre-sentations where the students (in groups) will either apply selected lecture topics to real-world business cases or present the core aspects of research articles dealing with e-commerce topics in general.",This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as-sessing business strategies.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +E-Commerce II,12-M-EC2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in-dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat-egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti-ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre-sentations where the students (in groups) will either apply selected lecture topics to real-world business cases or present the core aspects of research articles dealing with e-commerce topics in general.",This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as-sessing business strategies.,V (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Real-Time Process Analytics,12-M-RTP-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,The course teaches advanced approaches to process analytics. Students will learn to model and measure pro-cesses and process execution based on past and present data.,"After successfully completing the course, students should be able to• Understand process modeling and process execution in an SOA• OLAP analysis in a process warehouse• Business Rules for BPM• Complex Event Processing• Event-driven BPM using CEP and Business Rules",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Data Science,12-M-TDS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"Data science is concerned with extracting knowledge and valuable insights from data assets. It is an emerging field that is currently in high demand in both academia and industry. This course provides a practical introducti-on to the full spectrum of data science techniques spanning data acquisition and processing, data visualization and presentation, creation and evaluation of machine learning models.The course focuses on the practical aspects of data science, with emphasis on the implementation and use of the above techniques. Students will complete programming homework assignments that emphasize practical understanding of the methods described in the course.",Topics covered include:• Data acquisition and processing• graph and network models• text analysis• working with geospatial data• Usage of machine learning models (supervised and unsupervised),V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Information Systems 1,12-M-TIF1-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Information Systems 2,12-M-TIF2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Stochastic Models for Risk Analysis,12-RM-RA-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Point and interval estimation for the value at risk Point and interval estimation for the conditional value at risk Prediction of value at risk in time series Risk of forecasts in time series, in particular exponential smoothing un-der covariates Conditional heteroscedasticity: ARCH, GARCH, EGARCH, DVEC, BEKK, DCC Aggregated losses and their empirical analysis Empirical analysis of statistical distributions Nonparametric bounds for the value at risk and conditional value at risk Empirical estimation of nonparametric bounds for value at risk and conditional va-lue at risk Market model: definition, derivation, parameters, empirical analysis Capital asset pricing model: de-finition, parameters, empirical analysis Asset portfolios: definition, risk parameters Estimation of portfolio para-meters: variance, value at risk, conditional value at risk, shortfall Optimum portfolios: concepts, theory, numeri-cal analysis","The student is able to estimate risk measures and the parameters of risk models from data. In particular, the stu-dent knows software packages and routines which enable empirical risk evaluation in a business context.",Ü (2) + V (2),Written examination (approx. 60 minutes),"30 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Stochastic Models for Risk Assessment,12-RM-RW-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Etymological background of the risk concept Definitions of risk Basic concepts and terminology of stochastic risk modelling: risk phenomenon, risk object, risk variable, risk source, risk factor, risk cause, direct peril, indirect peril, loss under risk, profit under risk, loss variable, profit variable, risk distribution, risk indicator, risk parame-ter Classification of business risks Risk policy, risk management Risk analysis: risk identification, risk descrip-tion, risk exploration, risk-relevant measurements, risk evaluation, risk assessment, risk modelling Risk mana-gement: risk minimisation, risk protection, risk avoidance, risk mitigation, bearing of risk, risk prevention Risk control, risk monitoring Norms and standards of risk management: ISO 31000, ONR 49000 -- 49004, IEC/ISO 31010, COSO II, AIRMIC, IRM, ALARM FMEA (Failure Mode and Effect Analysis) as a tool of risk analysis and risk assessment: historical and thematic background, methodology, discussion of the FMEA assessment methodo-logy Risk matrix, risk diagram Score diagram Stochastic risk parameters and risk measures as distribution para-meters Probability distributions: Gaussian, Laplace, Students t, extreme value, logistic, exponential, Weibull, gamma, negative Gaussian, Burr, hyperbolic, generalised hyperbolic Elementary stochastic risk measures: va-riance, standard deviation, signal-to-noise ratio, coefficient of variation, Sharpe ratio, nonconformance probabi-lity, expected shortfall, shortfall probability, risk parameters under reference values, Stone family Value at Risk and Conditional Value at Risk: definition, formal representations, values under special probability distributions Axioms of risk measures: distribution invariance, subadditivity, superadditivity, additivity, comonotonous additi-vity, nonnegative homogeneity, translation invariance, convexity, continuity, coherence","The student knows the schemes and concepts of risk analysis, risk assessment, risk measurement, and the theoretical background. The student knows the concepts of advanced stochastic risk modeling. In a practical business situation, the student is able to identify an appropriate scheme of risk assessment and corresponding meaningful risk measures.",V (2) + Ü (2),Written examination (approx. 60 minutes),"30 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Communication in Business and Economics,12-M-BUC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"The lecture names introductory relevant communication models. Furthermore, the theoretical models of PR are discussed. The added value of communication for companies, business, politics, and science is explained. The discrepancy between journalism and PR is discussed, as well as the basic elements, instruments, goals, and forms of PR. The preparation and implementation of press meetings, conferences, campaigns, and events will be systematically explained, and the central aspects of corporate communications will be outlined. The exerci-se deals with the practical implementation of journalistic styles in the various media and provides an overview of the possibilities and concepts of PR work across different media and target groups.","After participating in the module courses, students are able to understand and apply PR and its forms, elements as well as methods and in a holistic context. Students learn professional competencies in the field of (business) communication with regard to reflection, argumentation, and exchange as a PR consultant in different areas. In addition, students will be able to apply concrete PR instruments in practice and prepare them professionally.",V (2) + Ü (2)Module taught in: English,written examination (approx. 60 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +"Business Communication in Print, Online and Social Media",12-M-ECC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"This module focuses on the relationship of offer characteristics with benefit aspects for the end consumer and the business models on the part of the providers. Starting from the basics of editorial work and professional text management, the new forms of communication management in social networks are presented. The focus of the lecture is on the use of social media in campaigns (Facebook, Twitter, Instagram, Tiktok). There will also be exer-cises on various Web 2.0 applications (e.g. online social networks) and on the collection and interpretation of online market research data. However, crisis communication of companies will also be covered in particular opi-nion-makers on the web as well as protest culture on the web.","By participating in the module courses, students acquire job-specific skills in research and interviewing. Stu-dents are able to collect and organize information according to criteria of topicality and relevance. In addition, students are taught journalistic expertise so that they are able to recognize the forms of presentation of news, re-ports, and background reports with their media characteristics and communicative functions in different media genres and create them themselves. Students will be able to prototype and design a social media campaign, de-scribe the editorial and technical approach including feedback, response, and customer engagement. In additi-on, students will be able to design counter-strategies for corporate communication crises.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Practice Lectures,12-M-VGP-202-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"In this lecture, we invite board members of publicly listed companies, SMEs and Startups to discuss contempo-rary challenges of corporate management.Students gain sustainable insights into current management practices, challenges of corporate management in various industries, and discuss pressing managerial issues with C-level executives. In individual and group as-signments, students are required to connect management theories with the managerial challenges of the spea-kers.Managers of the different companies are required to address the following questions that will foster a detailed discussion at the end of each lecture:- What are the current challenges facing your company?- Which strategies do you employ to respond to these challenges?- How have leadership concepts and approaches changed in your company?","After participating in this module, students should be able to combine theoretical approaches with current chal-lenges in management. The students obtain a realistic insight into a cross-section of the German economy. Through discussions reports and group presentations students’ social skills are trained in addition to professio-nal skills.",S (2),portfolio (approx. 15 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Advanced Topics in Data Science,12-M-ATDS-211-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"In this course, students work on advanced data science projects. The course covers the entire data science work-flow from data collection to data preparation to modeling, evaluation and deployment. By following a top-down teaching approach, students are enabled to apply complex machine learning models from the beginning.","As part of the course work, students will acquire knowledge and skills in the following areas:1. Becoming familiar with the principles and frameworks in the research area of Data Science.2. Apply machine learning and deep learning frameworks to structured and unstructured data3. Design, implementation and evaluation of key algorithms within an end-to-end workflow in the field of Data Science4. Application of Jupyter notebooks and their infrastructure (collection, storage, retrieval, and analysis of data)5. Understanding of a data-driven & analytical approach to decision problems",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) orb) term paper (approx. 15 pages)Language of assessment: German and/or EnglishAssessment offered: Only when announced in the semester in which the courses are offeredcreditable for bonus,--,--,150 h,--,-- +International Marketing Strategy,12-M-IMS-211-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The objective of this simulation course is to develop hands-on skills of how to make international marketing de-cisions. Emphasis is put on the computer simulation game Country Manager which focuses on the managerial is-sues arising when companies plan and execute market entry into new countries. This exercise allows students to experience the challenges pertaining to corresponding decisions by playing the role of a responsible manager for a major consumer products company. Students have to decide on the countries to enter, the mode of entry, the segments to target, and every aspect of the marketing mix (price, promotion, place and product) and will get im-mediate feedback on the consequences of their actions.","After completion of the course, participants should have gained a broad appreciation of critical decisions in in-ternational marketing.",S (2),a) written examination (40 to 60 minutes) orb) term paper (15 to 20 pages) and presentation (approx. 20 minutes) (weighted 2:1) orc) term paper (30 to 40 pages) ord) portfolio (approx. 20 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Economist Practice Lectures,12-M-VWP-211-m01,Faculty of Business Management and Economics,"Holder of the Senior Professorship for Economics, Money",5,numerical grade,1 semester,graduate,"The content of the seminar is the active participation in as well as the follow-up of the lectures of economists from different national and international fields of activity, which are organized for the event.The invitation of speakers from practice strengthens the practical orientation of the scientifically founded and at the same time internationally oriented education at the faculty of economics of the University of Würzburg.In this way, students will gain lasting insights into the fields of activity of economists, gain an insight into prac-tical activities, discuss these with high-ranking economists and combine them with theoretical economic know-ledge gained during their studies.","By participating in the seminar, Masters students of the faculty of economics and business administration should get to know the different fields of activity of economists and the questions that determine the daily work of the speakers in the course of the lectures.In addition, the participants of the seminar will have the opportunity to apply the knowledge of economics they have acquired during their studies. For this purpose, in addition to a discussion with the speakers following the respective lecture, a debating workshop is offered to the participants of the seminar, in which the students are to learn economic argumentation and debate management. The learned contents and competencies will be tested at the end of the semester.",S (2),"a) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orb) term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1) orc) written examination (approx. 60 minutes)Language of assessment: German and/or English",--,--,150 h,--,-- +Enterprise AI,12-M-EAI-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) term paper (approx. 15 pages) orc) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Information Systems and Artificial Intelligence 1,12-M-KI1-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) orc) term paper (approx. 15 to 20 pages)Language of assessment: German and/or EnglishAssessment offered: In the semester in which the course is offeredcreditable for bonus,--,--,150 h,--,-- +Information Systems and Artificial Intelligence 2,12-M-KI2-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) orc) term paper (approx. 15 to 20 pages)Language of assessment: German and/or EnglishAssessment offered: In the semester in which the course is offeredcreditable for bonus,--,--,150 h,--,-- +Vertical Storytelling,12-M-VS-221-m01,Faculty of Business Management and Economics,nan,10,numerical grade,1 semester,nan,--,--,S (2),"portfolio (approx. 5 pages)Assessment offered: every year, summer semester",--,--,300 h,--,-- +Organizational Economics and Digital Transformation,12-M-OEDT-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: EnglishCreditable for bonus,--,--,150 h,--,-- +Policy Evaluation Methods,12-M-PEM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Labor Economics,5,numerical grade,1 semester,graduate,"This course offers an introduction to the fundamentals of causal inference and to widely used research desi-gns in the social sciences. In the first part a framework for understanding causality is introduced. Specifically, the epistemological differences between association, intervention and counterfactuals are explained. Then it is shown why experiments are paramount in generating causal knowledge and which assumptions are needed for which level of the causal hierarchy. Finally, we will discuss two widely used approaches to causality in the social sciences, i.e. potential outcomes and directed acyclic graphs.The second part is devoted to the research designs regressions analysis, difference-in-differences, instrumen-tal variables, and regression discontinuity. The emphasis is how these research designs are for example applied to answer important questions in labour economics such as the effects of a minimum wage increase on employ-ment or the effect of children on female labour supply and wages.The assumptions each research design requires in order to identify a causal effect will be at center stage of the lecture. Therefore the emphasis is to teach students what one needs to estimate in order to answer a given que-stion. Further, the research designs are discussed such that students will be able to evaluate and apply these re-search designs to other questions and fields.","At the end of the course, students should be able to understand basic concepts and methods of causal infe-rence, as well as read, interpret, and assess the credibility of scientific publications. In addition, the course ser-ves as preparation for advanced statistics and econometrics courses.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: Englishcreditable for bonus,--,Research track module in Masters programme IEP,150 h,--,-- +Topics in Empirical Economics,12-M-TE-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,portfolio (approx. 50 hours)Prüfungssprache: EnglischCreditable for bonus,"12 *WA1(1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.(2) Places on all courses of the module with a restricted number of places will be allocated in the same procedu-re.(3) A waiting list will be maintained and places re-allocated by lot as they become available.",--,150 h,--,-- +Master Thesis Information Systems,12-WI-MA-192-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,30,numerical grade,1 semester,graduate,"Students will complete their degree with a Masters thesis in which they will be required to independently rese-arch and write on a topic in the area of business management and economics, drawing on the subject-specific knowledge they have acquired and adhering to the principles of good scientific practice. This thesis may either take the form of an analysis and structured presentation of the existing literature on a certain topic or may, as is often the case, also include a presentation of the students own original achievements, e. g. new algorithms de-veloped by students, surveys, the prototypical demonstration of a concept they developed or the application and (further) development of a theoretical model.","In the master thesis students prove that they can plan and carry out a science-based work to solve a particular problem within a specified period autonomously and to document the results in accordance with the professio-nal scientific standards in writing. Students are able to understand relevant contributions to research and pro-fessional practice, critically analyze and assess the relevance to their own specific questions. They can assess and recognize major lines of development and dynamics of the subject and therefore also the need to retrain continuously.",--,Masters thesis (approx. 60 to 80 pages)Language of assessment: German and/or English,--,Time to complete: 6 months,900 h,--,-- diff --git a/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx b/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..75d9e00e5e6ae7f8fb14584927d026c282de8e2b Binary files /dev/null and b/03_extracted_final_modules/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx differ diff --git a/03_extracted_final_modules/MS_MM_all_modules.xlsx b/03_extracted_final_modules/MS_MM_all_modules.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..20496c4c7409ce639e8480b8e29fb9c5adfee57e Binary files /dev/null and b/03_extracted_final_modules/MS_MM_all_modules.xlsx differ diff --git a/04_finetuning_approaches/FT_Tapas.ipynb b/04_finetuning_approaches/FT_Tapas.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..2001d5ed96e38911ecc50bb9e8ee76a85c7da6f2 --- /dev/null +++ b/04_finetuning_approaches/FT_Tapas.ipynb @@ -0,0 +1,3191 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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0ms-is-0100What is the abbreviation of the module Informa...felix_playground_SQA_Training/MS_IS_all_module...['(0, 1)']['12-IV-161-m01']
1ms-is-0100What is the ID of IT-Management?felix_playground_SQA_Training/MS_IS_all_module...['(1, 1)']['12-M-ITM-161-m01']
2ms-is-0100What is the abbreviation of Project Seminar?felix_playground_SQA_Training/MS_IS_all_module...['(2, 1)']['12-PS-192-m01']
3ms-is-0100What is the code for Information Retrieval?felix_playground_SQA_Training/MS_IS_all_module...['(3, 1)']['10-I=IR-161-m01']
4ms-is-0100What is the abbreviation of the module Analysi...felix_playground_SQA_Training/MS_IS_all_module...['(4, 1)']['10-I=PA-161-m01']
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idannotatorpositionquestiontable_fileanswer_coordinatesanswer_text
0ms-is-0100What is the abbreviation of the module Informa...felix_playground_SQA_Training/MS_IS_all_module...[(0, 1)][12-IV-161-m01]
1ms-is-0100What is the ID of IT-Management?felix_playground_SQA_Training/MS_IS_all_module...[(1, 1)][12-M-ITM-161-m01]
2ms-is-0100What is the abbreviation of Project Seminar?felix_playground_SQA_Training/MS_IS_all_module...[(2, 1)][12-PS-192-m01]
3ms-is-0100What is the code for Information Retrieval?felix_playground_SQA_Training/MS_IS_all_module...[(3, 1)][10-I=IR-161-m01]
4ms-is-0100What is the abbreviation of the module Analysi...felix_playground_SQA_Training/MS_IS_all_module...[(4, 1)][10-I=PA-161-m01]
5ms-is-0100What is the code for Security of Software Syst...felix_playground_SQA_Training/MS_IS_all_module...[(5, 1)][10-I=SSS-172-m01]
6ms-is-0100What is the ID of Software Architecture?felix_playground_SQA_Training/MS_IS_all_module...[(6, 1)][10-I=SAR-161-m01]
7ms-is-0100What is the abbreviation of the module Artific...felix_playground_SQA_Training/MS_IS_all_module...[(7, 1)][10-I=KI1-161-m01]
8ms-is-0100What is the abbreviation of Discrete Event Sim...felix_playground_SQA_Training/MS_IS_all_module...[(8, 1)][10-I=ST-161-m01]
9ms-is-0100What is the code for Advanced Programming?felix_playground_SQA_Training/MS_IS_all_module...[(9, 1)][10-I=APR-182-m01]
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" + ], + "text/plain": [ + " id annotator position \\\n", + "0 ms-is-01 0 0 \n", + "1 ms-is-01 0 0 \n", + "2 ms-is-01 0 0 \n", + "3 ms-is-01 0 0 \n", + "4 ms-is-01 0 0 \n", + "5 ms-is-01 0 0 \n", + "6 ms-is-01 0 0 \n", + "7 ms-is-01 0 0 \n", + "8 ms-is-01 0 0 \n", + "9 ms-is-01 0 0 \n", + "\n", + " question \\\n", + "0 What is the abbreviation of the module Informa... \n", + "1 What is the ID of IT-Management? \n", + "2 What is the abbreviation of Project Seminar? \n", + "3 What is the code for Information Retrieval? \n", + "4 What is the abbreviation of the module Analysi... \n", + "5 What is the code for Security of Software Syst... \n", + "6 What is the ID of Software Architecture? \n", + "7 What is the abbreviation of the module Artific... \n", + "8 What is the abbreviation of Discrete Event Sim... \n", + "9 What is the code for Advanced Programming? \n", + "\n", + " table_file answer_coordinates \\\n", + "0 felix_playground_SQA_Training/MS_IS_all_module... [(0, 1)] \n", + "1 felix_playground_SQA_Training/MS_IS_all_module... [(1, 1)] \n", + "2 felix_playground_SQA_Training/MS_IS_all_module... [(2, 1)] \n", + "3 felix_playground_SQA_Training/MS_IS_all_module... [(3, 1)] \n", + "4 felix_playground_SQA_Training/MS_IS_all_module... [(4, 1)] \n", + "5 felix_playground_SQA_Training/MS_IS_all_module... [(5, 1)] \n", + "6 felix_playground_SQA_Training/MS_IS_all_module... [(6, 1)] \n", + "7 felix_playground_SQA_Training/MS_IS_all_module... [(7, 1)] \n", + "8 felix_playground_SQA_Training/MS_IS_all_module... [(8, 1)] \n", + "9 felix_playground_SQA_Training/MS_IS_all_module... [(9, 1)] \n", + "\n", + " answer_text \n", + "0 [12-IV-161-m01] \n", + "1 [12-M-ITM-161-m01] \n", + "2 [12-PS-192-m01] \n", + "3 [10-I=IR-161-m01] \n", + "4 [10-I=PA-161-m01] \n", + "5 [10-I=SSS-172-m01] \n", + "6 [10-I=SAR-161-m01] \n", + "7 [10-I=KI1-161-m01] \n", + "8 [10-I=ST-161-m01] \n", + "9 [10-I=APR-182-m01] " + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import ast\n", + "\n", + "def _parse_answer_coordinates(answer_coordinate_str):\n", + " \"\"\"Parses the answer_coordinates of a question.\n", + " Args:\n", + " answer_coordinate_str: A string representation of a Python list of tuple\n", + " strings.\n", + " For example: \"['(1, 4)','(1, 3)', ...]\"\n", + " \"\"\"\n", + "\n", + " try:\n", + " answer_coordinates = []\n", + " # make a list of strings\n", + " coords = ast.literal_eval(answer_coordinate_str)\n", + " # parse each string as a tuple\n", + " for row_index, column_index in sorted(\n", + " ast.literal_eval(coord) for coord in coords):\n", + " answer_coordinates.append((row_index, column_index))\n", + " except SyntaxError:\n", + " raise ValueError('Unable to evaluate %s' % answer_coordinate_str)\n", + " \n", + " return answer_coordinates\n", + "\n", + "\n", + "def _parse_answer_text(answer_text):\n", + " \"\"\"Populates the answer_texts field of `answer` by parsing `answer_text`.\n", + " Args:\n", + " answer_text: A string representation of a Python list of strings.\n", + " For example: \"[u'test', u'hello', ...]\"\n", + " answer: an Answer object.\n", + " \"\"\"\n", + " try:\n", + " answer = []\n", + " for value in ast.literal_eval(answer_text):\n", + " answer.append(value)\n", + " except SyntaxError:\n", + " raise ValueError('Unable to evaluate %s' % answer_text)\n", + "\n", + " return answer\n", + "\n", + "sqa_data['answer_coordinates'] = sqa_data['answer_coordinates'].apply(lambda coords_str: _parse_answer_coordinates(coords_str))\n", + "sqa_data['answer_text'] = sqa_data['answer_text'].apply(lambda txt: _parse_answer_text(txt))\n", + "\n", + "sqa_data.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idannotatorpositionquestiontable_fileanswer_coordinatesanswer_textsequence_id
0ms-is-0100What is the abbreviation of the module Informa...felix_playground_SQA_Training/MS_IS_all_module...[(0, 1)][12-IV-161-m01]ms-is-01-0
1ms-is-0100What is the ID of IT-Management?felix_playground_SQA_Training/MS_IS_all_module...[(1, 1)][12-M-ITM-161-m01]ms-is-01-0
2ms-is-0100What is the abbreviation of Project Seminar?felix_playground_SQA_Training/MS_IS_all_module...[(2, 1)][12-PS-192-m01]ms-is-01-0
3ms-is-0100What is the code for Information Retrieval?felix_playground_SQA_Training/MS_IS_all_module...[(3, 1)][10-I=IR-161-m01]ms-is-01-0
4ms-is-0100What is the abbreviation of the module Analysi...felix_playground_SQA_Training/MS_IS_all_module...[(4, 1)][10-I=PA-161-m01]ms-is-01-0
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" + ], + "text/plain": [ + " id annotator position \\\n", + "0 ms-is-01 0 0 \n", + "1 ms-is-01 0 0 \n", + "2 ms-is-01 0 0 \n", + "3 ms-is-01 0 0 \n", + "4 ms-is-01 0 0 \n", + "\n", + " question \\\n", + "0 What is the abbreviation of the module Informa... \n", + "1 What is the ID of IT-Management? \n", + "2 What is the abbreviation of Project Seminar? \n", + "3 What is the code for Information Retrieval? \n", + "4 What is the abbreviation of the module Analysi... \n", + "\n", + " table_file answer_coordinates \\\n", + "0 felix_playground_SQA_Training/MS_IS_all_module... [(0, 1)] \n", + "1 felix_playground_SQA_Training/MS_IS_all_module... [(1, 1)] \n", + "2 felix_playground_SQA_Training/MS_IS_all_module... [(2, 1)] \n", + "3 felix_playground_SQA_Training/MS_IS_all_module... [(3, 1)] \n", + "4 felix_playground_SQA_Training/MS_IS_all_module... [(4, 1)] \n", + "\n", + " answer_text sequence_id \n", + "0 [12-IV-161-m01] ms-is-01-0 \n", + "1 [12-M-ITM-161-m01] ms-is-01-0 \n", + "2 [12-PS-192-m01] ms-is-01-0 \n", + "3 [10-I=IR-161-m01] ms-is-01-0 \n", + "4 [10-I=PA-161-m01] ms-is-01-0 " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def get_sequence_id(example_id, annotator):\n", + " if \"-\" in str(annotator):\n", + " raise ValueError('\"-\" not allowed in annotator.')\n", + " return f\"{example_id}-{annotator}\"\n", + "\n", + "sqa_data['sequence_id'] = sqa_data.apply(lambda x: get_sequence_id(x.id, x.annotator), axis=1)\n", + "sqa_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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questiontable_fileanswer_coordinatesanswer_text
sequence_id
ms-is-01-0[What is the abbreviation of the module Inform...felix_playground_SQA_Training/MS_IS_all_module...[[(0, 1)], [(1, 1)], [(2, 1)], [(3, 1)], [(4, ...[[12-IV-161-m01], [12-M-ITM-161-m01], [12-PS-1...
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" + ], + "text/plain": [ + " question \\\n", + "sequence_id \n", + "ms-is-01-0 [What is the abbreviation of the module Inform... \n", + "\n", + " table_file \\\n", + "sequence_id \n", + "ms-is-01-0 felix_playground_SQA_Training/MS_IS_all_module... \n", + "\n", + " answer_coordinates \\\n", + "sequence_id \n", + "ms-is-01-0 [[(0, 1)], [(1, 1)], [(2, 1)], [(3, 1)], [(4, ... \n", + "\n", + " answer_text \n", + "sequence_id \n", + "ms-is-01-0 [[12-IV-161-m01], [12-M-ITM-161-m01], [12-PS-1... " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# let's group table-question pairs by sequence id, and remove some columns we don't need \n", + "grouped = sqa_data.groupby(by='sequence_id').agg(lambda x: x.tolist())\n", + "grouped = grouped.drop(columns=['id', 'annotator', 'position'])\n", + "grouped['table_file'] = grouped['table_file'].apply(lambda x: x[0])\n", + "grouped.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Module titleAbbreviationModule coordinatorModule offered byETCSMethod of gradingDurationModule levelContentsIntended learning outcomesCoursesMethod of assessmentAllocation of placesAdditional informationWorkloadTeaching cycleReferred to in LPO I
0Information Processing within Organizations12-IV-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduateContent:This course provides students with an ...After completing the course \"Integrated Inform...V (2) + Ü (2)written examination (approx. 60 minutes)Langua...----150 h----
1IT-Management12-M-ITM-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Information Systems Eng...5numerical grade1 semestergraduateContent:This course provides students with an ...After completing the course \"IT Management\", s...V (2) + Ü (2)a) written examination (approx. 60 minutes) or...----150 h----
2Project Seminar12-PS-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...15numerical grade1 semestergraduateContent:In small project teams of 4 to 10 memb...After completing the course \"Projektseminar\", ...S (2)project: preparing a conceptual design (approx...----450 h----
3Information Retrieval10-I=IR-161-m01Institute of Computer ScienceDean of Studies Informatik (Computer Science)5numerical grade1 semestergraduateIR models (e. g. Boolean and vector space mode...The students possess theoretical and practical...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
4Analysis and Design of Programs10-I=PA-161-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduateProgram analysis, model creation in software e...The students are able to analyse programs, to ...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
......................................................
115Vertical Storytelling12-M-VS-221-m01Faculty of Business Management and Economicsnan10numerical grade1 semesternan----S (2)portfolio (approx. 5 pages)Assessment offered:...----300 h----
116Organizational Economics and Digital Transform...12-M-OEDT-231-m01Faculty of Business Management and Economicsnan5numerical grade1 semesternan----V (2) + Ü (2)Module taught in: Englisha) written examination (approx. 60 minutes) or...----150 h----
117Policy Evaluation Methods12-M-PEM-182-m01Faculty of Business Management and EconomicsHolder of the Chair of Labor Economics5numerical grade1 semestergraduateThis course offers an introduction to the fund...At the end of the course, students should be a...V (2) + Ü (2)Module taught in: Englisha) written examination (approx. 60 minutes) or...--Research track module in Masters programme IEP150 h----
118Topics in Empirical Economics12-M-TE-231-m01Faculty of Business Management and Economicsnan5numerical grade1 semesternan----V (2) + Ü (2)Module taught in: Englishportfolio (approx. 50 hours)Prüfungssprache: E...12 *WA1(1) Should the number of applications e...--150 h----
119Master Thesis Information Systems12-WI-MA-192-m01Faculty of Business Management and EconomicsDean of the Faculty of Business Management and...30numerical grade1 semestergraduateStudents will complete their degree with a Mas...In the master thesis students prove that they ...--Masters thesis (approx. 60 to 80 pages)Languag...--Time to complete: 6 months900 h----
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Boolean and vector space mode... \n", + "4 Program analysis, model creation in software e... \n", + ".. ... \n", + "115 -- \n", + "116 -- \n", + "117 This course offers an introduction to the fund... \n", + "118 -- \n", + "119 Students will complete their degree with a Mas... \n", + "\n", + " Intended learning outcomes \\\n", + "0 After completing the course \"Integrated Inform... \n", + "1 After completing the course \"IT Management\", s... \n", + "2 After completing the course \"Projektseminar\", ... \n", + "3 The students possess theoretical and practical... \n", + "4 The students are able to analyse programs, to ... \n", + ".. ... \n", + "115 -- \n", + "116 -- \n", + "117 At the end of the course, students should be a... \n", + "118 -- \n", + "119 In the master thesis students prove that they ... \n", + "\n", + " Courses \\\n", + "0 V (2) + Ü (2) \n", + "1 V (2) + Ü (2) \n", + "2 S (2) \n", + "3 V (2) + Ü (2) \n", + "4 V (2) + Ü (2) \n", + ".. ... \n", + "115 S (2) \n", + "116 V (2) + Ü (2)Module taught in: English \n", + "117 V (2) + Ü (2)Module taught in: English \n", + "118 V (2) + Ü (2)Module taught in: English \n", + "119 -- \n", + "\n", + " Method of assessment \\\n", + "0 written examination (approx. 60 minutes)Langua... \n", + "1 a) written examination (approx. 60 minutes) or... \n", + "2 project: preparing a conceptual design (approx... \n", + "3 written examination (approx. 60 to 120 minutes... \n", + "4 written examination (approx. 60 to 120 minutes... \n", + ".. ... \n", + "115 portfolio (approx. 5 pages)Assessment offered:... \n", + "116 a) written examination (approx. 60 minutes) or... \n", + "117 a) written examination (approx. 60 minutes) or... \n", + "118 portfolio (approx. 50 hours)Prüfungssprache: E... \n", + "119 Masters thesis (approx. 60 to 80 pages)Languag... \n", + "\n", + " Allocation of places \\\n", + "0 -- \n", + "1 -- \n", + "2 -- \n", + "3 -- \n", + "4 -- \n", + ".. ... \n", + "115 -- \n", + "116 -- \n", + "117 -- \n", + "118 12 *WA1(1) Should the number of applications e... \n", + "119 -- \n", + "\n", + " Additional information Workload \\\n", + "0 -- 150 h \n", + "1 -- 150 h \n", + "2 -- 450 h \n", + "3 Focuses available for students of the Masters ... 150 h \n", + "4 Focuses available for students of the Masters ... 150 h \n", + ".. ... ... \n", + "115 -- 300 h \n", + "116 -- 150 h \n", + "117 Research track module in Masters programme IEP 150 h \n", + "118 -- 150 h \n", + "119 Time to complete: 6 months 900 h \n", + "\n", + " Teaching cycle Referred to in LPO I \n", + "0 -- -- \n", + "1 -- -- \n", + "2 -- -- \n", + "3 -- -- \n", + "4 -- -- \n", + ".. ... ... \n", + "115 -- -- \n", + "116 -- -- \n", + "117 -- -- \n", + "118 -- -- \n", + "119 -- -- \n", + "\n", + "[120 rows x 17 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "['What is the abbreviation of the module Information Processing within Organizations?', 'What is the ID of IT-Management?', 'What is the abbreviation of Project Seminar?', 'What is the code for Information Retrieval?', 'What is the abbreviation of the module Analysis and Design of Programs?', 'What is the code for Security of Software Systems?', 'What is the ID of Software Architecture?', 'What is the abbreviation of the module Artificial Intelligence 1?', 'What is the abbreviation of Discrete Event Simulation?', 'What is the code for Advanced Programming?', 'What is the code for Programming with neural nets?', 'What is the abbreviation of the module NLP and Text Mining?', 'What is the code for Systems Benchmarking?', 'What is the code for Computer Vision?', 'What is the abbreviation of Image Processing and Computational Photography?', 'What is the abbreviation of the module Multilingual NLP?']\n" + ] + } + ], + "source": [ + "# path to the directory containing all csv files\n", + "table_csv_path = \"table_csv\"\n", + "\n", + "item = grouped.iloc[0]\n", + "table = pd.read_csv(\"table_csv/MS_IS_all_modules_orginal_cleaned.csv\").astype(str) \n", + "\n", + "display(table)\n", + "print(\"\")\n", + "print(item.question)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "from transformers import TapasTokenizer\n", + "# initialize the tokenizer\n", + "tokenizer = TapasTokenizer.from_pretrained(\"google/tapas-base\")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['input_ids', 'labels', 'numeric_values', 'numeric_values_scale', 'token_type_ids', 'attention_mask'])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "encoding = tokenizer(table=table, queries=item.question, answer_coordinates=item.answer_coordinates, answer_text=item.answer_text,\n", + " truncation=True, padding=\"max_length\", return_tensors=\"pt\")\n", + "encoding.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] what is the abbreviation of the module information processing within organizations? [SEP] module abbreviation module module etcs method duration module contents intended courses method allocation additional workload teaching referred information 12 faculty holder 5 numerical 1 graduate content after v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] it 12 faculty holder 5 numerical 1 graduate content after v a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] project 12 faculty holder 15 numerical 1 graduate content after s project [EMPTY] [EMPTY] 450 [EMPTY] [EMPTY] information 10 institute dean 5 numerical 1 graduate ir the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] analysis 10 institute holder 5 numerical 1 graduate program the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] security 10 institute holder 5 numerical 1 graduate the students v written [EMPTY] focuses 150 [EMPTY] [EMPTY] software 10 institute holder 5 numerical 1 graduate current the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] artificial 10 institute holder 5 numerical 1 graduate intelligent the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] discrete 10 institute holder 8 numerical 1 graduate introduction the v written [EMPTY] focuses 240 [EMPTY] [EMPTY] advanced 10 institute holder 5 numerical 1 graduate with students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] programming 10 institute holder 5 numerical 1 graduate overview knowledge v written [EMPTY] focuses 150 [EMPTY] [EMPTY] nlp 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] systems 10 institute holder 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] computer 10 institute dean 5 numerical 1 graduate the students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] image 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] multilingual 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] statistical 10 institute holder 5 numerical 1 graduate networks the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] operations 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] machine 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] data 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] advanced 12 faculty holder 10 numerical 1 graduate in after s term 20 [EMPTY] 300 [EMPTY] [EMPTY] decision 12 faculty holder 5 numerical 1 graduate the after v a 40 [EMPTY] 150 [EMPTY] [EMPTY] analytical 12 faculty holder 5 numerical 1 graduate the the v written 40 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 10 numerical 1 graduate in the s term 20 [EMPTY] 300 [EMPTY] [EMPTY] e 12 faculty holder 5 numerical 1 graduate the - v a 40 [EMPTY] 150 [EMPTY] [EMPTY] mobile 12 faculty holder 5 numerical 1 graduate the - u a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY]'" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(encoding[\"input_ids\"][0])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['12-IV-161-m01']\n" + ] + } + ], + "source": [ + "print(item.answer_text[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[CLS] 0\n", + "what 0\n", + "is 0\n", + "the 0\n", + "id 0\n", + "of 0\n", + "it 0\n", + "- 0\n", + "management 0\n", + "? 0\n", + "[SEP] 0\n", + "module 0\n", + "abbreviation 0\n", + "module 0\n", + "module 0\n", + "etc 0\n", + "##s 0\n", + "method 0\n", + "duration 0\n", + "module 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tokenizer\n", + "\n", + " def __getitem__(self, idx):\n", + " item = self.df.iloc[idx]\n", + " table = pd.read_csv(\"table_csv/MS_IS_all_modules_orginal_cleaned.csv\").astype(str) # TapasTokenizer expects the table data to be text only\n", + " if item.position != 0:\n", + " # use the previous table-question pair to correctly set the prev_labels token type ids\n", + " previous_item = self.df.iloc[idx-1]\n", + " encoding = self.tokenizer(table=table, \n", + " queries=[previous_item.question, item.question], \n", + " answer_coordinates=[previous_item.answer_coordinates, item.answer_coordinates], \n", + " answer_text=[previous_item.answer_text, item.answer_text],\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " # use encodings of second table-question pair in the batch\n", + " encoding = {key: val[-1] for key, val in encoding.items()}\n", + " else:\n", + " # this means it's the first table-question pair in a sequence\n", + " encoding = self.tokenizer(table=table, \n", + " queries=item.question, \n", + " answer_coordinates=item.answer_coordinates, \n", + " answer_text=item.answer_text,\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " # remove the batch dimension which the tokenizer adds \n", + " encoding = {key: val.squeeze(0) for key, val in encoding.items()}\n", + " return encoding\n", + "\n", + " def __len__(self):\n", + " return len(self.df)\n", + "\n", + "train_dataset = TableDataset(df=sqa_data, tokenizer=tokenizer)\n", + "train_dataloader = torch.utils.data.DataLoader(train_dataset, batch_size=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([512, 7])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train_dataset[0][\"token_type_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "batch = next(iter(train_dataloader))" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 512])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "batch[\"input_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 512, 7])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "batch[\"token_type_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] what is the abbreviation of the module information processing within organizations? [SEP] module abbreviation module module etcs method duration module contents intended courses method allocation additional workload teaching referred information 12 faculty holder 5 numerical 1 graduate content after v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] it 12 faculty holder 5 numerical 1 graduate content after v a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] project 12 faculty holder 15 numerical 1 graduate content after s project [EMPTY] [EMPTY] 450 [EMPTY] [EMPTY] information 10 institute dean 5 numerical 1 graduate ir the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] analysis 10 institute holder 5 numerical 1 graduate program the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] security 10 institute holder 5 numerical 1 graduate the students v written [EMPTY] focuses 150 [EMPTY] [EMPTY] software 10 institute holder 5 numerical 1 graduate current the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] artificial 10 institute holder 5 numerical 1 graduate intelligent the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] discrete 10 institute holder 8 numerical 1 graduate introduction the v written [EMPTY] focuses 240 [EMPTY] [EMPTY] advanced 10 institute holder 5 numerical 1 graduate with students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] programming 10 institute holder 5 numerical 1 graduate overview knowledge v written [EMPTY] focuses 150 [EMPTY] [EMPTY] nlp 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] systems 10 institute holder 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] computer 10 institute dean 5 numerical 1 graduate the students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] image 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] multilingual 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] statistical 10 institute holder 5 numerical 1 graduate networks the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] operations 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] machine 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] data 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] advanced 12 faculty holder 10 numerical 1 graduate in after s term 20 [EMPTY] 300 [EMPTY] [EMPTY] decision 12 faculty holder 5 numerical 1 graduate the after v a 40 [EMPTY] 150 [EMPTY] [EMPTY] analytical 12 faculty holder 5 numerical 1 graduate the the v written 40 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 10 numerical 1 graduate in the s term 20 [EMPTY] 300 [EMPTY] [EMPTY] e 12 faculty holder 5 numerical 1 graduate the - v a 40 [EMPTY] 150 [EMPTY] [EMPTY] mobile 12 faculty holder 5 numerical 1 graduate the - u a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY]'" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(batch[\"input_ids\"][0])" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "#first example should not have any prev_labels set\n", + "assert batch[\"token_type_ids\"][0][:,3].sum() == 0" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] what is the id of it - management? [SEP] module abbreviation module module etcs method duration module contents intended courses method allocation additional workload teaching referred information 12 faculty holder 5 numerical 1 graduate content after v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] it 12 faculty holder 5 numerical 1 graduate content after v a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] project 12 faculty holder 15 numerical 1 graduate content after s project [EMPTY] [EMPTY] 450 [EMPTY] [EMPTY] information 10 institute dean 5 numerical 1 graduate ir the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] analysis 10 institute holder 5 numerical 1 graduate program the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] security 10 institute holder 5 numerical 1 graduate the students v written [EMPTY] focuses 150 [EMPTY] [EMPTY] software 10 institute holder 5 numerical 1 graduate current the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] artificial 10 institute holder 5 numerical 1 graduate intelligent the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] discrete 10 institute holder 8 numerical 1 graduate introduction the v written [EMPTY] focuses 240 [EMPTY] [EMPTY] advanced 10 institute holder 5 numerical 1 graduate with students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] programming 10 institute holder 5 numerical 1 graduate overview knowledge v written [EMPTY] focuses 150 [EMPTY] [EMPTY] nlp 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] systems 10 institute holder 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] computer 10 institute dean 5 numerical 1 graduate the students v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] image 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] multilingual 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] statistical 10 institute holder 5 numerical 1 graduate networks the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] operations 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] machine 10 institute [EMPTY] 5 numerical 1 [EMPTY] [EMPTY] [EMPTY] v written [EMPTY] focuses 150 [EMPTY] [EMPTY] data 10 institute holder 5 numerical 1 graduate foundations the v written [EMPTY] focuses 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 5 numerical 1 graduate content after v a 20 [EMPTY] 150 [EMPTY] [EMPTY] advanced 12 faculty holder 10 numerical 1 graduate in after s term 20 [EMPTY] 300 [EMPTY] [EMPTY] decision 12 faculty holder 5 numerical 1 graduate the after v a 40 [EMPTY] 150 [EMPTY] [EMPTY] analytical 12 faculty holder 5 numerical 1 graduate the the v written 40 [EMPTY] 150 [EMPTY] [EMPTY] business 12 faculty holder 10 numerical 1 graduate in the s term 20 [EMPTY] 300 [EMPTY] [EMPTY] e 12 faculty holder 5 numerical 1 graduate the - v a 40 [EMPTY] 150 [EMPTY] [EMPTY] mobile 12 faculty holder 5 numerical 1 graduate the - u a [EMPTY] [EMPTY] 150 [EMPTY] [EMPTY] [PAD] [PAD] [PAD]'" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(batch[\"input_ids\"][1])" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[CLS] 0\n", + "what 0\n", + "is 0\n", + "the 0\n", + "id 0\n", + "of 0\n", + "it 0\n", + "- 0\n", + "management 0\n", + "? 0\n", + "[SEP] 0\n", + "module 0\n", + "abbreviation 0\n", + "module 0\n", + "module 0\n", + "etc 0\n", + "##s 0\n", + "method 0\n", + "duration 0\n", + "module 0\n", + "contents 0\n", + "intended 0\n", + "courses 0\n", + "method 0\n", + "allocation 0\n", + "additional 0\n", + "work 0\n", + "##load 0\n", + "teaching 0\n", + "referred 0\n", + "information 0\n", + "12 0\n", + "faculty 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}, + { + "data": { + "text/plain": [ + "TapasForQuestionAnswering(\n", + " (tapas): TapasModel(\n", + " (embeddings): TapasEmbeddings(\n", + " (word_embeddings): Embedding(30522, 768, padding_idx=0)\n", + " (position_embeddings): Embedding(1024, 768)\n", + " (token_type_embeddings_0): Embedding(3, 768)\n", + " (token_type_embeddings_1): Embedding(256, 768)\n", + " (token_type_embeddings_2): Embedding(256, 768)\n", + " (token_type_embeddings_3): Embedding(2, 768)\n", + " (token_type_embeddings_4): Embedding(256, 768)\n", + " (token_type_embeddings_5): Embedding(256, 768)\n", + " (token_type_embeddings_6): Embedding(10, 768)\n", + " (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n", + " (dropout): Dropout(p=0.07, inplace=False)\n", + " )\n", + " (encoder): TapasEncoder(\n", + " (layer): ModuleList(\n", + " (0-11): 12 x TapasLayer(\n", + " (attention): TapasAttention(\n", + " (self): TapasSelfAttention(\n", + " (query): Linear(in_features=768, out_features=768, bias=True)\n", + " (key): Linear(in_features=768, out_features=768, bias=True)\n", + " (value): Linear(in_features=768, out_features=768, bias=True)\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " )\n", + " (output): TapasSelfOutput(\n", + " (dense): Linear(in_features=768, out_features=768, bias=True)\n", + " (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n", + " (dropout): Dropout(p=0.07, inplace=False)\n", + " )\n", + " )\n", + " (intermediate): TapasIntermediate(\n", + " (dense): Linear(in_features=768, out_features=3072, bias=True)\n", + " (intermediate_act_fn): GELUActivation()\n", + " )\n", + " (output): TapasOutput(\n", + " (dense): Linear(in_features=3072, out_features=768, bias=True)\n", + " (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n", + " (dropout): Dropout(p=0.07, inplace=False)\n", + " )\n", + " )\n", + " )\n", + " )\n", + " (pooler): TapasPooler(\n", + " (dense): Linear(in_features=768, out_features=768, bias=True)\n", + " (activation): Tanh()\n", + " )\n", + " )\n", + " (dropout): Dropout(p=0.07, inplace=False)\n", + ")" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from transformers import TapasForQuestionAnswering\n", + "\n", + "model = TapasForQuestionAnswering.from_pretrained(\"google/tapas-base\")\n", + "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", + "\n", + "model.to(device)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\FelixNeubauer\\anaconda3\\envs\\py38\\lib\\site-packages\\transformers\\optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0\n", + "Loss: 3.656862497329712\n", + "Loss: 2.2393763065338135\n", + "Loss: 1.0310397148132324\n", + "Loss: 0.40564000606536865\n", + "Loss: 0.27754873037338257\n", + "Loss: 0.2089463472366333\n", + "Loss: 0.18136566877365112\n", + "Loss: 0.16886121034622192\n", + "Epoch: 1\n", + "Loss: 0.15656918287277222\n", + "Loss: 0.1554507166147232\n", + "Loss: 0.1592925786972046\n", + "Loss: 0.15718212723731995\n", + "Loss: 0.1562442183494568\n", + "Loss: 0.15801993012428284\n", + "Loss: 0.15340173244476318\n", + "Loss: 0.1572810709476471\n", + "Epoch: 2\n", + "Loss: 0.14915084838867188\n", + "Loss: 0.14941248297691345\n", + "Loss: 0.1528778076171875\n", + "Loss: 0.1508742719888687\n", + "Loss: 0.1506081521511078\n", + "Loss: 0.15169525146484375\n", + "Loss: 0.14878258109092712\n", + "Loss: 0.15179219841957092\n", + "Epoch: 3\n", + "Loss: 0.14902304112911224\n", + "Loss: 0.14820906519889832\n", + "Loss: 0.14895713329315186\n", + "Loss: 0.14678704738616943\n", + "Loss: 0.14645236730575562\n", + "Loss: 0.14753571152687073\n", + "Loss: 0.14482052624225616\n", + "Loss: 0.14703711867332458\n", + "Epoch: 4\n", + "Loss: 0.1496383100748062\n", + "Loss: 0.14670369029045105\n", + "Loss: 0.14437901973724365\n", + "Loss: 0.14174023270606995\n", + "Loss: 0.14217612147331238\n", + "Loss: 0.1428726762533188\n", + "Loss: 0.14048904180526733\n", + "Loss: 0.14207255840301514\n" + ] + } + ], + "source": [ + "from transformers import AdamW\n", + "\n", + "optimizer = AdamW(model.parameters(), lr=5e-5)\n", + "\n", + "for epoch in range(5): # loop over the dataset multiple times\n", + " print(\"Epoch:\", epoch)\n", + " for idx, batch in enumerate(train_dataloader):\n", + " # get the inputs;\n", + " input_ids = batch[\"input_ids\"].to(device)\n", + " attention_mask = batch[\"attention_mask\"].to(device)\n", + " token_type_ids = batch[\"token_type_ids\"].to(device)\n", + " labels = batch[\"labels\"].to(device)\n", + " \n", + " # zero the parameter gradients\n", + " optimizer.zero_grad()\n", + " # forward + backward + optimize\n", + " outputs = model(input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids,\n", + " labels=labels)\n", + " loss = outputs.loss\n", + " print(\"Loss:\", loss.item())\n", + " loss.backward()\n", + " optimizer.step()" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "import collections\n", + "import numpy as np\n", + "\n", + "def compute_prediction_sequence(model, data, device):\n", + " \"\"\"Computes predictions using model's answers to the previous questions.\"\"\"\n", + " \n", + " # prepare data\n", + " input_ids = data[\"input_ids\"].to(device)\n", + " attention_mask = data[\"attention_mask\"].to(device)\n", + " token_type_ids = data[\"token_type_ids\"].to(device)\n", + "\n", + " all_logits = []\n", + " prev_answers = None\n", + "\n", + " num_batch = data[\"input_ids\"].shape[0]\n", + " \n", + " for idx in range(num_batch):\n", + " \n", + " if prev_answers is not None:\n", + " coords_to_answer = prev_answers[idx]\n", + " # Next, set the label ids predicted by the model\n", + " prev_label_ids_example = token_type_ids_example[:,3] # shape (seq_len,)\n", + " model_label_ids = np.zeros_like(prev_label_ids_example.cpu().numpy()) # shape (seq_len,)\n", + "\n", + " # for each token in the sequence:\n", + " token_type_ids_example = token_type_ids[idx] # shape (seq_len, 7)\n", + " for i in range(model_label_ids.shape[0]):\n", + " segment_id = token_type_ids_example[:,0].tolist()[i]\n", + " col_id = token_type_ids_example[:,1].tolist()[i] - 1\n", + " row_id = token_type_ids_example[:,2].tolist()[i] - 1\n", + " if row_id >= 0 and col_id >= 0 and segment_id == 1:\n", + " model_label_ids[i] = int(coords_to_answer[(col_id, row_id)])\n", + "\n", + " # set the prev label ids of the example (shape (1, seq_len) )\n", + " token_type_ids_example[:,3] = torch.from_numpy(model_label_ids).type(torch.long).to(device) \n", + "\n", + " prev_answers = {}\n", + " # get the example\n", + " input_ids_example = input_ids[idx] # shape (seq_len,)\n", + " attention_mask_example = attention_mask[idx] # shape (seq_len,)\n", + " token_type_ids_example = token_type_ids[idx] # shape (seq_len, 7)\n", + " # forward pass to obtain the logits\n", + " outputs = model(input_ids=input_ids_example.unsqueeze(0), \n", + " attention_mask=attention_mask_example.unsqueeze(0), \n", + " token_type_ids=token_type_ids_example.unsqueeze(0))\n", + " logits = outputs.logits\n", + " all_logits.append(logits)\n", + "\n", + " # convert logits to probabilities (which are of shape (1, seq_len))\n", + " dist_per_token = torch.distributions.Bernoulli(logits=logits)\n", + " probabilities = dist_per_token.probs * attention_mask_example.type(torch.float32).to(dist_per_token.probs.device) \n", + "\n", + " # Compute average probability per cell, aggregating over tokens.\n", + " # Dictionary maps coordinates to a list of one or more probabilities\n", + " coords_to_probs = collections.defaultdict(list)\n", + " prev_answers = {}\n", + " for i, p in enumerate(probabilities.squeeze().tolist()):\n", + " segment_id = token_type_ids_example[:,0].tolist()[i]\n", + " col = token_type_ids_example[:,1].tolist()[i] - 1\n", + " row = token_type_ids_example[:,2].tolist()[i] - 1\n", + " if col >= 0 and row >= 0 and segment_id == 1:\n", + " coords_to_probs[(col, row)].append(p)\n", + "\n", + " # Next, map cell coordinates to 1 or 0 (depending on whether the mean prob of all cell tokens is > 0.5)\n", + " coords_to_answer = {}\n", + " for key in coords_to_probs:\n", + " coords_to_answer[key] = np.array(coords_to_probs[key]).mean() > 0.5\n", + " prev_answers[idx+1] = coords_to_answer\n", + " \n", + " logits_batch = torch.cat(tuple(all_logits), 0)\n", + " \n", + " return logits_batch" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "queries = [\"What is the abbreviation of the module Information Processing within Organizations?\"]\n", + "\n", + "table = pd.read_csv(\"MS_IS_all_modules_orginal_15_rows_cleaned.csv\")\n", + "table = table.astype(str)\n", + "\n", + "inputs = tokenizer(table=table, queries=queries, padding='max_length', return_tensors=\"pt\", Truncation=True)\n", + "logits = compute_prediction_sequence(model, inputs, device)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "predicted_answer_coordinates, = tokenizer.convert_logits_to_predictions(inputs, logits.cpu().detach())" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Module titleAbbreviationModule coordinatorModule offered byETCSMethod of gradingDurationModule levelContentsIntended learning outcomesCoursesMethod of assessmentAllocation of placesAdditional informationWorkloadTeaching cycleReferred to in LPO I
0Information Processing within Organizations12-IV-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduateContent:This course provides students with an ...After completing the course \"Integrated Inform...V (2) + Ü (2)written examination (approx. 60 minutes)Langua...----150 h----
1IT-Management12-M-ITM-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Information Systems Eng...5numerical grade1 semestergraduateContent:This course provides students with an ...After completing the course \"IT Management\", s...V (2) + Ü (2)a) written examination (approx. 60 minutes) or...----150 h----
2Project Seminar12-PS-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...15numerical grade1 semestergraduateContent:In small project teams of 4 to 10 memb...After completing the course \"Projektseminar\", ...S (2)project: preparing a conceptual design (approx...----450 h----
3Information Retrieval10-I=IR-161-m01Institute of Computer ScienceDean of Studies Informatik (Computer Science)5numerical grade1 semestergraduateIR models (e. g. Boolean and vector space mode...The students possess theoretical and practical...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
4Analysis and Design of Programs10-I=PA-161-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduateProgram analysis, model creation in software e...The students are able to analyse programs, to ...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
5Security of Software Systems10-I=SSS-172-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduateThe lecture provides an overview of common sof...Students gain a deep understanding of software...V (2) + Ü (2)Module taught in: Englishwritten examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
6Software Architecture10-I=SAR-161-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduateCurrent topics in the area of aerospace.The students possess a fundamental and applica...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
7Artificial Intelligence 110-I=KI1-161-m01Institute of Computer Scienceholder of the Chair of Computer Science VI5numerical grade1 semestergraduateIntelligent agents, uninformed and heuristic s...The students possess theoretical and practical...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
8Discrete Event Simulation10-I=ST-161-m01Institute of Computer Scienceholder of the Chair of Computer Science III8numerical grade1 semestergraduateIntroduction to simulation techniques, statist...The students possess the methodic knowledge an...V (4) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...240 h----
9Advanced Programming10-I=APR-182-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduateWith the knowledge of basic programming, taugh...Students learn advanced programming paradigms ...V (2) + Ü (2)Module taught in: Englishwritten examination (90 to 120 minutes)Languag...----150 h----
10Programming with neural nets10-I=PNN-212-m01Institute of Computer Scienceholder of the Chair of Computer Science IX5numerical grade1 semestergraduateOverview over NN, implementation of important ...Knowledge about possible applications and limi...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
11NLP and Text Mining10-I=STM-162-m01Institute of Computer Scienceholder of the Chair of Computer Science VI5numerical grade1 semestergraduateFoundations in the following areas: definition...The students possess theoretical and practical...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
12Systems Benchmarking10-I=SB-212-m01Institute of Computer Scienceholder of the Chair of Computer Science IX5numerical grade1 semesternan----V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
13Computer Vision10-xtAI=CV-202-m01Institute of Computer ScienceDean of Studies Informatik (Computer Science)5numerical grade1 semestergraduateThe lecture provides knowledge about current m...Students have fundamental knowledge of problem...V (2) + Ü (2)Module taught in: EnglishWritten examination (approx. 60 to 120 minutes...----150 h----
14Image Processing and Computational Photography10-I=IP-222-m01Institute of Computer Sciencenan5numerical grade1 semesternan----V (2) + Ü (2)Module taught in: Englishwritten examination (approx. 60 to 120 minutes...----150 h----
\n", + "
" + ], + "text/plain": [ + " Module title Abbreviation \\\n", + "0 Information Processing within Organizations 12-IV-161-m01 \n", + "1 IT-Management 12-M-ITM-161-m01 \n", + "2 Project Seminar 12-PS-192-m01 \n", + "3 Information Retrieval 10-I=IR-161-m01 \n", + "4 Analysis and Design of Programs 10-I=PA-161-m01 \n", + "5 Security of Software Systems 10-I=SSS-172-m01 \n", + "6 Software Architecture 10-I=SAR-161-m01 \n", + "7 Artificial Intelligence 1 10-I=KI1-161-m01 \n", + "8 Discrete Event Simulation 10-I=ST-161-m01 \n", + "9 Advanced Programming 10-I=APR-182-m01 \n", + "10 Programming with neural nets 10-I=PNN-212-m01 \n", + "11 NLP and Text Mining 10-I=STM-162-m01 \n", + "12 Systems Benchmarking 10-I=SB-212-m01 \n", + "13 Computer Vision 10-xtAI=CV-202-m01 \n", + "14 Image Processing and Computational Photography 10-I=IP-222-m01 \n", + "\n", + " Module coordinator \\\n", + "0 Faculty of Business Management and Economics \n", + "1 Faculty of Business Management and Economics \n", + "2 Faculty of Business Management and Economics \n", + "3 Institute of Computer Science \n", + "4 Institute of Computer Science \n", + "5 Institute of Computer Science \n", + "6 Institute of Computer Science \n", + "7 Institute of Computer Science \n", + "8 Institute of Computer Science \n", + "9 Institute of Computer Science \n", + "10 Institute of Computer Science \n", + "11 Institute of Computer Science \n", + "12 Institute of Computer Science \n", + "13 Institute of Computer Science \n", + "14 Institute of Computer Science \n", + "\n", + " Module offered by ETCS Method of grading \\\n", + "0 holder of the Chair of Business Management and... 5 numerical grade \n", + "1 Holder of the Chair of Information Systems Eng... 5 numerical grade \n", + "2 Holder of the Chair of Business Management and... 15 numerical grade \n", + "3 Dean of Studies Informatik (Computer Science) 5 numerical grade \n", + "4 holder of the Chair of Computer Science II 5 numerical grade \n", + "5 holder of the Chair of Computer Science II 5 numerical grade \n", + "6 holder of the Chair of Computer Science II 5 numerical grade \n", + "7 holder of the Chair of Computer Science VI 5 numerical grade \n", + "8 holder of the Chair of Computer Science III 8 numerical grade \n", + "9 holder of the Chair of Computer Science II 5 numerical grade \n", + "10 holder of the Chair of Computer Science IX 5 numerical grade \n", + "11 holder of the Chair of Computer Science VI 5 numerical grade \n", + "12 holder of the Chair of Computer Science IX 5 numerical grade \n", + "13 Dean of Studies Informatik (Computer Science) 5 numerical grade \n", + "14 nan 5 numerical grade \n", + "\n", + " Duration Module level \\\n", + "0 1 semester graduate \n", + "1 1 semester graduate \n", + "2 1 semester graduate \n", + "3 1 semester graduate \n", + "4 1 semester graduate \n", + "5 1 semester graduate \n", + "6 1 semester graduate \n", + "7 1 semester graduate \n", + "8 1 semester graduate \n", + "9 1 semester graduate \n", + "10 1 semester graduate \n", + "11 1 semester graduate \n", + "12 1 semester nan \n", + "13 1 semester graduate \n", + "14 1 semester nan \n", + "\n", + " Contents \\\n", + "0 Content:This course provides students with an ... \n", + "1 Content:This course provides students with an ... \n", + "2 Content:In small project teams of 4 to 10 memb... \n", + "3 IR models (e. g. Boolean and vector space mode... \n", + "4 Program analysis, model creation in software e... \n", + "5 The lecture provides an overview of common sof... \n", + "6 Current topics in the area of aerospace. \n", + "7 Intelligent agents, uninformed and heuristic s... \n", + "8 Introduction to simulation techniques, statist... \n", + "9 With the knowledge of basic programming, taugh... \n", + "10 Overview over NN, implementation of important ... \n", + "11 Foundations in the following areas: definition... \n", + "12 -- \n", + "13 The lecture provides knowledge about current m... \n", + "14 -- \n", + "\n", + " Intended learning outcomes \\\n", + "0 After completing the course \"Integrated Inform... \n", + "1 After completing the course \"IT Management\", s... \n", + "2 After completing the course \"Projektseminar\", ... \n", + "3 The students possess theoretical and practical... \n", + "4 The students are able to analyse programs, to ... \n", + "5 Students gain a deep understanding of software... \n", + "6 The students possess a fundamental and applica... \n", + "7 The students possess theoretical and practical... \n", + "8 The students possess the methodic knowledge an... \n", + "9 Students learn advanced programming paradigms ... \n", + "10 Knowledge about possible applications and limi... \n", + "11 The students possess theoretical and practical... \n", + "12 -- \n", + "13 Students have fundamental knowledge of problem... \n", + "14 -- \n", + "\n", + " Courses \\\n", + "0 V (2) + Ü (2) \n", + "1 V (2) + Ü (2) \n", + "2 S (2) \n", + "3 V (2) + Ü (2) \n", + "4 V (2) + Ü (2) \n", + "5 V (2) + Ü (2)Module taught in: English \n", + "6 V (2) + Ü (2) \n", + "7 V (2) + Ü (2) \n", + "8 V (4) + Ü (2) \n", + "9 V (2) + Ü (2)Module taught in: English \n", + "10 V (2) + Ü (2) \n", + "11 V (2) + Ü (2) \n", + "12 V (2) + Ü (2) \n", + "13 V (2) + Ü (2)Module taught in: English \n", + "14 V (2) + Ü (2)Module taught in: English \n", + "\n", + " Method of assessment Allocation of places \\\n", + "0 written examination (approx. 60 minutes)Langua... -- \n", + "1 a) written examination (approx. 60 minutes) or... -- \n", + "2 project: preparing a conceptual design (approx... -- \n", + "3 written examination (approx. 60 to 120 minutes... -- \n", + "4 written examination (approx. 60 to 120 minutes... -- \n", + "5 written examination (approx. 60 to 120 minutes... -- \n", + "6 written examination (approx. 60 to 120 minutes... -- \n", + "7 written examination (approx. 60 to 120 minutes... -- \n", + "8 written examination (approx. 60 to 120 minutes... -- \n", + "9 written examination (90 to 120 minutes)Languag... -- \n", + "10 written examination (approx. 60 to 120 minutes... -- \n", + "11 written examination (approx. 60 to 120 minutes... -- \n", + "12 written examination (approx. 60 to 120 minutes... -- \n", + "13 Written examination (approx. 60 to 120 minutes... -- \n", + "14 written examination (approx. 60 to 120 minutes... -- \n", + "\n", + " Additional information Workload Teaching cycle \\\n", + "0 -- 150 h -- \n", + "1 -- 150 h -- \n", + "2 -- 450 h -- \n", + "3 Focuses available for students of the Masters ... 150 h -- \n", + "4 Focuses available for students of the Masters ... 150 h -- \n", + "5 Focuses available for students of the Masters ... 150 h -- \n", + "6 Focuses available for students of the Masters ... 150 h -- \n", + "7 Focuses available for students of the Masters ... 150 h -- \n", + "8 Focuses available for students of the Masters ... 240 h -- \n", + "9 -- 150 h -- \n", + "10 Focuses available for students of the Masters ... 150 h -- \n", + "11 Focuses available for students of the Masters ... 150 h -- \n", + "12 Focuses available for students of the Masters ... 150 h -- \n", + "13 -- 150 h -- \n", + "14 -- 150 h -- \n", + "\n", + " Referred to in LPO I \n", + "0 -- \n", + "1 -- \n", + "2 -- \n", + "3 -- \n", + "4 -- \n", + "5 -- \n", + "6 -- \n", + "7 -- \n", + "8 -- \n", + "9 -- \n", + "10 -- \n", + "11 -- \n", + "12 -- \n", + "13 -- \n", + "14 -- " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "What is the abbreviation of the module Information Processing within Organizations?\n", + "Predicted answer: \n" + ] + } + ], + "source": [ + "# handy helper function in case inference on Pandas dataframe\n", + "answers = []\n", + "for coordinates in predicted_answer_coordinates:\n", + " if len(coordinates) == 1:\n", + " # only a single cell:\n", + " answers.append(table.iat[coordinates[0]])\n", + " else:\n", + " # multiple cells\n", + " cell_values = []\n", + " for coordinate in coordinates:\n", + " cell_values.append(table.iat[coordinate])\n", + " answers.append(\", \".join(cell_values))\n", + "\n", + "display(table)\n", + "print(\"\")\n", + "for query, answer in zip(queries, answers):\n", + " print(query)\n", + " print(\"Predicted answer: \" + answer)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/04_finetuning_approaches/Fine_tuning_TapasForQuestionAnswering_on_SQA.ipynb b/04_finetuning_approaches/Fine_tuning_TapasForQuestionAnswering_on_SQA.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..14dff15229d72b536eebcb063a4b37b105416a0d --- /dev/null +++ b/04_finetuning_approaches/Fine_tuning_TapasForQuestionAnswering_on_SQA.ipynb @@ -0,0 +1,3346 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "l5Ds1ZM41KC9" + }, + "source": [ + "## Introduction: TAPAS\n", + "\n", + "* Original TAPAS paper (ACL 2020): https://www.aclweb.org/anthology/2020.acl-main.398/\n", + "* Follow-up paper on intermediate pre-training (EMMNLP Findings 2020): https://www.aclweb.org/anthology/2020.findings-emnlp.27/\n", + "* Original Github repository: https://github.com/google-research/tapas\n", + "* Blog post: https://ai.googleblog.com/2020/04/using-neural-networks-to-find-answers.html\n", + "\n", + "TAPAS is an algorithm that (among other tasks) can answer questions about tabular data. It is essentially a BERT model with relative position embeddings and additional token type ids that encode tabular structure, and 2 classification heads on top: one for **cell selection** and one for (optionally) performing an **aggregation** among selected cells (such as summing or counting).\n", + "\n", + "Similar to BERT, the base `TapasModel` is pre-trained using the masked language modeling (MLM) objective on a large collection of tables from Wikipedia and associated texts. In addition, the authors further pre-trained the model on an second task (table entailment) to increase the numerical reasoning capabilities of TAPAS (as explained in the follow-up paper), which further improves performance on downstream tasks.\n", + "\n", + "In this notebook, we are going to fine-tune `TapasForQuestionAnswering` on [Sequential Question Answering (SQA)](https://www.microsoft.com/en-us/research/publication/search-based-neural-structured-learning-sequential-question-answering/), a dataset built by Microsoft Research which deals with asking questions related to a table in a **conversational set-up**. We are going to do so as in the original paper, by adding a randomly initialized cell selection head on top of the pre-trained base model (note that SQA does not have questions that involve aggregation and hence no aggregation head), and then fine-tuning them altogether.\n", + "\n", + "First, we install both the Transformers library as well as the dependency on [`torch-scatter`](https://github.com/rusty1s/pytorch_scatter), which the model requires." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "MUMrt5Ow_PEA", + "outputId": "eda7d53e-9846-4941-ed72-ce84f495469f" + }, + "outputs": [], + "source": [ + "#! rm -r transformers\n", + "#! git clone https://github.com/huggingface/transformers.git\n", + "#! cd transformers\n", + "#! pip install ./transformers" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "gx4u09iTyRjY", + "outputId": "e4cd9f4b-7d8d-4b47-e8b2-304b921dba98" + }, + "outputs": [], + "source": [ + "#! pip install torch-scatter==latest+cu101 -f https://pytorch-geometric.com/whl/torch-1.7.0.html" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BSZfmBt0meYm" + }, + "source": [ + "We also install a small portion from the SQA training dataset, for demonstration purposes. This is a TSV file containing table-question pairs. Besides this, we also download the `table_csv` directory, which contains the actual tabular data.\n", + "\n", + "Note that you can download the entire SQA dataset on the [official website](https://www.microsoft.com/en-us/download/details.aspx?id=54253)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wsuwgDEU4J_f" + }, + "outputs": [], + "source": [ + "import requests, zipfile, io\n", + "import os\n", + "\n", + "def download_files(dir_name):\n", + " if not os.path.exists(dir_name):\n", + " # 28 training examples from the SQA training set + table csv data\n", + " urls = [\"https://www.dropbox.com/s/2p6ez9xro357i63/sqa_train_set_28_examples.zip?dl=1\",\n", + " \"https://www.dropbox.com/s/abhum8ssuow87h6/table_csv.zip?dl=1\"\n", + " ]\n", + " for url in urls:\n", + " r = requests.get(url)\n", + " z = zipfile.ZipFile(io.BytesIO(r.content))\n", + " z.extractall()\n", + "\n", + "dir_name = \"sqa_data\"\n", + "download_files(dir_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EPrYJOn81f0D" + }, + "source": [ + "## Prepare the data\n", + "\n", + "Let's look at the first few rows of the dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 279 + }, + "id": "2X27wyd805D8", + "outputId": "7ccfd32c-e8dd-4fec-c044-d7d8de8dd578" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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idannotatorpositionquestiontable_fileanswer_coordinatesanswer_text
0nt-63900where are the players from?table_csv/203_149.csv['(0, 4)', '(1, 4)', '(2, 4)', '(3, 4)', '(4, ...['Louisiana State University', 'Valley HS (Las...
1nt-63901which player went to louisiana state university?table_csv/203_149.csv['(0, 1)']['Ben McDonald']
2nt-63910who are the players?table_csv/203_149.csv['(0, 1)', '(1, 1)', '(2, 1)', '(3, 1)', '(4, ...['Ben McDonald', 'Tyler Houston', 'Roger Salke...
3nt-63911which ones are in the top 26 picks?table_csv/203_149.csv['(0, 1)', '(1, 1)', '(2, 1)', '(3, 1)', '(4, ...['Ben McDonald', 'Tyler Houston', 'Roger Salke...
4nt-63912and of those, who is from louisiana state univ...table_csv/203_149.csv['(0, 1)']['Ben McDonald']
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" + ], + "text/plain": [ + " id annotator position \\\n", + "0 nt-639 0 0 \n", + "1 nt-639 0 1 \n", + "2 nt-639 1 0 \n", + "3 nt-639 1 1 \n", + "4 nt-639 1 2 \n", + "\n", + " question table_file \\\n", + "0 where are the players from? table_csv/203_149.csv \n", + "1 which player went to louisiana state university? table_csv/203_149.csv \n", + "2 who are the players? table_csv/203_149.csv \n", + "3 which ones are in the top 26 picks? table_csv/203_149.csv \n", + "4 and of those, who is from louisiana state univ... table_csv/203_149.csv \n", + "\n", + " answer_coordinates \\\n", + "0 ['(0, 4)', '(1, 4)', '(2, 4)', '(3, 4)', '(4, ... \n", + "1 ['(0, 1)'] \n", + "2 ['(0, 1)', '(1, 1)', '(2, 1)', '(3, 1)', '(4, ... \n", + "3 ['(0, 1)', '(1, 1)', '(2, 1)', '(3, 1)', '(4, ... \n", + "4 ['(0, 1)'] \n", + "\n", + " answer_text \n", + "0 ['Louisiana State University', 'Valley HS (Las... \n", + "1 ['Ben McDonald'] \n", + "2 ['Ben McDonald', 'Tyler Houston', 'Roger Salke... \n", + "3 ['Ben McDonald', 'Tyler Houston', 'Roger Salke... \n", + "4 ['Ben McDonald'] " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "data = pd.read_excel(\"sqa_train_set_28_examples.xlsx\")\n", + "data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OMJ4dNBV1oj6" + }, + "source": [ + "As you can see, each row corresponds to a question related to a table.\n", + "* The `position` column identifies whether the question is the first, second, ... in a sequence of questions related to a table.\n", + "* The `table_file` column identifies the name of the table file, which refers to a CSV file in the `table_csv` directory.\n", + "* The `answer_coordinates` and `answer_text` columns indicate the answer to the question. The `answer_coordinates` is a list of tuples, each tuple being a (row_index, column_index) pair. The `answer_text` column is a list of strings, indicating the cell values.\n", + "\n", + "However, the `answer_coordinates` and `answer_text` columns are currently not recognized as real Python lists of Python tuples and strings respectively. Let's do that first using the `.literal_eval()`function of the `ast` module:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 511 + }, + "id": "BAovAs5s1k10", + "outputId": "0849a829-4ae8-43e9-e138-177fa14e3e36" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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idannotatorpositionquestiontable_fileanswer_coordinatesanswer_text
0nt-63900where are the players from?table_csv/203_149.csv[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, 4...[Louisiana State University, Valley HS (Las Ve...
1nt-63901which player went to louisiana state university?table_csv/203_149.csv[(0, 1)][Ben McDonald]
2nt-63910who are the players?table_csv/203_149.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Ben McDonald, Tyler Houston, Roger Salkeld, J...
3nt-63911which ones are in the top 26 picks?table_csv/203_149.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Ben McDonald, Tyler Houston, Roger Salkeld, J...
4nt-63912and of those, who is from louisiana state univ...table_csv/203_149.csv[(0, 1)][Ben McDonald]
5nt-63920who are the players in the top 26?table_csv/203_149.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Ben McDonald, Tyler Houston, Roger Salkeld, J...
6nt-63921of those, which one was from louisiana state u...table_csv/203_149.csv[(0, 1)][Ben McDonald]
7nt-1164900what are all the names of the teams?table_csv/204_135.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Cordoba CF, CD Malaga, Granada CF, UD Las Pal...
8nt-1164901of these, which teams had any losses?table_csv/204_135.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Cordoba CF, CD Malaga, Granada CF, UD Las Pal...
9nt-1164902of these teams, which had more than 21 losses?table_csv/204_135.csv[(15, 1)][CD Villarrobledo]
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" + ], + "text/plain": [ + " id annotator position \\\n", + "0 nt-639 0 0 \n", + "1 nt-639 0 1 \n", + "2 nt-639 1 0 \n", + "3 nt-639 1 1 \n", + "4 nt-639 1 2 \n", + "5 nt-639 2 0 \n", + "6 nt-639 2 1 \n", + "7 nt-11649 0 0 \n", + "8 nt-11649 0 1 \n", + "9 nt-11649 0 2 \n", + "\n", + " question table_file \\\n", + "0 where are the players from? table_csv/203_149.csv \n", + "1 which player went to louisiana state university? table_csv/203_149.csv \n", + "2 who are the players? table_csv/203_149.csv \n", + "3 which ones are in the top 26 picks? table_csv/203_149.csv \n", + "4 and of those, who is from louisiana state univ... table_csv/203_149.csv \n", + "5 who are the players in the top 26? table_csv/203_149.csv \n", + "6 of those, which one was from louisiana state u... table_csv/203_149.csv \n", + "7 what are all the names of the teams? table_csv/204_135.csv \n", + "8 of these, which teams had any losses? table_csv/204_135.csv \n", + "9 of these teams, which had more than 21 losses? table_csv/204_135.csv \n", + "\n", + " answer_coordinates \\\n", + "0 [(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, 4... \n", + "1 [(0, 1)] \n", + "2 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "3 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "4 [(0, 1)] \n", + "5 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "6 [(0, 1)] \n", + "7 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "8 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "9 [(15, 1)] \n", + "\n", + " answer_text \n", + "0 [Louisiana State University, Valley HS (Las Ve... \n", + "1 [Ben McDonald] \n", + "2 [Ben McDonald, Tyler Houston, Roger Salkeld, J... \n", + "3 [Ben McDonald, Tyler Houston, Roger Salkeld, J... \n", + "4 [Ben McDonald] \n", + "5 [Ben McDonald, Tyler Houston, Roger Salkeld, J... \n", + "6 [Ben McDonald] \n", + "7 [Cordoba CF, CD Malaga, Granada CF, UD Las Pal... \n", + "8 [Cordoba CF, CD Malaga, Granada CF, UD Las Pal... \n", + "9 [CD Villarrobledo] " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import ast\n", + "\n", + "def _parse_answer_coordinates(answer_coordinate_str):\n", + " \"\"\"Parses the answer_coordinates of a question.\n", + " Args:\n", + " answer_coordinate_str: A string representation of a Python list of tuple\n", + " strings.\n", + " For example: \"['(1, 4)','(1, 3)', ...]\"\n", + " \"\"\"\n", + "\n", + " try:\n", + " answer_coordinates = []\n", + " # make a list of strings\n", + " coords = ast.literal_eval(answer_coordinate_str)\n", + " # parse each string as a tuple\n", + " for row_index, column_index in sorted(\n", + " ast.literal_eval(coord) for coord in coords):\n", + " answer_coordinates.append((row_index, column_index))\n", + " except SyntaxError:\n", + " raise ValueError('Unable to evaluate %s' % answer_coordinate_str)\n", + "\n", + " return answer_coordinates\n", + "\n", + "\n", + "def _parse_answer_text(answer_text):\n", + " \"\"\"Populates the answer_texts field of `answer` by parsing `answer_text`.\n", + " Args:\n", + " answer_text: A string representation of a Python list of strings.\n", + " For example: \"[u'test', u'hello', ...]\"\n", + " answer: an Answer object.\n", + " \"\"\"\n", + " try:\n", + " answer = []\n", + " for value in ast.literal_eval(answer_text):\n", + " answer.append(value)\n", + " except SyntaxError:\n", + " raise ValueError('Unable to evaluate %s' % answer_text)\n", + "\n", + " return answer\n", + "\n", + "data['answer_coordinates'] = data['answer_coordinates'].apply(lambda coords_str: _parse_answer_coordinates(coords_str))\n", + "data['answer_text'] = data['answer_text'].apply(lambda txt: _parse_answer_text(txt))\n", + "\n", + "data.head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "X7FYPpdW5dY4" + }, + "source": [ + "Let's create a new dataframe that groups questions which are asked in a sequence related to the table. We can do this by adding a `sequence_id` column, which is a combination of the `id` and `annotator` columns:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 279 + }, + "id": "O1Quo0FL7h9-", + "outputId": "5223d575-b86d-41e6-b23a-6071b3048211" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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idannotatorpositionquestiontable_fileanswer_coordinatesanswer_textsequence_id
0nt-63900where are the players from?table_csv/203_149.csv[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, 4...[Louisiana State University, Valley HS (Las Ve...nt-639-0
1nt-63901which player went to louisiana state university?table_csv/203_149.csv[(0, 1)][Ben McDonald]nt-639-0
2nt-63910who are the players?table_csv/203_149.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Ben McDonald, Tyler Houston, Roger Salkeld, J...nt-639-1
3nt-63911which ones are in the top 26 picks?table_csv/203_149.csv[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1...[Ben McDonald, Tyler Houston, Roger Salkeld, J...nt-639-1
4nt-63912and of those, who is from louisiana state univ...table_csv/203_149.csv[(0, 1)][Ben McDonald]nt-639-1
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" + ], + "text/plain": [ + " id annotator position \\\n", + "0 nt-639 0 0 \n", + "1 nt-639 0 1 \n", + "2 nt-639 1 0 \n", + "3 nt-639 1 1 \n", + "4 nt-639 1 2 \n", + "\n", + " question table_file \\\n", + "0 where are the players from? table_csv/203_149.csv \n", + "1 which player went to louisiana state university? table_csv/203_149.csv \n", + "2 who are the players? table_csv/203_149.csv \n", + "3 which ones are in the top 26 picks? table_csv/203_149.csv \n", + "4 and of those, who is from louisiana state univ... table_csv/203_149.csv \n", + "\n", + " answer_coordinates \\\n", + "0 [(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, 4... \n", + "1 [(0, 1)] \n", + "2 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "3 [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1... \n", + "4 [(0, 1)] \n", + "\n", + " answer_text sequence_id \n", + "0 [Louisiana State University, Valley HS (Las Ve... nt-639-0 \n", + "1 [Ben McDonald] nt-639-0 \n", + "2 [Ben McDonald, Tyler Houston, Roger Salkeld, J... nt-639-1 \n", + "3 [Ben McDonald, Tyler Houston, Roger Salkeld, J... nt-639-1 \n", + "4 [Ben McDonald] nt-639-1 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def get_sequence_id(example_id, annotator):\n", + " if \"-\" in str(annotator):\n", + " raise ValueError('\"-\" not allowed in annotator.')\n", + " return f\"{example_id}-{annotator}\"\n", + "\n", + "data['sequence_id'] = data.apply(lambda x: get_sequence_id(x.id, x.annotator), axis=1)\n", + "data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 541 + }, + "id": "-uPpds5D762B", + "outputId": "38aa6f13-2cc7-4d96-b8b3-a510288bfca2" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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questiontable_fileanswer_coordinatesanswer_text
sequence_id
ns-1292-0[who are all the athletes?, where are they fro...table_csv/204_521.csv[[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ...[[Tommy Green, Janis Dalins, Ugo Frigerio, Kar...
nt-10730-0[what was the production numbers of each revol...table_csv/203_253.csv[[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, ...[[1,900 (estimated), 14,500 (estimated), 6,000...
nt-10730-1[what three revolver models had the least amou...table_csv/203_253.csv[[(0, 0), (6, 0), (7, 0)], [(0, 0)]][[Remington-Beals Army Model Revolver, New Mod...
nt-10730-2[what are all of the remington models?, how ma...table_csv/203_253.csv[[(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, ...[[Remington-Beals Army Model Revolver, Remingt...
nt-11649-0[what are all the names of the teams?, of thes...table_csv/204_135.csv[[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ...[[Cordoba CF, CD Malaga, Granada CF, UD Las Pa...
nt-11649-1[what are the losses?, what team had more than...table_csv/204_135.csv[[(0, 6), (1, 6), (2, 6), (3, 6), (4, 6), (5, ...[[6, 6, 9, 10, 10, 12, 12, 11, 13, 14, 15, 14,...
nt-11649-2[what were all the teams?, what were the loss ...table_csv/204_135.csv[[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ...[[Cordoba CF, CD Malaga, Granada CF, UD Las Pa...
nt-639-0[where are the players from?, which player wen...table_csv/203_149.csv[[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, ...[[Louisiana State University, Valley HS (Las V...
nt-639-1[who are the players?, which ones are in the t...table_csv/203_149.csv[[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ...[[Ben McDonald, Tyler Houston, Roger Salkeld, ...
nt-639-2[who are the players in the top 26?, of those,...table_csv/203_149.csv[[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ...[[Ben McDonald, Tyler Houston, Roger Salkeld, ...
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" + ], + "text/plain": [ + " question \\\n", + "sequence_id \n", + "ns-1292-0 [who are all the athletes?, where are they fro... \n", + "nt-10730-0 [what was the production numbers of each revol... \n", + "nt-10730-1 [what three revolver models had the least amou... \n", + "nt-10730-2 [what are all of the remington models?, how ma... \n", + "nt-11649-0 [what are all the names of the teams?, of thes... \n", + "nt-11649-1 [what are the losses?, what team had more than... \n", + "nt-11649-2 [what were all the teams?, what were the loss ... \n", + "nt-639-0 [where are the players from?, which player wen... \n", + "nt-639-1 [who are the players?, which ones are in the t... \n", + "nt-639-2 [who are the players in the top 26?, of those,... \n", + "\n", + " table_file \\\n", + "sequence_id \n", + "ns-1292-0 table_csv/204_521.csv \n", + "nt-10730-0 table_csv/203_253.csv \n", + "nt-10730-1 table_csv/203_253.csv \n", + "nt-10730-2 table_csv/203_253.csv \n", + "nt-11649-0 table_csv/204_135.csv \n", + "nt-11649-1 table_csv/204_135.csv \n", + "nt-11649-2 table_csv/204_135.csv \n", + "nt-639-0 table_csv/203_149.csv \n", + "nt-639-1 table_csv/203_149.csv \n", + "nt-639-2 table_csv/203_149.csv \n", + "\n", + " answer_coordinates \\\n", + "sequence_id \n", + "ns-1292-0 [[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ... \n", + "nt-10730-0 [[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, ... \n", + "nt-10730-1 [[(0, 0), (6, 0), (7, 0)], [(0, 0)]] \n", + "nt-10730-2 [[(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, ... \n", + "nt-11649-0 [[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ... \n", + "nt-11649-1 [[(0, 6), (1, 6), (2, 6), (3, 6), (4, 6), (5, ... \n", + "nt-11649-2 [[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ... \n", + "nt-639-0 [[(0, 4), (1, 4), (2, 4), (3, 4), (4, 4), (5, ... \n", + "nt-639-1 [[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ... \n", + "nt-639-2 [[(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, ... \n", + "\n", + " answer_text \n", + "sequence_id \n", + "ns-1292-0 [[Tommy Green, Janis Dalins, Ugo Frigerio, Kar... \n", + "nt-10730-0 [[1,900 (estimated), 14,500 (estimated), 6,000... \n", + "nt-10730-1 [[Remington-Beals Army Model Revolver, New Mod... \n", + "nt-10730-2 [[Remington-Beals Army Model Revolver, Remingt... \n", + "nt-11649-0 [[Cordoba CF, CD Malaga, Granada CF, UD Las Pa... \n", + "nt-11649-1 [[6, 6, 9, 10, 10, 12, 12, 11, 13, 14, 15, 14,... \n", + "nt-11649-2 [[Cordoba CF, CD Malaga, Granada CF, UD Las Pa... \n", + "nt-639-0 [[Louisiana State University, Valley HS (Las V... \n", + "nt-639-1 [[Ben McDonald, Tyler Houston, Roger Salkeld, ... \n", + "nt-639-2 [[Ben McDonald, Tyler Houston, Roger Salkeld, ... " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# let's group table-question pairs by sequence id, and remove some columns we don't need\n", + "grouped = data.groupby(by='sequence_id').agg(lambda x: x.tolist())\n", + "grouped = grouped.drop(columns=['id', 'annotator', 'position'])\n", + "grouped['table_file'] = grouped['table_file'].apply(lambda x: x[0])\n", + "grouped.head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r6RKTkSeLLyJ" + }, + "source": [ + "Each row in the dataframe above now consists of a **table and one or more questions** which are asked in a **sequence**. Let's visualize the first row, i.e. a table, together with its queries:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 525 + }, + "id": "J-dTi5omLdN_", + "outputId": "b8e1d893-8d8b-4540-dc35-57586312c992" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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RankNameNationalityTime (hand)Notes
0nanTommy GreenGreat Britain4:50:10OR
1nanJanis DalinsLatvia4:57:20nan
2nanUgo FrigerioItaly4:59:06nan
34.0Karl HahnelGermany5:06:06nan
45.0Ettore RivoltaItaly5:07:39nan
56.0Paul SievertGermany5:16:41nan
67.0Henri QuintricFrance5:27:25nan
78.0Ernie CrosbieUnited States5:28:02nan
89.0Bill ChisholmUnited States5:51:00nan
910.0Alfred MaasikEstonia6:19:00nan
10nanHenry CiemanCanadananDNF
11nanJohn MoralisGreecenanDNF
12nanFrancesco PrettiItalynanDNF
13nanArthur Tell SchwabSwitzerlandnanDNF
14nanHarry HinkelUnited StatesnanDNF
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" + ], + "text/plain": [ + " Rank Name Nationality Time (hand) Notes\n", + "0 nan Tommy Green Great Britain 4:50:10 OR\n", + "1 nan Janis Dalins Latvia 4:57:20 nan\n", + "2 nan Ugo Frigerio Italy 4:59:06 nan\n", + "3 4.0 Karl Hahnel Germany 5:06:06 nan\n", + "4 5.0 Ettore Rivolta Italy 5:07:39 nan\n", + "5 6.0 Paul Sievert Germany 5:16:41 nan\n", + "6 7.0 Henri Quintric France 5:27:25 nan\n", + "7 8.0 Ernie Crosbie United States 5:28:02 nan\n", + "8 9.0 Bill Chisholm United States 5:51:00 nan\n", + "9 10.0 Alfred Maasik Estonia 6:19:00 nan\n", + "10 nan Henry Cieman Canada nan DNF\n", + "11 nan John Moralis Greece nan DNF\n", + "12 nan Francesco Pretti Italy nan DNF\n", + "13 nan Arthur Tell Schwab Switzerland nan DNF\n", + "14 nan Harry Hinkel United States nan DNF" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "['who are all the athletes?', 'where are they from?', 'along with paul sievert, which athlete is from germany?']\n" + ] + } + ], + "source": [ + "# path to the directory containing all csv files\n", + "table_csv_path = \"table_csv\"\n", + "\n", + "item = grouped.iloc[0]\n", + "table = pd.read_csv(table_csv_path + item.table_file[9:]).astype(str)\n", + "\n", + "display(table)\n", + "print(\"\")\n", + "print(item.question)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yw8MqIExLnnq" + }, + "source": [ + "We can see that there are 3 sequential questions asked related to the contents of the table.\n", + "\n", + "We can now use `TapasTokenizer` to batch encode this, as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "t5iU5byAICWb" + }, + "outputs": [], + "source": [ + "import torch\n", + "from transformers import TapasTokenizer\n", + "\n", + "# initialize the tokenizer\n", + "tokenizer = TapasTokenizer.from_pretrained(\"google/tapas-base\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5qOBiUPEGgK8", + "outputId": "7bc36d39-21be-433e-ecde-3f0d81c340ea" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['input_ids', 'labels', 'numeric_values', 'numeric_values_scale', 'token_type_ids', 'attention_mask'])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "encoding = tokenizer(table=table, queries=item.question, answer_coordinates=item.answer_coordinates, answer_text=item.answer_text,\n", + " truncation=True, padding=\"max_length\", return_tensors=\"pt\")\n", + "encoding.keys()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y2JRiKjPRHAF" + }, + "source": [ + "TAPAS basically flattens every table-question pair before feeding it into a BERT like model:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 137 + }, + "id": "lhipz2_GRNKQ", + "outputId": "a3ad3993-5173-45c7-a43b-993ab42f77e3" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] who are all the athletes? [SEP] rank name nationality time ( hand ) notes [EMPTY] tommy green great britain 4 : 50 : 10 or [EMPTY] janis dalins latvia 4 : 57 : 20 [EMPTY] [EMPTY] ugo frigerio italy 4 : 59 : 06 [EMPTY] 4. 0 karl hahnel germany 5 : 06 : 06 [EMPTY] 5. 0 ettore rivolta italy 5 : 07 : 39 [EMPTY] 6. 0 paul sievert germany 5 : 16 : 41 [EMPTY] 7. 0 henri quintric france 5 : 27 : 25 [EMPTY] 8. 0 ernie crosbie united states 5 : 28 : 02 [EMPTY] 9. 0 bill chisholm united states 5 : 51 : 00 [EMPTY] 10. 0 alfred maasik estonia 6 : 19 : 00 [EMPTY] [EMPTY] henry cieman canada [EMPTY] dnf [EMPTY] john moralis greece [EMPTY] dnf [EMPTY] francesco pretti italy [EMPTY] dnf [EMPTY] arthur tell schwab switzerland [EMPTY] dnf [EMPTY] harry hinkel united states [EMPTY] dnf [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD]'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(encoding[\"input_ids\"][0])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nVeB5IPaN5oN" + }, + "source": [ + "The `token_type_ids` created here will be of shape (batch_size, sequence_length, 7), as TAPAS uses 7 different token types to encode tabular structure. Let's verify this:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "id": "zM0v-pwbN6gR" + }, + "outputs": [], + "source": [ + "assert encoding[\"token_type_ids\"].shape == (3, 512, 7)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TMt7cWJMLvue" + }, + "source": [ + "\n", + "\n", + "One thing we can verify is whether the `prev_label` token type ids are created correctly. These indicate which tokens were (part of) an answer to the previous table-question pair.\n", + "\n", + "The prev_label token type ids of the first example in a batch must always be zero (since there's no previous table-question pair). Let's verify this:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "id": "ytUk-H1yL9cc" + }, + "outputs": [], + "source": [ + "assert encoding[\"token_type_ids\"][0][:,3].sum() == 0" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rJ_o-82nMfK5" + }, + "source": [ + "However, the `prev_label` token type ids of the second table-question pair in the batch must be set to 1 for the tokens which were an answer to the previous (i.e. the first) table question pair in the batch. The answers to the first table-question pair are the following:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "yxT9h2LIMNt3", + "outputId": "69b29df5-8103-4b55-e8f4-598bd637a546" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Tommy Green', 'Janis Dalins', 'Ugo Frigerio', 'Karl Hahnel', 'Ettore Rivolta', 'Paul Sievert', 'Henri Quintric', 'Ernie Crosbie', 'Bill Chisholm', 'Alfred Maasik', 'Henry Cieman', 'John Moralis', 'Francesco Pretti', 'Arthur Tell Schwab', 'Harry Hinkel']\n" + ] + } + ], + "source": [ + "print(item.answer_text[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CSUkMGAcMpfE" + }, + "source": [ + "So let's now verify whether the `prev_label` ids of the second table-question pair are set correctly:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Uv6P7OpJGxuu", + "outputId": "69b92a6a-408f-48f8-9842-dd3842f7188c" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[CLS] 0\n", + "where 0\n", + "are 0\n", + "they 0\n", + "from 0\n", + "? 0\n", + "[SEP] 0\n", + "rank 0\n", + "name 0\n", + "nationality 0\n", + "time 0\n", + "( 0\n", + "hand 0\n", + ") 0\n", + "notes 0\n", + "[EMPTY] 0\n", + "tommy 1\n", + "green 1\n", + "great 0\n", + "britain 0\n", + "4 0\n", + ": 0\n", + "50 0\n", + ": 0\n", + "10 0\n", + "or 0\n", + "[EMPTY] 0\n", + "jan 1\n", + "##is 1\n", + "dali 1\n", + "##ns 1\n", + "latvia 0\n", + "4 0\n", + ": 0\n", + "57 0\n", + ": 0\n", + "20 0\n", + "[EMPTY] 0\n", + "[EMPTY] 0\n", + "u 1\n", + "##go 1\n", + "fr 1\n", + "##iger 1\n", + "##io 1\n", + "italy 0\n", + "4 0\n", + ": 0\n", + "59 0\n", + ": 0\n", + "06 0\n", + "[EMPTY] 0\n", + "4 0\n", + ". 0\n", + "0 0\n", + "karl 1\n", + "hahn 1\n", + "##el 1\n", + "germany 0\n", + "5 0\n", + ": 0\n", + "06 0\n", + ": 0\n", + "06 0\n", + "[EMPTY] 0\n", + "5 0\n", + ". 0\n", + "0 0\n", + "et 1\n", + "##tore 1\n", + "ri 1\n", + "##vo 1\n", + "##lta 1\n", + "italy 0\n", + "5 0\n", + ": 0\n", + "07 0\n", + ": 0\n", + "39 0\n", + "[EMPTY] 0\n", + "6 0\n", + ". 0\n", + "0 0\n", + "paul 1\n", + "si 1\n", + "##ever 1\n", + "##t 1\n", + "germany 0\n", + "5 0\n", + ": 0\n", + "16 0\n", + ": 0\n", + "41 0\n", + "[EMPTY] 0\n", + "7 0\n", + ". 0\n", + "0 0\n", + "henri 1\n", + "qui 1\n", + "##nt 1\n", + "##ric 1\n", + "france 0\n", + "5 0\n", + ": 0\n", + "27 0\n", + ": 0\n", + "25 0\n", + "[EMPTY] 0\n", + "8 0\n", + ". 0\n", + "0 0\n", + "ernie 1\n", + "cr 1\n", + "##os 1\n", + "##bie 1\n", + "united 0\n", + "states 0\n", + "5 0\n", + ": 0\n", + "28 0\n", + ": 0\n", + "02 0\n", + "[EMPTY] 0\n", + "9 0\n", + ". 0\n", + "0 0\n", + "bill 1\n", + "chi 1\n", + "##sho 1\n", + "##lm 1\n", + "united 0\n", + "states 0\n", + "5 0\n", + ": 0\n", + "51 0\n", + ": 0\n", + "00 0\n", + "[EMPTY] 0\n", + "10 0\n", + ". 0\n", + "0 0\n", + "alfred 1\n", + "ma 1\n", + "##asi 1\n", + "##k 1\n", + "estonia 0\n", + "6 0\n", + ": 0\n", + "19 0\n", + ": 0\n", + "00 0\n", + "[EMPTY] 0\n", + "[EMPTY] 0\n", + "henry 1\n", + "ci 1\n", + "##eman 1\n", + "canada 0\n", + "[EMPTY] 0\n", + "d 0\n", + "##n 0\n", + "##f 0\n", + "[EMPTY] 0\n", + "john 1\n", + "moral 1\n", + "##is 1\n", + "greece 0\n", + "[EMPTY] 0\n", + "d 0\n", + "##n 0\n", + "##f 0\n", + "[EMPTY] 0\n", + "francesco 1\n", + "pre 1\n", + "##tti 1\n", + "italy 0\n", + "[EMPTY] 0\n", + "d 0\n", + "##n 0\n", + "##f 0\n", + "[EMPTY] 0\n", + "arthur 1\n", + "tell 1\n", + "sc 1\n", + "##hwa 1\n", + "##b 1\n", + "switzerland 0\n", + "[EMPTY] 0\n", + "d 0\n", + "##n 0\n", + "##f 0\n", + "[EMPTY] 0\n", + "harry 1\n", + "hi 1\n", + "##nk 1\n", + "##el 1\n", + "united 0\n", + "states 0\n", + "[EMPTY] 0\n", + "d 0\n", + "##n 0\n", + "##f 0\n" + ] + } + ], + "source": [ + "for id, prev_label in zip (encoding[\"input_ids\"][1], encoding[\"token_type_ids\"][1][:,3]):\n", + " if id != 0: # we skip padding tokens\n", + " print(tokenizer.decode([id]), prev_label.item())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wjVk49fO6u8H" + }, + "source": [ + "This looks OK! Be sure to check this, because the token type ids are critical for the performance of TAPAS.\n", + "\n", + "Let's create a PyTorch dataset and corresponding dataloader. Note the __getitem__ method here: in order to properly set the prev_labels token types, we must check whether a table-question pair is the first in a sequence or not. In case it is, we can just encode it. In case it isn't, we need to encode it together with the previous table-question pair.\n", + "\n", + "Note that this is not the most efficient approach, because we're effectively tokenizing each table-question pair twice when applied on the entire dataset (feel free to ping me a more efficient solution)." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "id": "C-n9vDTD1-k9" + }, + "outputs": [], + "source": [ + "class TableDataset(torch.utils.data.Dataset):\n", + " def __init__(self, df, tokenizer):\n", + " self.df = df\n", + " self.tokenizer = tokenizer\n", + "\n", + " def __getitem__(self, idx):\n", + " item = self.df.iloc[idx]\n", + " table = pd.read_csv(table_csv_path + item.table_file[9:]).astype(str) # TapasTokenizer expects the table data to be text only\n", + " if item.position != 0:\n", + " # use the previous table-question pair to correctly set the prev_labels token type ids\n", + " previous_item = self.df.iloc[idx-1]\n", + " encoding = self.tokenizer(table=table,\n", + " queries=[previous_item.question, item.question],\n", + " answer_coordinates=[previous_item.answer_coordinates, item.answer_coordinates],\n", + " answer_text=[previous_item.answer_text, item.answer_text],\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " # use encodings of second table-question pair in the batch\n", + " encoding = {key: val[-1] for key, val in encoding.items()}\n", + " else:\n", + " # this means it's the first table-question pair in a sequence\n", + " encoding = self.tokenizer(table=table,\n", + " queries=item.question,\n", + " answer_coordinates=item.answer_coordinates,\n", + " answer_text=item.answer_text,\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " # remove the batch dimension which the tokenizer adds\n", + " encoding = {key: val.squeeze(0) for key, val in encoding.items()}\n", + " return encoding\n", + "\n", + " def __len__(self):\n", + " return len(self.df)\n", + "\n", + "train_dataset = TableDataset(df=data, tokenizer=tokenizer)\n", + "train_dataloader = torch.utils.data.DataLoader(train_dataset, batch_size=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "X4CHgnTzwfNp", + "outputId": "a0980f27-a317-4375-9bc4-0085acad0e5f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([512, 7])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train_dataset[0][\"token_type_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "bZN1psdBy5_s", + "outputId": "e085d737-3a6f-45e5-c200-7c21916b284a" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([512])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train_dataset[1][\"input_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "id": "pHAyf85k_xQt" + }, + "outputs": [], + "source": [ + "batch = next(iter(train_dataloader))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "FoqySHh-_0JV", + "outputId": "9c0ab5d9-0a06-4331-80e2-ba3b739cfa92" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 512])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "batch[\"input_ids\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "g5pjJCCT_53N", + "outputId": "d2ebbf1e-0701-47c1-8533-a087892bd715" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 512, 7])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "batch[\"token_type_ids\"].shape" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xVb1-H-jAEoS" + }, + "source": [ + "Let's decode the first table-question pair:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 137 + }, + "id": "1vfjT1JC_7zI", + "outputId": "f1a85d76-96ab-4a4d-f8ae-c7ee913c6d7f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] where are the players from? [SEP] pick player team position school 1 ben mcdonald baltimore orioles rhp louisiana state university 2 tyler houston atlanta braves c valley hs ( las vegas, nv ) 3 roger salkeld seattle mariners rhp saugus ( ca ) hs 4 jeff jackson philadelphia phillies of simeon hs ( chicago, il ) 5 donald harris texas rangers of texas tech university 6 paul coleman saint louis cardinals of frankston ( tx ) hs 7 frank thomas chicago white sox 1b auburn university 8 earl cunningham chicago cubs of lancaster ( sc ) hs 9 kyle abbott california angels lhp long beach state university 10 charles johnson montreal expos c westwood hs ( fort pierce, fl ) 11 calvin murray cleveland indians 3b w. t. white high school ( dallas, tx ) 12 jeff juden houston astros rhp salem ( ma ) hs 13 brent mayne kansas city royals c cal state fullerton 14 steve hosey san francisco giants of fresno state university 15 kiki jones los angeles dodgers rhp hillsborough hs ( tampa, fl ) 16 greg blosser boston red sox of sarasota ( fl ) hs 17 cal eldred milwaukee brewers rhp university of iowa 18 willie greene pittsburgh pirates ss jones county hs ( gray, ga ) 19 eddie zosky toronto blue jays ss fresno state university 20 scott bryant cincinnati reds of university of texas 21 greg gohr detroit tigers rhp santa clara university 22 tom goodwin los angeles dodgers of fresno state university 23 mo vaughn boston red sox 1b seton hall university 24 alan zinter new york mets c university of arizona 25 chuck knoblauch minnesota twins 2b texas a & m university 26 scott burrell seattle mariners rhp hamden ( ct ) hs [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD]'" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(batch[\"input_ids\"][0])" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "id": "sujsp8o9DtsY" + }, + "outputs": [], + "source": [ + "#first example should not have any prev_labels set\n", + "assert batch[\"token_type_ids\"][0][:,3].sum() == 0" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EIeql5vfFI6s" + }, + "source": [ + "Let's decode the second table-question pair and verify some more:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 137 + }, + "id": "WrNo_qMqFOzi", + "outputId": "b2051f0b-72d8-42e2-a6b6-c5a40eda666f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'[CLS] which player went to louisiana state university? [SEP] pick player team position school 1 ben mcdonald baltimore orioles rhp louisiana state university 2 tyler houston atlanta braves c valley hs ( las vegas, nv ) 3 roger salkeld seattle mariners rhp saugus ( ca ) hs 4 jeff jackson philadelphia phillies of simeon hs ( chicago, il ) 5 donald harris texas rangers of texas tech university 6 paul coleman saint louis cardinals of frankston ( tx ) hs 7 frank thomas chicago white sox 1b auburn university 8 earl cunningham chicago cubs of lancaster ( sc ) hs 9 kyle abbott california angels lhp long beach state university 10 charles johnson montreal expos c westwood hs ( fort pierce, fl ) 11 calvin murray cleveland indians 3b w. t. white high school ( dallas, tx ) 12 jeff juden houston astros rhp salem ( ma ) hs 13 brent mayne kansas city royals c cal state fullerton 14 steve hosey san francisco giants of fresno state university 15 kiki jones los angeles dodgers rhp hillsborough hs ( tampa, fl ) 16 greg blosser boston red sox of sarasota ( fl ) hs 17 cal eldred milwaukee brewers rhp university of iowa 18 willie greene pittsburgh pirates ss jones county hs ( gray, ga ) 19 eddie zosky toronto blue jays ss fresno state university 20 scott bryant cincinnati reds of university of texas 21 greg gohr detroit tigers rhp santa clara university 22 tom goodwin los angeles dodgers of fresno state university 23 mo vaughn boston red sox 1b seton hall university 24 alan zinter new york mets c university of arizona 25 chuck knoblauch minnesota twins 2b texas a & m university 26 scott burrell seattle mariners rhp hamden ( ct ) hs [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD]'" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tokenizer.decode(batch[\"input_ids\"][1])" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9a1OToVqxNap", + "outputId": "2040d63a-024f-4e65-e17c-2a51630a9226" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor(132)\n" + ] + } + ], + "source": [ + "assert batch[\"labels\"][0].sum() == batch[\"token_type_ids\"][1][:,3].sum()\n", + "print(batch[\"token_type_ids\"][1][:,3].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "x4PRdYvBE1k3", + "outputId": "31bc6092-57e8-4040-f410-83e314ee4a0f" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[CLS] 0\n", + "which 0\n", + "player 0\n", + "went 0\n", + "to 0\n", + "louisiana 0\n", + "state 0\n", + "university 0\n", + "? 0\n", + "[SEP] 0\n", + "pick 0\n", + "player 0\n", + "team 0\n", + "position 0\n", + "school 0\n", + "1 0\n", + "ben 0\n", + "mcdonald 0\n", + "baltimore 0\n", + "orioles 0\n", + "r 0\n", + "##hp 0\n", + "louisiana 1\n", + "state 1\n", + "university 1\n", + "2 0\n", + "tyler 0\n", + "houston 0\n", + "atlanta 0\n", + "braves 0\n", + "c 0\n", + "valley 1\n", + "hs 1\n", + "( 1\n", + "las 1\n", + "vegas 1\n", + ", 1\n", + "n 1\n", + "##v 1\n", + ") 1\n", + "3 0\n", + "roger 0\n", + "sal 0\n", + "##kel 0\n", + "##d 0\n", + "seattle 0\n", + "mariners 0\n", + "r 0\n", + "##hp 0\n", + "sa 1\n", + "##ug 1\n", + "##us 1\n", + "( 1\n", + "ca 1\n", + ") 1\n", + "hs 1\n", + "4 0\n", + "jeff 0\n", + "jackson 0\n", + "philadelphia 0\n", + "phillies 0\n", + "of 0\n", + "simeon 1\n", + "hs 1\n", + "( 1\n", + "chicago 1\n", + ", 1\n", + "il 1\n", + ") 1\n", + "5 0\n", + "donald 0\n", + "harris 0\n", + "texas 0\n", + "rangers 0\n", + "of 0\n", + "texas 1\n", + "tech 1\n", + "university 1\n", + "6 0\n", + "paul 0\n", + "coleman 0\n", + "saint 0\n", + "louis 0\n", + "cardinals 0\n", + "of 0\n", + "franks 1\n", + "##ton 1\n", + "( 1\n", + "tx 1\n", + ") 1\n", + "hs 1\n", + "7 0\n", + "frank 0\n", + "thomas 0\n", + "chicago 0\n", + "white 0\n", + "sox 0\n", + "1b 0\n", + "auburn 1\n", + "university 1\n", + "8 0\n", + "earl 0\n", + "cunningham 0\n", + "chicago 0\n", + "cubs 0\n", + "of 0\n", + "lancaster 1\n", + "( 1\n", + "sc 1\n", + ") 1\n", + "hs 1\n", + "9 0\n", + "kyle 0\n", + "abbott 0\n", + "california 0\n", + "angels 0\n", + "l 0\n", + "##hp 0\n", + "long 1\n", + "beach 1\n", + "state 1\n", + "university 1\n", + "10 0\n", + "charles 0\n", + "johnson 0\n", + "montreal 0\n", + "expo 0\n", + "##s 0\n", + "c 0\n", + "westwood 1\n", + "hs 1\n", + "( 1\n", + "fort 1\n", + "pierce 1\n", + ", 1\n", + "fl 1\n", + ") 1\n", + "11 0\n", + "calvin 0\n", + "murray 0\n", + "cleveland 0\n", + "indians 0\n", + "3 0\n", + "##b 0\n", + "w 1\n", + ". 1\n", + "t 1\n", + ". 1\n", + "white 1\n", + "high 1\n", + "school 1\n", + "( 1\n", + "dallas 1\n", + ", 1\n", + "tx 1\n", + ") 1\n", + "12 0\n", + "jeff 0\n", + "jude 0\n", + "##n 0\n", + "houston 0\n", + "astros 0\n", + "r 0\n", + "##hp 0\n", + "salem 1\n", + "( 1\n", + "ma 1\n", + ") 1\n", + "hs 1\n", + "13 0\n", + "brent 0\n", + "may 0\n", + "##ne 0\n", + "kansas 0\n", + "city 0\n", + "royals 0\n", + "c 0\n", + "cal 1\n", + "state 1\n", + "fuller 1\n", + "##ton 1\n", + "14 0\n", + "steve 0\n", + "hose 0\n", + "##y 0\n", + "san 0\n", + "francisco 0\n", + "giants 0\n", + "of 0\n", + "fresno 1\n", + "state 1\n", + "university 1\n", + "15 0\n", + "ki 0\n", + "##ki 0\n", + "jones 0\n", + "los 0\n", + "angeles 0\n", + "dodgers 0\n", + "r 0\n", + "##hp 0\n", + "hillsborough 1\n", + "hs 1\n", + "( 1\n", + "tampa 1\n", + ", 1\n", + "fl 1\n", + ") 1\n", + "16 0\n", + "greg 0\n", + "b 0\n", + "##los 0\n", + "##ser 0\n", + "boston 0\n", + "red 0\n", + "sox 0\n", + "of 0\n", + "sara 1\n", + "##so 1\n", + "##ta 1\n", + "( 1\n", + "fl 1\n", + ") 1\n", + "hs 1\n", + "17 0\n", + "cal 0\n", + "el 0\n", + "##dre 0\n", + "##d 0\n", + "milwaukee 0\n", + "brewers 0\n", + "r 0\n", + "##hp 0\n", + "university 1\n", + "of 1\n", + "iowa 1\n", + "18 0\n", + "willie 0\n", + "greene 0\n", + "pittsburgh 0\n", + "pirates 0\n", + "ss 0\n", + "jones 1\n", + "county 1\n", + "hs 1\n", + 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+ "chuck 0\n", + "knob 0\n", + "##lau 0\n", + "##ch 0\n", + "minnesota 0\n", + "twins 0\n", + "2 0\n", + "##b 0\n", + "texas 1\n", + "a 1\n", + "& 1\n", + "m 1\n", + "university 1\n", + "26 0\n", + "scott 0\n", + "burr 0\n", + "##ell 0\n", + "seattle 0\n", + "mariners 0\n", + "r 0\n", + "##hp 0\n", + "ham 1\n", + "##den 1\n", + "( 1\n", + "ct 1\n", + ") 1\n", + "hs 1\n" + ] + } + ], + "source": [ + "for id, prev_label in zip(batch[\"input_ids\"][1], batch[\"token_type_ids\"][1][:,3]):\n", + " if id != 0:\n", + " print(tokenizer.decode([id]), prev_label.item())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cAem9QnIxoKb" + }, + "source": [ + "## Define the model\n", + "\n", + "Here we initialize the model with a pre-trained base and randomly initialized cell selection head, and move it to the GPU (if available).\n", + "\n", + "Note that the `google/tapas-base` checkpoint has (by default) an SQA configuration, so we don't need to specify any additional hyperparameters." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000, + "referenced_widgets": [ + "768723f1af4c4bf497064a9796567382", + "82bfe5d88c5546358de33952e42221a3", + "c6aadbda246d47fcad9660c2f57926a0", + "cd910003940b498e94db9746091e4c3c", + "a11bc2e0d34543d1bb0ab708e0cc1a67", + "d59737fa0a424a90ba02110e4cf1b639", + "d534c2ebdbb144efa59500fcadf6e118", + "f6fef10b29f74c458d05c2cbda46bf4a", + "695d0c44ebbe4a55a17c735645c26c82", + "7e3cd6c49143436bad3d84be7ca2cf79", + "be6159a5be0945629a517297df1170b8", + "b889ffa28a1949e9ac46e205ee582688", + "3c95dd6249784fe6a2a466737e5f5866", + "cf9382ee988f4787a88340d3b2af95f3", + "45fdca8a04f94b43b021c590181e8a48", + "3bad5ab136084c2e92b55153828a403f" + ] + }, + "id": "_OsPodbiDliR", + "outputId": "e2094861-fc6c-42b9-b12b-0f6824ad3048" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5448e41096dc49b1a25147fdf8720f83", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading pytorch_model.bin: 0%| | 0.00/443M [00:00= 0 and col_id >= 0 and segment_id == 1:\n", + " model_label_ids[i] = int(coords_to_answer[(col_id, row_id)])\n", + "\n", + " # set the prev label ids of the example (shape (1, seq_len) )\n", + " token_type_ids_example[:,3] = torch.from_numpy(model_label_ids).type(torch.long).to(device)\n", + "\n", + " prev_answers = {}\n", + " # get the example\n", + " input_ids_example = input_ids[idx] # shape (seq_len,)\n", + " attention_mask_example = attention_mask[idx] # shape (seq_len,)\n", + " token_type_ids_example = token_type_ids[idx] # shape (seq_len, 7)\n", + " # forward pass to obtain the logits\n", + " outputs = model(input_ids=input_ids_example.unsqueeze(0),\n", + " attention_mask=attention_mask_example.unsqueeze(0),\n", + " token_type_ids=token_type_ids_example.unsqueeze(0))\n", + " logits = outputs.logits\n", + " all_logits.append(logits)\n", + "\n", + " # convert logits to probabilities (which are of shape (1, seq_len))\n", + " dist_per_token = torch.distributions.Bernoulli(logits=logits)\n", + " probabilities = dist_per_token.probs * attention_mask_example.type(torch.float32).to(dist_per_token.probs.device)\n", + "\n", + " # Compute average probability per cell, aggregating over tokens.\n", + " # Dictionary maps coordinates to a list of one or more probabilities\n", + " coords_to_probs = collections.defaultdict(list)\n", + " prev_answers = {}\n", + " for i, p in enumerate(probabilities.squeeze().tolist()):\n", + " segment_id = token_type_ids_example[:,0].tolist()[i]\n", + " col = token_type_ids_example[:,1].tolist()[i] - 1\n", + " row = token_type_ids_example[:,2].tolist()[i] - 1\n", + " if col >= 0 and row >= 0 and segment_id == 1:\n", + " coords_to_probs[(col, row)].append(p)\n", + "\n", + " # Next, map cell coordinates to 1 or 0 (depending on whether the mean prob of all cell tokens is > 0.5)\n", + " coords_to_answer = {}\n", + " for key in coords_to_probs:\n", + " coords_to_answer[key] = np.array(coords_to_probs[key]).mean() > 0.5\n", + " prev_answers[idx+1] = coords_to_answer\n", + "\n", + " logits_batch = torch.cat(tuple(all_logits), 0)\n", + "\n", + " return logits_batch" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "id": "jflxDE_BfVg9" + }, + "outputs": [], + "source": [ + "data = {'Actors': [\"Brad Pitt\", \"Leonardo Di Caprio\", \"George Clooney\"],\n", + " 'Age': [\"56\", \"45\", \"59\"],\n", + " 'Number of movies': [\"87\", \"53\", \"69\"],\n", + " 'Date of birth': [\"7 february 1967\", \"10 june 1996\", \"28 november 1967\"]}\n", + "queries = [\"How many movies has George Clooney played in?\", \"How old is he?\", \"What's his date of birth?\"]\n", + "\n", + "table = pd.DataFrame.from_dict(data)\n", + "\n", + "inputs = tokenizer(table=table, queries=queries, padding='max_length', return_tensors=\"pt\")\n", + "logits = compute_prediction_sequence(model, inputs, device)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k_a_Y-rDq__o" + }, + "source": [ + "Finally, we can use the handy `convert_logits_to_predictions` function of `TapasTokenizer` to convert the logits into predicted coordinates, and print out the result:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "id": "5fAcNOVsqoVD" + }, + "outputs": [], + "source": [ + "predicted_answer_coordinates, = tokenizer.convert_logits_to_predictions(inputs, logits.cpu().detach())" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 254 + }, + "id": "QP4AHMxFujhV", + "outputId": "aed2fc99-957b-4b9f-e804-b426a80de8df" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ActorsAgeNumber of moviesDate of birth
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" + ], + "text/plain": [ + " Actors Age Number of movies Date of birth\n", + "0 Brad Pitt 56 87 7 february 1967\n", + "1 Leonardo Di Caprio 45 53 10 june 1996\n", + "2 George Clooney 59 69 28 november 1967" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "How many movies has George Clooney played in?\n", + "Predicted answer: \n", + "How old is he?\n", + "Predicted answer: Brad Pitt, Leonardo Di Caprio, George Clooney\n", + "What's his date of birth?\n", + "Predicted answer: 7 february 1967, 10 june 1996, 28 november 1967\n" + ] + } + ], + "source": [ + "# handy helper function in case inference on Pandas dataframe\n", + "answers = []\n", + "for coordinates in predicted_answer_coordinates:\n", + " if len(coordinates) == 1:\n", + " # only a single cell:\n", + " answers.append(table.iat[coordinates[0]])\n", + " else:\n", + " # multiple cells\n", + " cell_values = []\n", + " for coordinate in coordinates:\n", + " cell_values.append(table.iat[coordinate])\n", + " answers.append(\", \".join(cell_values))\n", + "\n", + "display(table)\n", + "print(\"\")\n", + "for query, answer in zip(queries, answers):\n", + " print(query)\n", + " print(\"Predicted answer: \" + answer)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6L0KBaPjG7uj" + }, + "source": [ + "Note that the results here are not correct, that's obvious since we only trained on 28 examples and tested it on an entire different example. In reality, you should train on the entire dataset. The result of this is the `google/tapas-base-finetuned-sqa` checkpoint." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Y4S-TIGSvqhZ" + }, + "source": [ + "## Legacy\n", + "\n", + "The code below was considered during the creation of this tutorial, but eventually not used." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ox1ZECiJ5vSD" + }, + "outputs": [], + "source": [ + "# grouped = data.groupby(data.position)\n", + "# test = grouped.get_group(0)\n", + "# test.index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "L0IuO6vivrw_" + }, + "outputs": [], + "source": [ + "def custom_collate_fn(data):\n", + " \"\"\"\n", + " A custom collate function to batch input_ids, attention_mask, token_type_ids and so on of different batch sizes.\n", + "\n", + " Args:\n", + " data:\n", + " a list of dictionaries (each dictionary is what the __getitem__ method of TableDataset returns)\n", + " \"\"\"\n", + " result = {}\n", + " for k in data[0].keys():\n", + " result[k] = torch.cat([x[k] for x in data], dim=0)\n", + "\n", + " return result\n", + "\n", + "class TableDataset(torch.utils.data.Dataset):\n", + " def __init__(self, df, tokenizer):\n", + " self.df = df\n", + " self.tokenizer = tokenizer\n", + "\n", + " def __getitem__(self, idx):\n", + " item = self.df.iloc[idx]\n", + " table = pd.read_csv(table_csv_path + item.table_file[9:]).astype(str) # TapasTokenizer expects the table data to be text only\n", + " if item.position != 0:\n", + " # use the previous table-question pair\n", + " previous_item = self.df.iloc[idx-1]\n", + " encoding = self.tokenizer(table=table,\n", + " queries=[previous_item.question, item.question],\n", + " answer_coordinates=[previous_item.answer_coordinates, item.answer_coordinates],\n", + " answer_text=[previous_item.answer_text, item.answer_text],\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " # remove the batch dimension which the tokenizer adds\n", + " encoding = {key: val[-1] for key, val in encoding.items()}\n", + " #encoding = {key: val.squeeze(0) for key, val in encoding.items()}\n", + " else:\n", + " # this means it's the first table-question pair in a sequence\n", + " encoding = self.tokenizer(table=table,\n", + " queries=item.question,\n", + " answer_coordinates=item.answer_coordinates,\n", + " answer_text=item.answer_text,\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + " )\n", + " return encoding\n", + "\n", + " def __len__(self):\n", + " return len(self.df)\n", + "\n", + "train_dataset = TableDataset(df=grouped, tokenizer=tokenizer)\n", + "train_dataloader = torch.utils.data.DataLoader(train_dataset, batch_size=2, collate_fn=custom_collate_fn)" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "name": "Fine-tuning TapasForQuestionAnswering on SQA.ipynb", + "provenance": [], + "toc_visible": true + }, + 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/dev/null and b/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows.xlsx differ diff --git a/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.csv b/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.csv new file mode 100644 index 0000000000000000000000000000000000000000..e2435730cbbfa2c11e3552758e7d7d9ee6b28e4c --- /dev/null +++ b/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.csv @@ -0,0 +1,16 @@ +Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I +Information Processing within Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of the structure and the application areas of business management information systems in enterprises and public institutions.Outline of syllabus:1. What is software: concepts, categories, application2. Software life cycle: duration, phases, steps3. As-is analysis: tasks, problems4. To-be concept: system design, data design, dialog design, function design5. Object orientation: paradigm shift6. Change management: meaning, methodologies, project management7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to(i) understand the importance of integration in enterprises, especially in information systems;(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require-ments, which brings a software implementation with;(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply (with participation in the exercise);(iv) understand the importance of change management and project management and know the appropriate me-thods for specific applications.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage-ment.Outline of syllabus:1. Organisation and distinction2. IT strategy3. IT organisation4. Management of IT systems5. Enterprise Architecture Management6. IT project management7. IT security8. IT law9. IT controllingReading:• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden.• Tiemeyer: Handbuch IT-Management, Munich.• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to1. overview the different aspects to be considered regarding a purposeful IT management;2. understand and apply appropriate methods and tools;3. independently perform system search and selection in a team project (only after participation in the practice lessons).",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content:In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analy-sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen-dently and will only receive advice and minor support from research assistants.Reading:will vary according to topic","After completing the course ""Projektseminar"", students will be able to1. analyze business tasks and requirements and generate fitting IS solutions;2. apply project management methods;3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1Language of assessment: German, EnglishCreditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua-ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me-thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).",The students possess theoretical and practical knowledge in the area of information retrieval and have acquired the technical know-how to create a search engine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo-dern computer systems, as well as the measures implemented to protect against these attacks. In the course, the following topics are discussed:• x86-64 instruction set architecture and assembly language• Runtime attacks (code injection, code reuse, defenses)• Web security• Blockchains and smart contracts• Side-channel attacks• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con-cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci-ses allow students to gain hands-on experience with attacks and analysis of systems from an attackers perspec-tive.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, LR, HCI, ES.Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,The students possess a fundamental and applicable knowledge about advanced topics in software engineering with a focus on modern software architectures and fundamental approaches to model-driven software enginee-ring.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia-bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of measured data, planning and evaluation of simulation experiments, special random processes, possibilities and limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of (technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu-lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro-grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co-de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis-cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par-allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces-sing.",V (2) + Ü (2)Module taught in: English,written examination (90 to 120 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de-tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili-stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing mostly for English. They are able to solve problems through the methods taught. They have gained experience in the application of text mining algorithms.",The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing. They are able to solve practical problems with the methods acquired in class. They have gained experience in the application of text mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important basics as well as the most recent approaches to image representation, image processing and image analysis are taught. Actual models and methods of machine learning as well as their technical backgrounds are presented and their respective applications in image processing are shown.",Students have fundamental knowledge of problems and techniques in the field of computer vision and are able to independently identify and apply suitable methods for concrete problems.,V (2) + Ü (2)Module taught in: English,"Written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- diff --git a/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx b/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..2ff8fc7f77bae9d402716a2f65c5695fc6c69f27 Binary files /dev/null and b/04_finetuning_approaches/MS_IS_all_modules_orginal_15_rows_cleaned.xlsx differ diff --git a/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean.xlsx b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..a00295f6bdf315d318a01a0d3638c95a4a3ef45d Binary files /dev/null and b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean.xlsx differ diff --git a/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.csv b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.csv new file mode 100644 index 0000000000000000000000000000000000000000..367d9840612cbaec55eea23a48b558e98a55b08c --- /dev/null +++ b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.csv @@ -0,0 +1,121 @@ +Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I +Information Processing within Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of the structure and the application areas of business management information systems in enterprises and public institutions.Outline of syllabus:1. What is software: concepts, categories, application2. Software life cycle: duration, phases, steps3. As-is analysis: tasks, problems4. To-be concept: system design, data design, dialog design, function design5. Object orientation: paradigm shift6. Change management: meaning, methodologies, project management7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to(i) understand the importance of integration in enterprises, especially in information systems;(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require-ments, which brings a software implementation with;(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply (with participation in the exercise);(iv) understand the importance of change management and project management and know the appropriate me-thods for specific applications.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content:This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage-ment.Outline of syllabus:1. Organisation and distinction2. IT strategy3. IT organisation4. Management of IT systems5. Enterprise Architecture Management6. IT project management7. IT security8. IT law9. IT controllingReading:• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden.• Tiemeyer: Handbuch IT-Management, Munich.• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to1. overview the different aspects to be considered regarding a purposeful IT management;2. understand and apply appropriate methods and tools;3. independently perform system search and selection in a team project (only after participation in the practice lessons).",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content:In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analy-sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen-dently and will only receive advice and minor support from research assistants.Reading:will vary according to topic","After completing the course ""Projektseminar"", students will be able to1. analyze business tasks and requirements and generate fitting IS solutions;2. apply project management methods;3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1Language of assessment: German, EnglishCreditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua-ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me-thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).",The students possess theoretical and practical knowledge in the area of information retrieval and have acquired the technical know-how to create a search engine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo-dern computer systems, as well as the measures implemented to protect against these attacks. In the course, the following topics are discussed:• x86-64 instruction set architecture and assembly language• Runtime attacks (code injection, code reuse, defenses)• Web security• Blockchains and smart contracts• Side-channel attacks• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con-cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci-ses allow students to gain hands-on experience with attacks and analysis of systems from an attackers perspec-tive.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, LR, HCI, ES.Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,The students possess a fundamental and applicable knowledge about advanced topics in software engineering with a focus on modern software architectures and fundamental approaches to model-driven software enginee-ring.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia-bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of measured data, planning and evaluation of simulation experiments, special random processes, possibilities and limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of (technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu-lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro-grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co-de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis-cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par-allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces-sing.",V (2) + Ü (2)Module taught in: English,written examination (90 to 120 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de-tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili-stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing mostly for English. They are able to solve problems through the methods taught. They have gained experience in the application of text mining algorithms.",The students possess theoretical and practical knowledge about typical methods and algorithms in the area of text mining and language processing. They are able to solve practical problems with the methods acquired in class. They have gained experience in the application of text mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).creditable for bonusLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important basics as well as the most recent approaches to image representation, image processing and image analysis are taught. Actual models and methods of machine learning as well as their technical backgrounds are presented and their respective applications in image processing are shown.",Students have fundamental knowledge of problems and techniques in the field of computer vision and are able to independently identify and apply suitable methods for concrete problems.,V (2) + Ü (2)Module taught in: English,"Written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: German and/or English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: EnglishCreditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in-formation systems and social media in the World Wide Web, but also for various social, economic and biologi-cal systems. What can we learn from data that capture the interaction topology of such complex systems? What is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most influential actors in a social network? And how can we analyze time series data on systems with dynamic net-work topologies?Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari-ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha-stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma-terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri-ven modelling of complex technical, social, and biological systems. Students will understand how we can quan-titatively model the topology of networked systems and how we can detect and characterize topological pat-terns. Participants will learn how to use analytical methods to make statements about the expected properties of very large networks that are generated based on different stochastic models. They further gain an analytical un-derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree distributions influence the robustness of systems, and how emergent network features emerge from simple ran-dom processes.",V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: German and/or English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,"written examination (approx. 60 to 120 minutes)If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, SVM), learning methods for special data types, further learning paradigms.",The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da-ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use or implementation of data mining algorithms.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IT,KI,HCI,GE,SEC",150 h,--,-- +Business Software 1: IS-based Enterprise Management,12-GPU-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This module provides students with an overview of the structure of a business information system (SAP Business ByDesign) in depth.Outline of syllabus:1. Integrated information systems: integration, standard software, system architecture2. Working with standard business software3. Consulting in integrated information systems: project management, project organisation, presentation skillsDescription:The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the software, dealing with a wide variety of business processes.If you would like to register for this course, please submit an application to the consultants (cover letter, CV, cer-tificates; please also specify your degree programme and student ID number).","After completing the course ""Business Software 1"", students will be able to(i) understand an ERP system in its depth;(ii) understand the interaction of business processes;(iii) execute business tasks and processes in an ERP system independently (after participation in the practice lessons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orc) Term paper (15 to 20 pages) orCreditable for bonusLanguage of assessment: German and/or EnglishAssessment offered: Once a year, winter semester","20 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Software 2: Enterprise Resource Planning Systems,12-M-ERP-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content:This module provides students with an overview of the structure of business information systems in width as well as the selection and implementation of business information systems in organisations.Outline of syllabus:1. Integrated information systems: integration, standard software, system architectures, operating models2. Selection of integrated information systems: methods, cost-benefit analysis3. Implementation of integrated information systems: project management, project organisation, project marke-tingThe lecture will be accompanied by an exercise that will present students with an opportunity to access, in small groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the software, dealing with a wide variety of business processes.","After completing the course ""Business Software 2"", students will be able to1. differentiate between system architectures and -philosophies;2. understand the interaction of business processes;3. come to a selection decision for an ERP system using a structured approach and compare different ERP sy-stems;4. execute business tasks and processes in an ERP system independently (after participation in the practice les-sons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orc) Term paper (15 to 20 pages) orCreditable for bonusLanguage of assessment: German and/or EnglishAssessment offered: Once a year, summer semester","20 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Advanced Seminar: Enterprise Systems,12-M-ES-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the fields of informati-on systems and enterprise systems.Reading:will vary according to topic","After completing the course ""Enterprise Systems"", students will be able to1. understand the fundamentals of scientific literature reviews;2. integrate elaborated content in a scientific thesis;3. create presentations independently.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Decision Support Systems,12-M-DSS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,The course discusses advanced approaches for modelling and solving decision problems in business settings. The acquired insights are used to design and implement decision support systems using standard software tools (Python).,"After successfully completing the course, students should be able to• Understand the structure of classic business decision problems• Isolate key elements from general problem descriptions and convert them to quantitative decision models• Solve different classes of optimization problems (linear, network, integer, multi-objective, non-linear, stochastic)• Implement decision support systems",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)Creditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Analytical Information Systems,12-BI-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course provides an overview of the structure and applications of analytical information systems. A special fo-cus is on individual quantitative methods of data analysis. On the one hand, methods from the areas of data pre-paration and data manipulation as well as their practical application are introduced. On the other hand, an intro-duction to methods and the application of machine learning methods for predictive analytics, in particular neural networks and deep learning, is given.",The module provides students with knowledge of:• Data Manipulation• Data Engineering• Descriptive Analytics• Predictive Analytics and Data Mining• Supervised Learning• Unsupervised Learning• Neural Networks and Deep Learning• Text Mining• Big Data Technologies,V (2) + Ü (2),Written examination (approx. 60 Minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.WM1:Should the number of applications exceed the number of available places, places will be allocated as follows:1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Analytics,12-M-BUA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the field of business management decision models and methods and their application in the development of decision-support sy-stems as well as analytical information systems and quantitative methods of data analysis.Students work on current topics using methods from machine learning, mathematical optimization and simulati-on.",The module provides students with knowledge of:• Scientific literature• Implementation of methods in code• Integration of developed results in scientific papers• Creating presentations and lectures,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +E-Business Strategies,12-M-IBS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of strategic implications of digital technologies at the level of organisations, industries and value networks. To this end, concepts and frameworks from strategic technology management are applied to digital innovations and illustrated with numerous examples. In the accompanying exercise, case stu-dies of well-known digital companies and their business models are analysed and discussed.",- Understand theoretical concepts of strategy development and implementation in the context of digital techno-logies.- Apply different frames of reference and understand their strengths and weaknesses in the context of practical application.- Transfer the concepts to real business situations,V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orCreditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Mobile and Ubiquitous Systems,12-M-MUS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of technologies and business applications of mobile & ubiquitous computing. Concepts and applications are illustrated using numerous examples from mobile telecommunications to the In-ternet of Things. In the accompanying exercise, corresponding case study texts are analysed and discussed.","- Understand the technological basics of mobile & ubiquitous computing.- Analysing business applications in processes, products/services and business models- Apply the concepts learned to real-life problems in a business context",Ü (2) + V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Seminar: E-Business Strategies,12-M-SEBS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc-tured term paper and to present the results of their work with the help of relevant topics in the fields of web-ba-sed platforms (electronic markets, Web 2.0 etc.) and strategic management of a company.",- Academic literature review- Integration of developed results in scientific papers- Creating presentations and talks,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Corporate Entrepreneurship,12-M-UGF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,This module is a theory-led and practice-oriented primer on corporate entrepreneurship. It provides you with knowledge useful for anyone aiming at working (or researching) in the field of corporate innovation and entrepre-neurship or at pursuing an ‘intrapreneurial’ or entrepreneurial career.(1) Introduction to corporate entrepreneurship(2) Antecedents and forms of corporate entrepreneurship(3) Corporate strategy and corporate entrepreneurship(4) Organizational structure and corporate entrepreneurship(5) Human resource management and corporate entrepreneurship(6) Building supportive organizational cultures(7) Entrepreneurial control systems(8) Entrepreneurial leadership(9) The corporate entrepreneur as a champion and diplomat(10) The pay-off from corporate entrepreneurship(11) Corporate venture capital(12) Corporate entrepreneurship in nonprofit and government organizations(13) Universities and academic spin-offs(14) Wrap-up and Q&A,Educational aims• Clarify the role of corporate entrepreneurship• Explain theoretical concepts and mechanisms behind corporate entrepreneurship• Enable students to critically appraise alternative approaches to corporate entrepreneurship• Enable students to evaluate the boundaries and risks of corporate entrepreneurshipLearning outcomesOn successful completion of this module students will be able to:• Create and evaluate concepts related to corporate entrepreneurship• Assess the role of corporate entrepreneurship for creating and sustaining competitive advantage• Make judgements about the organizational and managerial implications of corporate entrepreneurship• Systematically choose between different routes of action,V (2) + Ü (2)Module taught in: English,"a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, groups of 3 approx. 30 minutes)Language of assessment: English",--,--,150 h,--,-- +Digital Entrepreneurship,12-M-UGF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,This module provides an introduction into digital entrepreneurship and digital transformation. (1) Introduction (2) Digital business models (3) Identifying and exploiting opportunities for digital entrepreneurship (4) Strategies for creating competitive advantage in digital entrepreneurship (5) Digital marketing for entrepreneurs (6) Crowd-funding for entrepreneurs (7) Design thinking (8) Lean startup (9) Platform ecosystems and online communities (10) Digital strategy and digital transformation (11) The agile organization (12) Crowdsourcing (13) Cyberfraud (14) Wrap-up and Q&A,"Educational aims: Clarify the role of digital entrepreneurship and digital transformation. Explain theoretical con-cepts and mechanisms behind digital entrepreneurship and digital transformation. Enable students to critically appraise alternative approaches to digital entrepreneurship and digital transformation. Enable students to eva-luate the boundaries and risks of digital entrepreneurship and digital transformationLearning outcomes: On successful completion of this module students will be able to (1) Assess the role of di-gital entrepreneurship and digital transformation for creating and sustaining competitive advantage, (2) Crea-te and evaluate concepts related to digital entrepreneurship and digital transformation, (3) Make judgements about the organizational and managerial implications of digital entrepreneurship and digital transformation, (4) Systematically choose between different routes of action.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) log (15 to 20 pages) or c) oral examination (one candida-te each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: English,--,--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation and present the key insights from their work.",Educational aims• Enable students to position their research• Enable students to critically review a substantial body of literature in short time• Enable students to develop a sound theoretical framework• Enable students to create a research paper fully meeting academic standardsLearning outcomesOn successful completion of this module students will be able to:• Differentiate their research from previous work• Adopt theoretical perspectives to understand complex phenomena• Engage in comprehensive academic reasoning• Articulate abstract and complex phenomena and relationships in written and oral form,S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Global Logistics & Supply Chain Management,12-M-GLSC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Global Logistics & Supply Chain Management"" acquaints students with advanced methods for the planning of global production networks and demonstrates the application of these with the help of multiple case studies.",After completing this course students can(i) analyze and evaluate global production networks;(ii) develop and apply appropriate methods to plan production networks;(iii) evaluate the consequences of uncertainties in processes and apply concepts and methods to plan uncertain processes.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Advanced Operations & Logistics Management,12-M-AOLM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Advanced Operations & Logistics Management"" acquaints students with advanced methods for the planning of integrated production and logistics systems and demonstrates the application of these with the help of multiple case studies","After completing this course students can(i) analyze and evaluate integrated production and logistics systems;(ii) develop and apply appropriate methods to plan complex production and logistics systems;(iii) evaluate the consequences of uncertainties in processes, and(iv) apply concepts and methods to plan uncertainties processes.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Seminar: Operations Management,12-M-SN-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"With the help of topics from the area of ""Operations Management"", this course will provide students with know-ledge and skills that will enable them to prepare a well-structured term paper and to present the key results of their work.",Students will learn how to convince a critical audience by giving a presenation regarding a topic from the area of Operations Management. By developing and giving a presentation as well as by answering questions the stu-dents will practice their skills to deal with difficult communication situations and to argument for and against a certain topic.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English",--,--,300 h,--,-- +Adaption and Continuous System Engineering,12-ACSE-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Business Suite: The constantly changing environment with its organisational and IT-oriented developments forces companies to adapt their standard business software solutions. With the help of dynamic adaptation (Continuous System Engineering), this process of change can be supported effectively and efficiently. This mo-dule discusses both the systematic implementation of adaptation steps (so-called customising) using the exam-ple of the mySAP Business Suite and the concept of Continuous System Engineering using various practical ex-amples. Business Apps: The course combines theory and practice in the area of cloud computing and ERP. Par-ticipants gain an insight into the architecture of the ByDesign platform and are presented with an opportunity to gain practical experience working with the corresponding software development kit.Content:• Fundamentals of cloud computing• Cloud business solutions• Architecture of the SAP Business ByDesign platform• Platform adaption and extensibility• Basics of software development in SAP Cloud Applications Studio• Hands-on SDK: independently designing and developing a demo app","Business Suite: Students learn about the various ways of adapting a standard business software solution to the special requirements of a company. They also develop a fundamental understanding of the dynamic adaptation of business software libraries. Based on selected examples from the SAP Business Suite that the acquired know-ledge will be deepened by using case studies. Business Apps: The course imparts knowledge and delivers skills in cloud computing for businesses, ERP systems architecture and software development at the example of the SAP Business ByDesign platform. The independent planning, implementation and documentation of a business app trains important core competencies of technology-oriented Business Informatics.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) oral examination (one can-didate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Business Service Platforms 2,12-AGP2-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The next generation of business service platforms leads to a transformation of traditional industrial enterprises into service businesses that generate a large proportion of value in developed economies. New ICT technologies such as cloud computing, the Internet of Things and semantic technologies will contribute to the success of the-se businesses in a similar way as ERP contributed to the success of industrial enterprises. But we are still at the beginning of the evolution of business service platforms, which will have to become more adaptable to support special business models and allow differentiating customer service processes.The course will discuss different case studies on services businesses. The digital transformation of the software industry into a service industry is the most prominent of these case.","Be aware of the growing economic importance of the service sector. Understand that services businesses in are facing a special productivity problem, which could not be adressed by the same processes applied in the ma-nufacturing industries. Understand the new ICT technologies we have at hand today to deliver smart solutions for this problem. Be aware of the diversity of services business today where we have no evidence that a general standard can be found applicable to most subsectors similar to the standardization achieved for the manufactu-ring industries after twenty years of research.",V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,--_x000C_ +Business Service Platforms 1,12-BSA-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"A next generation of enterprise systems called business service platforms is emerging using new disruptive tech-nologies such as cloud computing, big data and mobility. These business service platforms apply the concept of product platforms to software. They will1. be services based2. be offered as a service in the cloud3. address new classes of users and types of business especially in the service business4. allow for a high degree of business adaptability and extensibility.5. be supplemented by a broad offer of partner add-ons supporting accelerated innovation.These new business service platforms will play a key role in the digital transformation of the software industry.",Be aware of the big business productivity progress enabled by BIS in the last 50 years. Understand the limitati-ons of these systems in spite of the digital transformation of the software industry ahead. Be able to critically as-sess the business potential of new IC technologies. Understand the business demand for change. Understand the necessary organizational learning needed to leverage new technology for business change management.,V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +"Business Processes Organisation, Business Software and Process Industries",12-GLP-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"ERP systems have become key elements of successful companies. Business processes in companies can no lon-ger be managed without using such ERP systems. In financial departments of companies, such systems have be-en used for a long time, but business processes e. g. for logistical tasks have so far not been supported by ERP solutions. This module explains how this issue could be resolved as well as what constraints and what depen-dencies have to be considered.","After completing this module, students should be able to(i) know about actual business processes in companies;(ii) understand selected problems in the organization and design of logistical business processes and work out solutions;(iii) know and design basic data structures and data flows of an ERP system;(iv) map businesss processes within an ERP system;(v) consider the specifics of a certain industry (e. g. the process industry) when organizing business processes;(vi) map the core business processes within an ERP system.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Work and Information,12-ITA-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This module discusses relevant principles, concepts and applications of business information processing and its impact on organisational and process structures in todays business world.","The expertise gained from other modules related to business management issues can be interpreted and clas-sified in a certain way by participating in this module. For decisions in regards to human resources planning, in-vestment, and a companys strategy, the students will get to know all the relevant concepts and interdependen-cies, which come with taking information processing into account as the so called ""fourth"" factor of production.",V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Work Order Planning for Automated Manufacturing,12-M-AGAF-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The idea of integration of business information systems is primarily practiced and developed as an ERP system in terms of business application areas, their temporal overlap (data warehouse), their spatial relationship (sup-ply network) and connection of legal tasks (eGovernment). However, linking the commercial view of incoming cu-stomer orders with the logistic or more technical view of the scheduling of production orders and the resulting consequences for the processes is a critical success factor.",Linking research and lectures of the Institute of Robotics and Telematics as well as the orientation of the Chair of Business Integration allows students a conceptual as well as practical insight into the challenges of this in the future essential part of the operational automation development.,V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Topics in Business Information Systems 1,12-M-ATW1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Topics in Business Information Systems 2,12-M-ATW2-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Information systems research,12-M-ISR-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The course provides an overview of theoretical scientific foundations, theories, research topics and methods of international research in business informatics.","The module provides students with knowledge of:(i) Exploration of classical themes of WI / IS research;(ii) Getting to know the relevant paradigms, theories and methods;(iii) Recognition of the interfaces to other areas of business administration and management practice;(iv) Gain experience in finding and evaluation of scientific literature",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 15 to 20 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)Creditable for bonusLanguage of assessment: German and/or English","40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Databases 2,10-I=DB2-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Data warehouses and data mining; web databases; introduction to Datalog.,"The students have advanced knowledge about relational databases, XML and data mining.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, HCI.",150 h,--,-- +Compiler Construction,10-I=CB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Lexical analysis, syntactic analysis, semantics, compiler generators, code generators, code optimisation.","The students possess knowledge in the formal description of programming languages and their compilation. They are able to perform transformations between them with the help of finite automata, push-down automata and compiler generators.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,GE",150 h,--,-- +Artificial Intelligence 2,10-I=KI2-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Planning, probabilistic closure and Bayesian networks, utility theory and decidability problems, learning from observations, knowledge while learning, neural networks and statistical learning methods, reinforcement lear-ning, processing of natural language.","The students possess theoretical and practical knowledge about artificial intelligence in the area of probabilistic closure, learning and language processing and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,SE,IS,HCI,GE",150 h,--,-- +E-Learning,10-I=EL-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Learning paradigms, learning system types, author systems, learning platforms, standards for learning systems, intelligent tutoring systems, student models, didactics, problem-oriented learning and case-based training sy-stems, adaptive tutoring systems, computer-supported cooperative learning, evaluation of learning systems.",The students possess a theoretical and practical knowledge about eLearning and are able to assess possible ap-plications.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,HCI,GE",150 h,--,-- +Professional Project Management,10-I=PM-182-m01,Institute of Computer Science,holder of the Chair of Computer Science III,5,numerical grade,1 semester,graduate,"Project goals, project assignment, project success criteria, business plan, environment analysis and stakeholder management, initialisation, definition, planning, execution/control, finishing of projects, reporting, project com-munication and marketing, project organisation, team building and development, opportunity and risk manage-ment; conflict and crisis management, change and claim management; contract and procurement management, quality management, work techniques, methods and tools; leadership and social skills in project management, program management, multiproject management, project portfolio management, PMOs; peculiarities of software projects; agile project management/SCRUM, combination of classic and agile methods.","The students possess practically relevant knowledge about the topics of production management and/or pro-fessional project management. They are familiar with the critical success criteria and are able to initiate, define, plan, control and review projects.",V (4),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +Algorithms for Geographic Information Systems,10-I=AGIS-161-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Algorithmic foundations of geographic information systems and their application in selected problems of acqui-sition, processing, analysis and presentation of spatial information. Processes of discrete and continuous opti-misation. Applications such as the creation of digital height models, working with GPS trajectories, tasks of spa-tial planning as well as cartographic generalisation.",The students are able to formalise algorithmic problems in the field of geographic information systems as well as to select and improve suitable approaches to solving these problems.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):AT,IS,HCI",150 h,--,-- +Real-Time Interactive Systems,10-HCI=RIS-182-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"This course provides an introduction into the requirements, concepts, and engineering art of highly interactive human-computer systems. Such systems are typically found in perceptual computing, Virtual, Augmented, Mixed Reality, computer games, and cyber-physical systems. Lately, these systems are often termed Real-Time Interac-tive Systems (RIS) due to their common aspects.The course covers theoretical models derived from the requirements of the application area as well as common hands-on and novel solutions necessary to tackle and fulfill these requirements. The first part of the course will concentrate on the conceptual principles characterizing real-time interactive systems. Questions answered are: What are the main requirements? How do we handle multiple modalities? How do we define the timeliness of RIS? Why is it important? What do we have to do to assure timeliness? The second part will introduce a concep-tual model of the mission-critical aspects of time, latencies, processes, and events necessary to describe a sy-stems behavior. The third part introduces the application state, its requirements of distribution and coherence, and the consequences these requirements have on decoupling and software quality aspects in general. The last part introduces some potential solutions to data redundancy, distribution, synchronization, and interoperability.Along the way, typical and prominent state-of-the-art approaches to reoccurring engineering tasks are discussed. This includes pipeline systems, scene graphs, application graphs (aka field routing), event systems, entity and component models, and others. Novel concepts like actor models and ontologies will be covered as alternative solutions. The theoretical and conceptual discussions will be put into a practical context of todays commercial and research systems, e.g., X3D, instant reality, Unity3d, Unreal Engine 4, and Simulator X.","After the course, the students will have a solid understanding of the boundary conditions defined by both, the physiological and psychological characteristics of the human users as well as by the architectures and technolo-gical characteristics of todays computer systems. Participants will gain a solid understanding about what they can expect from todays technological solutions. They will be able to choose the appropriate approach and tools to solve a given engineering task in this application area and they will have a well-founded basis enabling them to develop alternative approaches for future real-time interactive systems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): HCI.Cf. Section 3 Subsection 3 Sentence 8 FSB (subject-specific provisions).",150 h,--,-- +Logic Programming,10-I=LP-172-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Logic-relational programming paradigm, top-down evaluation with SLD(NF) resolution. Introduction to the logic programming language Prolog: recursion, predicate-oriented programming, backtracking, cut, side effects, ag-gregations. Connection to (deductive) databases. Comparison with Datalog, short introduction of advanced con-cepts like constraint logic programming.","The students have fundamental and practicable knowledge of logic programming. They are able to implement compact and declarative programs in Prolog, and to compare this approach to the traditional imperative pro-gramming paradigm.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, SE, IT, IS.",150 h,--,-- +Machine Learning for Natural Language Processing,10-I=NLP-182-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture conveys advanced knowledge about methods in computational text processing. To this end, it pres-ents state of the art models and techniques in the area of machine learning, as well as their technical back-ground, and their respective applications in Natural Language Processing. As one important building block of almost all modern NLP-models, different techniques for learning representations of words, so called Word Em-beddings, are presented. Starting from this we cover, among others, models from the area of Deep Learning, li-ke CNNs, RNNs and Sequence-to-Sequence architectures. The theoretical foundations of these models, like their training with Backpropagation, are also covered in depth. For all models presented in the lecture, we show their application to problems like sentiment analysis, text generation and machine translation in practice.",The participants have solid knowledge on problems and methods in the area of computational text processing and are able to identify and apply suitable methods for a specific task.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, IS, HCI.",150 h,--,-- +Medical Informatics,10-I=MI-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Electronic patient folder, coding of medical data, hospital information systems, operation of computers in infir-mary and functional units, medical decision making and assistance systems, statistics and data mining in medi-cal research, case-based training systems in medical training.",The students possess theoretical and practical knowledge about the application of computer science methods in medicine.,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,IS,HCI,GE",150 h,--,-- +Performance Engineering & Benchmarking of Computer Systems,10-I=PEB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Introduction to performance engineering of commercial software systems, performance measurement techni-ques, benchmarking of commercial software systems, modelling for performance prediction, case studies.","The students possess a fundamental and applicable knowledge in the areas of performance metrics, measure-ment techniques, multi-factorial variance analysis, data analysis with R, benchmark approaches, modelling with queue networks, modelling methods, resource demand approximation, petri nets.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits):SE,IT,ES,HCI,GE",150 h,--,-- +Programming with neural nets,10-I=PNN-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite-rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IT, IS, HCI, GE.",150 h,--,-- +Robotics 1,10-I=RO1-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VII,8,numerical grade,1 semester,graduate,"History, applications and properties of robots, direct kinematics of manipulators: coordinate systems, rotations, homogenous coordinates, axis coordinates, arm equation. Inverse kinematics: solution properties, end effec-tor configuration, numerical and analytical approaches, examples of different robots for analytical approaches. Workspace analysis and trajectory planning, dynamics of manipulators: Lagrange-Euler model, direct and inver-se dynamics. Mobile robots: direct and inverse kinematics, propulsion system, tricycle, Ackermann steering, ho-lonomes and non-holonome restrictions, kinematic classification of mobile robots, posture kinematic model. Movement control and path planning: roadmap methods, cell decomposition methods, potential field methods. Sensors: position sensors, speed sensors, distance sensors.","The students master the fundamentals of robot manipulators and vehicles and are, in particular, familiar with their kinematics and dynamics as well as the planning of paths and task execution.",V (4) + Ü (2)Module taught in: English,written examination (approx. 60 to 90 minutes)Separate written examination for Masters students.Language of assessment: Englishcreditable for bonus,--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): IS, ES, LR, HCI, GE.",240 h,--,-- +Project - Current Topics in Computer Science,10-I=PRJAK-162-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Completion of a project task (in Teams).,The project allows participants to work on a problem in computer science in teams.,P (4),"project report (10 to 15 pages) and presentation of project (15 to 30 minutes)Each project is offered one time only. The project will not be repeated; there will not be another project with the same topic. Assessment can, therefore, only be offered for the project offered in the respective semester.Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or English",--,"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): AT, SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +International Marketing,12-M-IMM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:The module builds on the knowledge acquired during the Bachelors degree programme or the Grundstudium(stage I studies). It provides a systematic introduction to strategic marketing decisions in global and internatio-nal contexts. These are explained mainly by Porters diamond and cluster models. Another focus is on internatio-nalisation strategies, which require country analyses and decisions on the selection of national markets as well as a timing of the countries market development. In addition, the module discusses different strategies for mar-ket entry and market development.Outline of syllabus:1. Internationalisation of the economy and regional integration processes• Globalisation• Competitiveness of countries, industries and companies in an international context2. International strategic marketing decisions• Market entry forms• Market development strategies• Timing strategies• International organisation structures3. Theories and strategies of internationalisation• Foreign trade theory• Multinational enterprise• Internationalisation strategiesReading:Meffert, H. / Burmann C. / Becker, C.: Internationales Marketing-Management, Stuttgart etc. (most recent editi-on).Berndt, R. / Fantapié-Altobelli C. / Sander M.: Internationales Marketing-Management, Berlin etc. (most recent edition).","Students acquire in-depth skills in the field of strategic and operational management with particular attention to the international context. Students achieve particular expertise in the analysis, assessment and implementation of international business decisions and gain skills thus guiding the execution of marketing and management po-sitions in globally-active companies.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Brand Management & Market Research,12-M-MM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:At the beginning of the 21st century, marketing - until then interpreted as a market-oriented corporate manage-ment approach - was further developed to be seen as the entrepreneurial task of creating ""shared value"" for the organisation on the one hand and - broadly speaking - for society on the other hand. This idea leads to high re-quirements regarding the strategic sustainable positioning of the brand as well as brand management itself.Outline of syllabus:1. Brand leadership and brand assessment2. Brand leadership, identity and relevance according to David Aakers approach3. Brand strategies4. Consumer behaviour5. Market research methods and the development of brand strategies6. Market research methods","Based on the theories of Meffert and Aaker, students will gain a profound understanding for brand leadership, which will be deepened by many pracital implications and examples. Provided by cases studies and market re-search tools, its the defined goal of this lecture to convey an in-depth knowledge for consumer behavior and su-stainable brand management.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Strategic Networks in Industry,12-M-MS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"The primary object of this course is to gain a detailed understanding of strategic networks and of the phenome-non of clustering in the industrial industry. The example of the international automotive industry is used for clari-fication of the theoretical contents.The focus is on marketing in industrial companies and also on CSR - CSR is considered the ""driver"" of sustaina-ble innovations - as well as the different strategy types of sustainable innovations.Outline of syllabus:1. Strategic networks and clusters in industrial industries such as the automotive industry2. Transaction types of Williamson as well as strategic cooperation between automobile manufacturers and sup-pliers3. Management of business types, in particular the business of suppliers in the automotive industry4. Cluster and entrepreneurship activities5. Sustainable innovation strategies","By the end of the course, students gain a profound understanding above the basics of network research. Further-more students will aquire sectoral knowledge of the automotive industry as well as detailed cluster skills.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Strategic Marketing,12-M-SM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description:The module raises awareness in students of the relevance and necessity of strategic management in a competiti-ve and dynamical competitive process.Content:Based on the marketing strategies as well as the stakeholder and entrepreneurship approaches, this module discusses the roots of the concept of strategy in marketing based on Drucker, Porter, Ansoff and Mintzberg. The focus of the module is on thinking in competitive advantages, which is directly related to responsible leadership.Outline of syllabus:1. Competitive dynamics requires strategy and leadership2. Marketing strategies, stakeholder management and entrepreneurship3. Objectives and tasks of corporate governance in management practice4. Competitive forces, strategies and benefits according to Michael Porter5. Growth strategies and marketing myths6. Future technologies, new businesses and dynamic capabilities7. Nature and principles of responsible managementReading:Barnard, CI (1938): The Functions of the Executive, Harvard University Press, Cambridge, Massachusetts.Eschenbach, R.; Eschenbach, S.; Kunesch, H. (2008): Strategische Konzepte: Management-Ansätze von Ansoff bis Ulrich, 5th ed., Schäffer-Poeschel Stuttgart.Freeman, RE (2010): Strategic Management: A Stakeholder Approach, Cambridge University Press.Grant, R. M.; Nippa, M. (2006): Strategisches Management: Analyse, Entwicklung und Implementierung von Un-ternehmensstrategien, 5th ed., Pearson Munich.Hinterhuber, H. H. (2011): Strategische Unternehmensführung -- I. Strategisches Denken, 8th ed., Erich Schmidt Verlag, Berlin.Hungenberg, H. (2012): Strategisches Management in Unternehmen: Ziele -- Prozesse -- Verfahren, 7th ed., Gabler, Wiesbaden.Johnson, G.; Scholes, K.; Whittington, R. (2009): Fundamentals of Strategy, 1st ed., Financial Times and Prentice Hall Harlow.Kotler, P.; Berger, R.; Bickhoff, N. (2010): The Quintessence of Strategic Management, Springer, Heidelberg.Laasch, O.; Conaway RN (2014): The Principles of Responsible Management: Global Sustainability, Responsibili-ty, and Ethics, Cengage Stamford.Meffert, H.; Burmannn, C.; Kirchgeorg, M. (2012): Marketing -- Grundlagen marktorientierter Unternehmensfüh-rung, 11th ed., Gabler, Wiesbaden.Meyer, M. (1995): Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unter-nehmung, Gabler, Wiesbaden.Müller-Stewens, G.; Lechner, C. (2011): Strategisches Management -- Wie strategische Initiativen zum Wandel führen, 4th ed., Schäffer-Poeschel Stuttgart.Porter, M. (1999): Wettbewerb und Strategie, Econ Munich. (Original: Porter, M.: On Competition, Boston, 1998.)Porter, M. (2014): Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frank-furt / New York. (Original: Porter, M.: Competitive Advantage, New York, 1985)Porter, M. (2013): Wettbewerbsstrategie -- Methoden zur Analyse von Branchen und Konkurrenten, 12th ed., Campus, Frankfurt / New York. (Original: Porter, M.: Competitive Strategy, New York, 1980)Welge, M. K.; Al-Laham, A. (2012): Strategisches Management: Grundlagen -- Prozesse -- Implementierung, 6th ed., Springer Wiesbaden.","The students have a deeper understanding of the sustainable corporate management and have the basics of the competitive process and competitive dynamics available. In addition, they can use the acquired knowledge, whi-le taking into account the conventional problems of the strategic and sustainable management, to solve busi-ness case studys on their own.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,-- +Industrial Management 4,12-M-BE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This course will develop the objectives, principles and structure of electronically supported procurement proces-ses with a special focus on catalogue-based procurement systems, electronic tendering systems, electronic (re-verse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management sy-stems.","The students will be able to describe and evaluate both the potentials and goals of electronic supported pro-curement systens and will be able to design appropriate systems for real-life applications. Students will get in-sight into the essentials of operational procurement management, especially e-procurement with a focus on ca-talog-based procurement systems, electronic tendering systems, electronic (reverse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management systems. After completing this mo-dule, students can define and analyze the related tasks and processes and show or develop theory-based and application-oriented possible solutions at a high professional level.",V (2) + Ü (2),"a) Written examination (approx. 40 to 60 minutes) orb) Presentation (approx. 20 Minutes) and term paper (15 to 20 pages), weighted 1:1 orc) Term paper (30 to 40 pages) ord) entirely or partly computerised written examination (approx. 60 minutes) ore) Portfolio (approx. 20 pages)Creditable for bonusLanguage of assessment: German and/or English","20 places.(1) A total of 15 places will be allocated to students of the Masters degree programmes Management as well as International Economic Policy.Should the number of applications exceed 15, these places will be allocated by lot. A waiting list will be maintai-ned and places re-allocated by lot as they become available.(2) A total of 5 places will be allocated to students of the Masters degree programme Information Systems. Should the number of applications exceed 5, these places will be allocated by lot. A waiting list will be maintai-ned and places re-allocated by lot as they become available.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.","Module can be taught in form of E Learning course, seminar, workshop etc.",150 h,--,-- +Industrial Management 2,12-M-LA-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module analyses and classifies approaches of production planning and control. In addition, it develops methods and models of lot sizing and scheduling. The focus is on the determination of optimal production and transport volumes as well as the planning of orders and manufacturing orders.","Students learn essential concepts, principles and methods of production planning and control with emphasis on the determination of optimal production and transport volumes as well as the planning of production and order sequences. Then, based on this expertise related knowledge broadening and deepening, essential competen-cies are conveyed, which allow the imaging of realistic situations and problems using mathematical and quanti-tative models for the derivation and assessment of alternative courses of action. After completion of the modu-le students can answer, analyze and structure questions of production planning and control, goal-oriented. They can also arrange the planning areas in the overall business context and have an in-depth overview of the produc-tion planning and control.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Industrial Management 1,12-M-SBM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"The course addresses central issues of strategic supply management. The supply function of the company (purchasing, materials management, procurement logistics) and its strategic importance is analysed and basic methods are developed that are relevant in this area.","Students learn the principles of performance-oriented optimization of all procurement activities to develop long-term, competitively sensitive potential for success. After completion of the module students are able to prepa-re structured, to goal-oriented analyze and to respond to performance-oriented issues of strategic procurement based on key instruments. Students are able to accurately classify the tasks of the procurement and to describe and discuss their strategic importance and dominate essential methods and procedures used in this area to ap-ply.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Industrial Management 3,12-M-SPM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module will discuss contents and procedures of strategic production management and, in particular, plan-ning and control concepts.Students will become familiar with the essentials of strategic production management. Theoretical and analyti-cal models will be used for analysing both economic and ecological issues. In addition, the module will discuss principles of value structure optimisation and will develop competences regarding the development of integra-ted mathematical models.","After completion of the module students are able to process, to analyze and answer questions of operations strategy structured and goal-oriented in a global context using appropriate methods. Furthermore, they know the main strategic tasks and objectives in production management and evaluate and apply planning and control concepts for the production in realistic application situations.","V (2) + Ü (2)Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to 20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex-amination (approx. 60 minutes) or e) portfolio (approx 20 pages)Language of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Legal Foundations of Risk Management and Compliance,12-M-RM1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,2,numerical grade,1 semester,graduate,"Content: This module analyses the presentation of opportunities and risks in financial reports, i. e. annual or in-terim reports, in conjunction with selected value-based management and profitability analysis approaches.Outline of syllabus:1. Basics of financial reporting and risk management;2. Practice of risk reporting;3. Profitability analysis according to Penman;4. Value-based management and risk management;5. Residual income and business valuation;6. Analysis of equity risk;7. Analysis of credit risk;8. Risk management monitoring by audit committees and auditors.Reading list to be provided in class.","After completing the course, the students will be able1. to present the relation between risk management and financial reporting;2. to analyze and solve independently complex problems with respect to the presentation of opportunities and risk in financial reports based on national and international standards;3. to identify the relation between risks and value-based management;4. to evaluate independently selected research results concerning risk reporting and desing own research- or practice-oriented projects.",V (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,"30 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,60 h,--,-- +Financial Statement Analysis and Business Valuation,12-M-UA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,5,numerical grade,1 semester,graduate,"Fundamental investing involves valuation, and much of the information for valuation is contained in financial statements. This module provides a basic understanding of financial statement analysis, particularly on how to extract value-relevant information from financial statements, carry out financial statement analysis, and use fi-nancial data to value corporations. The module also provides the necessary tools to gain insights into what ge-nerates value in a corporation.","Students can understand publicly traded companies financial statements (US GAAP/IFRS), identify value-rele-vant information in financial statements, and use this information for valuation. They know the relevant techni-ques to evaluate financial statements and understand the fundamental role of financial information in the valua-tion process. Students can apply valuation technics to real-world cases and recommend investment decisions.",V (2) + Ü (2),written examination (approx. 60 to 120 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Philosophy of Science and Ethics in Business Management and Economics,12-M-WEW-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,10,numerical grade,1 semester,graduate,This module will take the form of a seminar. Participants will independently work on a problem in economic poli-cy or will review an important publication on a topic in economics.,Students are able to present the status of a current project in a talk as well as to discuss and defend it.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,300 h,--,-- +Risk Management - Concepts and Systems,12-RM-KS-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Accoun-,5,numerical grade,1 semester,graduate,"Concepts: The course will provide students with an overview of the main goals, contents, methods and instru-ments of opportunity and risk management in industrial and commercial enterprises. Systems: The course will provide students with an overview of the design and functionality of essential information systems for risk mana-gement.","Concepts: After completion of the module students have a sound understanding of basic concepts, processes, methods and tools of risk management. They are able to justify the duties and functions of risk management in the company in theory and practice. They can also evaluate proposed solutions for the design of a risk manage-ment system, analyze selected issues of risk management and building on that, develop their own solutions. Sy-stems: After completing this module, students can(i) judge legal, organizational and methodological requirements for the implementation of risk management pro-cesses in a risk management information system (RMIS);(ii) understand the technical basis for RMIS;(iii) estimate the different characteristics of various information systems for the RM;(iv) understand the workings of RMIS.",V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,"25 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.",--,150 h,--,-- +Discounted Cashflow,12-M-CF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The module covers discounted cash flow (DCF) methods under certainty as well as uncertainty in the context of the valuation of unlevered and levered companies. Furthermore, tax aspects as well as their influence on the company value are considered.Syllabus:1. Introduction2. DCF Theory under certainty1. NPV without taxes2. NPV with personal taxes3. NPV with corporate taxes3. DCF Theory under uncertainty1. DCF basics2. Valuation of unlevered companies3. Valuation of levered companies4. Practice of DCF methods","After completion of this module, the students will know a variety of discounted cashflow techniques and are able to apply properly them in order to evaluate projects or firms.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Portfolio and Capital Market Theory,12-M-CF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module conveys profound knowledge of individual portfolio choices and on this basis the most important capital market theory (namely capital asset pricing model) is introduced, including its assumptions, implications and extensions.Syllabus:1. Modern Portfolio Selection1. 2 Asset-Case2. Multiple-Asset-Case3. Critique of Portfolio Theory2. Capital Asset Pricing Model1. Assumptions and Derivation2. Implications3. Empirical Aspects, Extensions and Alternatives",This module enables the students(i) to explain and to determine the optimal capital market position of an investor given the different investment opportunities and individual utility function;(ii) to understand and use the central CAPM propositions for valuating risky assets.,V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Risk Management and Corporate Finance,12-M-CF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module deals with the valuation and use of classical derivatives in financial markets. In particular, futures, swaps and options are considered as well as their possible applications in the context of financial risk manage-ment. In particular, students will be introduced to the theory involved in pricing options, as well as important va-luation parameters. In addition, some established risk measures such as value-at-risk are discussed.1. Introduction2. Futures & Forwards3. Swaps4. Options5. Measures of risk","Upon completion of this module students will be able to,(i) independently determine the fair value of the derivatives discussed, as well as(ii) to understand and evaluate common capital market hedging strategies.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Risk measurement and risk valuation: Concepts and applications for banks,12-M-CF5-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,The course augments the usual consideration of symmetric risk metrics by introducing metrics for downside risks and the concept of risk as a capital requirement. The focus for applications in banks lies in the treatment of risks with regard of supervisory regulations.,"After completing the course “Risk measurement and risk valuation: Concepts and applications for banks” the students are able1. to judge the appropriateness and problems of asymmetric risk measures,2. to address essential risks in banks and to understand their handling by supervisory regulations as well as3. to realize the concept of risk as a capital requirement being the systematic base for these aspects in the ban-king sector.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Economics of Tax Planning,12-M-SP-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This course deals with tax effects on fundamental economic decisions. Taxes are integrated into standard mo-dels for investment decisions, financing decisions, firm valuation, dividend policy and remuneration of employ-ees. Therefore, the interaction of corporate and personal income taxes is analysed.A reading list in English is available on request.","This course enables students to(i) combine their knowledge of tax law with microeconomic analyses in the areas of corporate and personal fi-nance;(ii) analyze the effect of taxes on fundamental economic decisions, e.g. investment and financing decisions, eva-luation of investment, financial assets, forms of remuneration for employees including managing and assessing;(iii) read and discuss research and policy papers in the field of taxation.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Tax Accounting,12-M-STB-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This module introduces the various methods of income recognition in the German Income Tax Code (Einkommen-steuergesetz, EStG). It discusses the main reporting and valuation provisions as well as the specific problems and techniques of income calculation for partnerships.",Students have in-depth knowledge of tax accounting of companies and are able to solve moderate to complex problems of tax accounting in particular of sole proprietorships and partnerships using legal source.,V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Incentives in Organizations,12-M-AO-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"Based on the classical principal-agent theory, this course discusses methodological and empirical aspects of in-centives in organisations. It uses contents from advanced text books and original (mainly empirical) research ar-ticles.Outline of syllabus1. Principal-agent theory2. Do top managers earn too much? (application)3. Performance-based payment4. Implementation of performance-based payment in companies (application)5. Seniority payment (with application)6. Financial incentives to work after retirement (with application)7. Efficiency wages (with case study)8. Team incentives (with case study)","Students acquire a working knowledge of key incentive models models, selected empirical applications and the necessary econometric background. This enables them to identify the advantages and disadvantages of different incentive systems that are applied in the enterprise context, to make informed management analyses and to cri-tically evaluate current controversies and developments as well as to conduct their own research.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Human Resource Management and Industrial Relations,12-M-HRM-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"The lecture ""Human Resource Management and Industrial Relations"" introduces advanced theories, estimation techniques and empirical results from the areas of human resources management and institutional frameworks such as ithe different actors in ndustrial relations.SyllabusIntroduction: Human Resource Management & Industrial RelationshipsChapter 1: The employment contract [formal model]Chapter 2: Motivation [formal model]Chapter 3: Employee resistance against reorganisations [empirical study]Chapter 4: The role of works councils [formal model]Chapter 5: Works councils and the employer wage structure [empirical study]Chapter 6: The behaviour of labour unions [formal model]Chapter7: Learning process of employers [formal model and empirical study]Chapter8: Demographic challenges of HRM [formal model and empirical study]","The aim of the lectures is to enable students to understand and apply advanced theories, estimation techniques and empirical results in the area human resource management and industrial relations on the basis of scientifc literature.",V (2) + Ü (2),a) Written examination (approx. 60 minutes) orb) Term paper (approx. 15 pages)Language of assessment: German and/or English,"There are no restrictions with regard to available places for students of the Masters degree programmes Mana-gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo-mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca-ted to students of other subjects; should the number of applications exceed the number of available places, the-se places will be allocated by lot.",--,150 h,--,-- +Corporate Strategy,12-M-UGF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This theory-led and application-oriented module provides you with critical knowledge and skills related to cor-porate strategy—essential for anyone aspiring to take on leadership roles in their future career, may it be in the private or public sector. The module goes beyond basic knowledge about strategic management provided by ba-chelor-level modules.(1) Developing strategies in pursuit of competitive advantage(2) Corporate diversification(3) Vertical integration and outsourcing(4) Mergers & acquisitions(5) Dynamic strategies(6) Cooperative strategies(7) Corporate spin-offs and spin-outs(8) Internationalization strategies (I)(9) Internationalization strategies (II)(10) Strategic change(11) Corporate strategies and new technologies(12) Corporate governance and corporate social responsibility(13) Corporate communication and crisis management(14) Wrap-up and Q&A",Educational aims• Clarify the role of corporate strategy• Explain theoretical concepts and mechanisms behind corporate strategy• Enable students to critically appraise alternative approaches to corporate strategy• Enable students to evaluate the boundaries and risks of corporate strategyLearning outcomesOn successful completion of this module students will be able to:• Assess the role of corporate strategy for creating and sustaining competitive advantage• Create and evaluate concepts related to corporate strategy• Make judgements about the organizational and managerial implications of corporate strategy• Systematically choose between different routes of action,V (2) + Ü (2)Module taught in: English,"a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, groups of 3 approx. 30 minutes)Language of assessment: English",--,--,150 h,--,-- +Change Management,12-M-CHA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis-cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa-tion is a universal principle. The module covers projects like merging two departments, restarting a department with team building, conducting an employee survey, or developing a new mission statement. The majority of the projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in-struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles in these processes and are able to use their knowledge for own future projects as well as to create their own so-lutions in change processes.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Accounting in the Company Management,12-M-CIU-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis-cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa-tion is a universal principle. The module covers projects like merging two departments, restarting a department with team building, conducting an employee survey, or developing a new mission statement. The majority of the projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in-struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles in these processes and are able to use their knowledge for own future projects as well as to create their own so-lutions in change processes.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Managerial Accounting,12-M-INST-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on accounting instruments, which are applied in the context of strategic management of enterprises. First, it addresses important drivers of strategic decisions from a microeconomic perspective, such as the emergence of cost and quality advantages in competition as well as scale and experience curve effects. Second, the module covers analytical and heuristic techniques of planning and control. In the context of these techniques, instruments of target costing, life cycle cost analysis, benchmarking and business wargaming are discussed with regard to their theoretical foundation and fields of application.","Initially, knowledge about fundamental requirements concerning instruments of decision-making and behavior control within enterprises is acquired. What is more, the module conveys obtaining knowledge about the strengt-hs and weaknesses and therewith fields of application and limits of prevalent instruments of strategic corporate management used by practitioners.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +"Coordination, Budgeting and Incentives in Organizations",12-M-KOBO-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"This module focuses on accounting-based instruments to control behavior in decentralized enterprises. The course first discusses the role of accounting in the context of decision-making and behavioral controlling as well as informational analyses. Afterwards, the most common instruments of behavioral controlling (budgeting, va-lue-oriented management, transfer prices) are discussed with regard to theory and practice.","This module aims to provide knowledge in the context of behavioral control in enterprises. Knowledge about re-quirements on instruments used for behavioral control are discussed and competences for deployment, struc-ture and development of coordination tools are provided.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Project Management and Control,12-M-PROM-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on the discussion and critical examination of instruments and methods used in the context of project management and control within enterprises. Both classic and agile approaches to project manage-ment are considered. It covers characteristic features and structures of projects, their possible success factors, methods and instruments of control and management of projects in various project phases. The theoretical basis as well as potential applications of these instruments are discussed.","Initially, knowledge about fundamental requirements concerning instruments of project management and con-trol is acquired. What is more, the module conveys knowledge about strengths and weaknesses and therewith fields of application and limits of commonly used instruments and methods of practitioners. Competences wi-thin the configuration and development of the project management and control as well as skills within the practi-cal use are obtained.",S (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Accounting and Capital Markets,12-M-REKA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on financial and management accounting, their functions, possible configurations as well as their impact on internal and external recipients under consideration of the institutional setting. In this con-text, an economic perspective has priority over detailed legal arrangements and regulations by the standard set-ters. Based on the theoretical foundations of information economics as well as decision-making and balance sheet theories, typical issues concerning cost and managerial accounting as well as financial accounting and pu-blicity are discussed.","Initially, a fundamental knowledge about the conception and impact of management and financial accounting as information systems is acquired. In the following, the module mainly sharpens the understanding of the eco-nomic impacts of the configuration of management and financial accounting. What is more, extensive knowled-ge about possible impacts of changes in institutional general frameworks is covered. For example, changes in valuation standards, publicity rules or regulations about the distribution of profits in enterprises and on capital markets are considered.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Analytics & Decision Making,12-M-MADM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Managerial Analytics & Decision Making"" discusses quantitative methods to structure and solve a diverse set of management problems and demonstrates the application of modern methods with the help of multiple case studies.",After completing this course students can(i) better understand and structure problems;(ii) apply important theoretical and empirical frameworks to practical problems that evaluate good and bad deci-sion making;(iii) implement advanced analytical methods to support decision making under risk.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Management of Global Supply Chains,12-M-SMGS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"Description:In the course ""Strategic Management of Global Supply Chains"", students will become familiar with the basic principles of building an efficient global supply chain and will apply what they have learned working on multiple case studies.","After completing this course students(i) can apply the basic methods and concepts of supply chain management to practical settings and evaluate the results, and(ii) understand the effects of global value chains onto strategic company decisions.",V (2) + Ü (2)Module taught in: English,written examination (approx 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Strategic Decisions and Competition,12-M-SDC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,1. Strategic situations and decision making2. Analyzing strategic situations with game theory1. Noncooperative simultaneous move games2. Nash equilibrium3. Models of oligopoly markets3. Dynamic Games1. Two(-multi) stage games and subgame perfect equilibrium2. Role of commitment in dynamic situations3. Models of advertising4. Wage bargaining and unions4. Repeated Games1. Emergence of coordination in long interactions2. Collusion between competing firms3. Time consistent monetary policy5. Static games of incomplete Information1. Bayesian Nash equilibrium2. Auctions6. Dynamic games of incomplete information1. Moral hazard and nonlinear pricing2. Perfect Bayesian equilibrium3. Signalling games4. Job-market signalling5. Corporate investment and capital structure,"After successful completion of this class, the students should be familiar with economic models that can be used to shape managerial strategy and aid in making decisions in strategic situations. Especially, by making use of simple two stage games, they should be able to formulate dynamic policies in a wide variety of strategic situa-tions. The students will acquire an intuitive understanding of the underlying economic mechanisms which emer-ge from the analysis of game theoretic models for a wide variety of strategic situations arising in industrial eco-nomics, marketing, organization, finance, trade and labor. Moreover, they will acquire skills which enable them to make predictions in strategic situations by making use of simple mathematical models. By means of comple-ting case based exercises, they will learn to transform real life business situations to an appropriate economic model. Based on an analysis of this model, they will be able to devise optimal strategies and derive the corre-sponding managerial implications.The course will be taught in English.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Theory of Industrial Organization,12-M-TI1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Theory of industrial organisation:1. Monopoly pricing• Nonlinear pricing and mechanism design• Dynamic pricing: experience goods, durable goods2. Oligopoly pricing• Static price and quantity competition in homogeneous and differentiated goods markets• Comparative statics• Equilibrium market structure3. Dynamic competition in oligopoly markets• Subgame perfect equilibrium and models of dynamic competition• Repeated games and collusion4. Strategic behaviour by incumbent firms• Entry deterrence and predation• Signalling and reputation5. Behavioral Industrial Organization• Reference Dependent Preferences and Framing Effects• Time inconsistent behaviorThe course will be taught in English.","Students which complete this class will acquire a working knowledge of advanced theoretical models of compe-tition in oligopoly markets as well as sophisticated pricing techniques in monopoly markets. They will learn the conditions under which the predictions of these models are valid. They will become familiar with applications of advanced game theoretic tools, such as dynamic models of competition, for studying interactions between firms in markets. By means of comprehensive exercises, they will apply the methods they learn in class to practical-ly relevant problems. They will be in a position to read academic papers on related topics, assess the strengths and weaknesses of an approach, summarize and comment on these papers and suggest possible extensions.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +European Competition Policy,12-M-WPE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Outline of syllabus:1. Legal environment, competition laws2. Market definition• Qualitative methods• Simple quantitative methods• Hypothetical monopoly test3. Horizontal agreements and collusion: repeated games and factors affecting likelihood of collusion4. Horizontal mergers and collusion• Economic theory• Efficiency effects• Coordinated effects5. Vertical relations and contracts• Economic analysis of contracts• ""More economic approach""6. Abuse of dominant position• Classification of abusive conduct• Economic analysis of abusive conduct and theory of harmThe course will be taught in English.","After completion of the module students can use the advanced concepts introduced in the lecture of competiti-on policy, including the legal framework, the trace models and methods for the study of competition policy issu-es, as well as understand the approach of European competition policy in high profile cases. When they are con-fronted with practical problems, they can refer to these cases, and the same logic to practical examples apply by draining the relevant economic theories that identify variables to be measured and methodologies for assessing, and based on that adequate conclusions for appropriate cases. They will sufficiently understand the subject in order to open up that build upon literature in journals and being able to think critically.",V (2)Module taught in: English,a) Written examination (approx. 60 to 120minutes) orb) Term paper (15 to 20 pages)Creditable for bonusLanguage of assessment: English,"There are no restrictions with regard to available places for students of the Masters degree programmes Mana-gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo-mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca-ted to students of other subjects; should the number of applications exceed the number of available places, the-se places will be allocated by lot.",--,150 h,--,-- +Econometrics 1,12-M-OE1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Econometrics,5,numerical grade,1 semester,graduate,"Description:This module deals with the basic concept and methodology of the ordinary least squares (OLS) regression mo-del. In particular, model assumptions and properties are discussed and formally motivated. In addition, the mo-dule examines linear restrictions on the models explanatory variables as well as dummy variables and introdu-ces tests to verify simple and multiple linear restrictions.Linear algebra is used as formal aid.Outline of syllabus:1. Random variables2. Important distributions3. Point estimates4. Simple linear regression model5. Model assumptions6. Model properties7. Simple hypothesis tests8. Multiple linear regression model9. Linear restrictions10. Dummy variables11. Multiple hypothesis tests","The students acquire knowledge of the basics, concepts and methods used in the classical linear regression mo-del and understand the role of econometrics in science and data analysis. In particular, they learn how to analy-tically derive, calculate and interpret the coefficients, standard errors and p-values of a classic regression output of the multiple regression model. Furthermore, they are able to formally state and motivate the assumptions and properties of OLS and know how to deal with transformed and dummy variables. Additionally, students will be able to test multiple linear restrictions on the parameters and will be able to apply these tests to real economic, business and social science questions.The competences acquired in this course serve as a prerequisite for ""Econometrics II"", ""Econometrics III"", ""Micro-econometrics"" und ""Financial Econometrics"".","V (2) + Ü (2)Module taught in: German (winter semester), English (summer semester)",a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Advanced Microeconomics,12-M-AM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Contract Theory and Information Eco-,5,numerical grade,1 semester,graduate,"In a nutshell, microeconomic theory considers the behavior of individual economic agents and builds from this foundation to a theory of aggregate economic outcomes, which then can be applied for conducting welfare ana-lysis and giving policy advice. This lecture addresses the core building block of this thought complex: individu-al decision making and behavior. Specifically, students will come to understand in detail the standard models of riskless consumer choice, choice under risk and intertemporal choice and learn about the empirical challenges and limitations of these models.Throughout the lecture, we will work with precise mathematical formalizations of the ideas that we want to think and talk about. In consequence, a solid understanding of the mathematical toolbox of standard microeconomics (e.g., differential calculus and constrained optimization; basic set theory; integration by parts) will be helpful as it will allow to focus on the underlying economic intuition. However, every required mathematical concept will be introduced and explained along the way, such that a strong interest in formal economic analysis is more import-ant than an advanced mathematical background.The exposition is primarily based on the standard graduate textbooks• Mas-Colell, Whinston and Green (1995): “Microeconomic Theory”• Jehle and Reny (2001): “Advanced Microeconomic Theory”","After completing the course students will be able to• explain essential findings of microeconomic theory,• apply the involved methods to given stylized examples on their own,• recognize in which real life situations and how the results can be applied.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Management and Economics 1,12-M-APW1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or presentation (approx. 30 to 45 minutes)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Management and Economics 2,12-M-APW2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or d) presentation (approx. 30 to 45 minutes)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Selected Topics in Business Information Systems 1,12-M-AWI1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi-ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration (approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 2,12-M-AWI2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,"a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi-ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration (approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus",--,--,150 h,--,-- +Digital Marketing I,12-M-DM1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Digitalization is rapidly changing our lives, including all types of business relationships. Therefore, new opportu-nities and approaches have emerged in all areas of the marketing mix: Managers can choose from a wide variety of new communication channels, such as social media networks, blogs, or messengers, and can engage in influ-encer marketing and search engine optimization. They increasingly rely on online customer co-creation or crowd-sourcing and create a wide variety of new digital products and services, often related to completely new busi-ness models. Through price crawlers and price setting tools customers‘ price search behaviors have significant-ly changed, requiring new price setting techniques. Artificial intelligence enables managers to automize and op-timize many of these marketing processes, thus offering new opportunities and challenges for companies. Over-all, digital marketing offers a tremendous variety of concepts and approaches to seize respective opportunities and deal with related challenges, which will be largely highlighted and discussed in this course.","This course provides a broad overview about these new approaches of digital marketing. It explains the underly-ing concepts of digital marketing and illustrates these approaches and concepts along numerous case studies. After attending this course, students will have a broad as well as in-depth understanding of digital marketing and its tools. Morever, they will understand of how to implement these tools successfully in business practice.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Digital Marketing II,12-M-DM2-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Students are required to put themselves in the following business situation:A large corporation has just recruited you and your team members as the new heads of the marketing depart-ment in one of the firm’s divisions in order to manage its general and digital marketing activities. Specifically, it is your task to manage the corporation’s digital product portfolio, segmentation and positioning as well as its marketing mix strategy over a period of 10 years.Structure of the class:• Long-term business simulation game (details see below) that students will play in groups• Lectures and discussion rounds on strategic approaches to succeed over a duration of 10 periods","Studierende lernen in diesem Kurs, zentrale Konzepte des Online- und Offline-Marketings gezielt und bezogen auf die jeweilige Unternehmenssituation anzuwenden. Der Kurs bildet somit die Brücke zwischen Theorievermitt-lung und entsprechende Anwendung in der Unternehmenspraxis.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +E-Commerce I,12-M-EC1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in-dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat-egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti-ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre-sentations where the students (in groups) will either apply selected lecture topics to real-world business cases or present the core aspects of research articles dealing with e-commerce topics in general.",This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as-sessing business strategies.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +E-Commerce II,12-M-EC2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in-dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat-egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti-ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre-sentations where the students (in groups) will either apply selected lecture topics to real-world business cases or present the core aspects of research articles dealing with e-commerce topics in general.",This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as-sessing business strategies.,V (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +Real-Time Process Analytics,12-M-RTP-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,The course teaches advanced approaches to process analytics. Students will learn to model and measure pro-cesses and process execution based on past and present data.,"After successfully completing the course, students should be able to• Understand process modeling and process execution in an SOA• OLAP analysis in a process warehouse• Business Rules for BPM• Complex Event Processing• Event-driven BPM using CEP and Business Rules",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Data Science,12-M-TDS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"Data science is concerned with extracting knowledge and valuable insights from data assets. It is an emerging field that is currently in high demand in both academia and industry. This course provides a practical introducti-on to the full spectrum of data science techniques spanning data acquisition and processing, data visualization and presentation, creation and evaluation of machine learning models.The course focuses on the practical aspects of data science, with emphasis on the implementation and use of the above techniques. Students will complete programming homework assignments that emphasize practical understanding of the methods described in the course.",Topics covered include:• Data acquisition and processing• graph and network models• text analysis• working with geospatial data• Usage of machine learning models (supervised and unsupervised),V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Information Systems 1,12-M-TIF1-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Topics in Information Systems 2,12-M-TIF2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,This module serves the purpose of transferring credits from• courses taken at other German or non-German universities• additional courses offered on a short-term basis• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions)The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.,"As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages)Assessment offered: In the semester in which the course is offeredLanguage of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Stochastic Models for Risk Analysis,12-RM-RA-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Point and interval estimation for the value at risk Point and interval estimation for the conditional value at risk Prediction of value at risk in time series Risk of forecasts in time series, in particular exponential smoothing un-der covariates Conditional heteroscedasticity: ARCH, GARCH, EGARCH, DVEC, BEKK, DCC Aggregated losses and their empirical analysis Empirical analysis of statistical distributions Nonparametric bounds for the value at risk and conditional value at risk Empirical estimation of nonparametric bounds for value at risk and conditional va-lue at risk Market model: definition, derivation, parameters, empirical analysis Capital asset pricing model: de-finition, parameters, empirical analysis Asset portfolios: definition, risk parameters Estimation of portfolio para-meters: variance, value at risk, conditional value at risk, shortfall Optimum portfolios: concepts, theory, numeri-cal analysis","The student is able to estimate risk measures and the parameters of risk models from data. In particular, the stu-dent knows software packages and routines which enable empirical risk evaluation in a business context.",Ü (2) + V (2),Written examination (approx. 60 minutes),"30 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Stochastic Models for Risk Assessment,12-RM-RW-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Etymological background of the risk concept Definitions of risk Basic concepts and terminology of stochastic risk modelling: risk phenomenon, risk object, risk variable, risk source, risk factor, risk cause, direct peril, indirect peril, loss under risk, profit under risk, loss variable, profit variable, risk distribution, risk indicator, risk parame-ter Classification of business risks Risk policy, risk management Risk analysis: risk identification, risk descrip-tion, risk exploration, risk-relevant measurements, risk evaluation, risk assessment, risk modelling Risk mana-gement: risk minimisation, risk protection, risk avoidance, risk mitigation, bearing of risk, risk prevention Risk control, risk monitoring Norms and standards of risk management: ISO 31000, ONR 49000 -- 49004, IEC/ISO 31010, COSO II, AIRMIC, IRM, ALARM FMEA (Failure Mode and Effect Analysis) as a tool of risk analysis and risk assessment: historical and thematic background, methodology, discussion of the FMEA assessment methodo-logy Risk matrix, risk diagram Score diagram Stochastic risk parameters and risk measures as distribution para-meters Probability distributions: Gaussian, Laplace, Students t, extreme value, logistic, exponential, Weibull, gamma, negative Gaussian, Burr, hyperbolic, generalised hyperbolic Elementary stochastic risk measures: va-riance, standard deviation, signal-to-noise ratio, coefficient of variation, Sharpe ratio, nonconformance probabi-lity, expected shortfall, shortfall probability, risk parameters under reference values, Stone family Value at Risk and Conditional Value at Risk: definition, formal representations, values under special probability distributions Axioms of risk measures: distribution invariance, subadditivity, superadditivity, additivity, comonotonous additi-vity, nonnegative homogeneity, translation invariance, convexity, continuity, coherence","The student knows the schemes and concepts of risk analysis, risk assessment, risk measurement, and the theoretical background. The student knows the concepts of advanced stochastic risk modeling. In a practical business situation, the student is able to identify an appropriate scheme of risk assessment and corresponding meaningful risk measures.",V (2) + Ü (2),Written examination (approx. 60 minutes),"30 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Communication in Business and Economics,12-M-BUC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"The lecture names introductory relevant communication models. Furthermore, the theoretical models of PR are discussed. The added value of communication for companies, business, politics, and science is explained. The discrepancy between journalism and PR is discussed, as well as the basic elements, instruments, goals, and forms of PR. The preparation and implementation of press meetings, conferences, campaigns, and events will be systematically explained, and the central aspects of corporate communications will be outlined. The exerci-se deals with the practical implementation of journalistic styles in the various media and provides an overview of the possibilities and concepts of PR work across different media and target groups.","After participating in the module courses, students are able to understand and apply PR and its forms, elements as well as methods and in a holistic context. Students learn professional competencies in the field of (business) communication with regard to reflection, argumentation, and exchange as a PR consultant in different areas. In addition, students will be able to apply concrete PR instruments in practice and prepare them professionally.",V (2) + Ü (2)Module taught in: English,written examination (approx. 60 minutes)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,-- +"Business Communication in Print, Online and Social Media",12-M-ECC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"This module focuses on the relationship of offer characteristics with benefit aspects for the end consumer and the business models on the part of the providers. Starting from the basics of editorial work and professional text management, the new forms of communication management in social networks are presented. The focus of the lecture is on the use of social media in campaigns (Facebook, Twitter, Instagram, Tiktok). There will also be exer-cises on various Web 2.0 applications (e.g. online social networks) and on the collection and interpretation of online market research data. However, crisis communication of companies will also be covered in particular opi-nion-makers on the web as well as protest culture on the web.","By participating in the module courses, students acquire job-specific skills in research and interviewing. Stu-dents are able to collect and organize information according to criteria of topicality and relevance. In addition, students are taught journalistic expertise so that they are able to recognize the forms of presentation of news, re-ports, and background reports with their media characteristics and communicative functions in different media genres and create them themselves. Students will be able to prototype and design a social media campaign, de-scribe the editorial and technical approach including feedback, response, and customer engagement. In additi-on, students will be able to design counter-strategies for corporate communication crises.",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Managerial Practice Lectures,12-M-VGP-202-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"In this lecture, we invite board members of publicly listed companies, SMEs and Startups to discuss contempo-rary challenges of corporate management.Students gain sustainable insights into current management practices, challenges of corporate management in various industries, and discuss pressing managerial issues with C-level executives. In individual and group as-signments, students are required to connect management theories with the managerial challenges of the spea-kers.Managers of the different companies are required to address the following questions that will foster a detailed discussion at the end of each lecture:- What are the current challenges facing your company?- Which strategies do you employ to respond to these challenges?- How have leadership concepts and approaches changed in your company?","After participating in this module, students should be able to combine theoretical approaches with current chal-lenges in management. The students obtain a realistic insight into a cross-section of the German economy. Through discussions reports and group presentations students’ social skills are trained in addition to professio-nal skills.",S (2),portfolio (approx. 15 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Advanced Topics in Data Science,12-M-ATDS-211-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"In this course, students work on advanced data science projects. The course covers the entire data science work-flow from data collection to data preparation to modeling, evaluation and deployment. By following a top-down teaching approach, students are enabled to apply complex machine learning models from the beginning.","As part of the course work, students will acquire knowledge and skills in the following areas:1. Becoming familiar with the principles and frameworks in the research area of Data Science.2. Apply machine learning and deep learning frameworks to structured and unstructured data3. Design, implementation and evaluation of key algorithms within an end-to-end workflow in the field of Data Science4. Application of Jupyter notebooks and their infrastructure (collection, storage, retrieval, and analysis of data)5. Understanding of a data-driven & analytical approach to decision problems",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) orb) term paper (approx. 15 pages)Language of assessment: German and/or EnglishAssessment offered: Only when announced in the semester in which the courses are offeredcreditable for bonus,--,--,150 h,--,-- +International Marketing Strategy,12-M-IMS-211-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The objective of this simulation course is to develop hands-on skills of how to make international marketing de-cisions. Emphasis is put on the computer simulation game Country Manager which focuses on the managerial is-sues arising when companies plan and execute market entry into new countries. This exercise allows students to experience the challenges pertaining to corresponding decisions by playing the role of a responsible manager for a major consumer products company. Students have to decide on the countries to enter, the mode of entry, the segments to target, and every aspect of the marketing mix (price, promotion, place and product) and will get im-mediate feedback on the consequences of their actions.","After completion of the course, participants should have gained a broad appreciation of critical decisions in in-ternational marketing.",S (2),a) written examination (40 to 60 minutes) orb) term paper (15 to 20 pages) and presentation (approx. 20 minutes) (weighted 2:1) orc) term paper (30 to 40 pages) ord) portfolio (approx. 20 pages)Language of assessment: German and/or English,--,--,150 h,--,-- +Economist Practice Lectures,12-M-VWP-211-m01,Faculty of Business Management and Economics,"Holder of the Senior Professorship for Economics, Money",5,numerical grade,1 semester,graduate,"The content of the seminar is the active participation in as well as the follow-up of the lectures of economists from different national and international fields of activity, which are organized for the event.The invitation of speakers from practice strengthens the practical orientation of the scientifically founded and at the same time internationally oriented education at the faculty of economics of the University of Würzburg.In this way, students will gain lasting insights into the fields of activity of economists, gain an insight into prac-tical activities, discuss these with high-ranking economists and combine them with theoretical economic know-ledge gained during their studies.","By participating in the seminar, Masters students of the faculty of economics and business administration should get to know the different fields of activity of economists and the questions that determine the daily work of the speakers in the course of the lectures.In addition, the participants of the seminar will have the opportunity to apply the knowledge of economics they have acquired during their studies. For this purpose, in addition to a discussion with the speakers following the respective lecture, a debating workshop is offered to the participants of the seminar, in which the students are to learn economic argumentation and debate management. The learned contents and competencies will be tested at the end of the semester.",S (2),"a) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes) orb) term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1) orc) written examination (approx. 60 minutes)Language of assessment: German and/or English",--,--,150 h,--,-- +Enterprise AI,12-M-EAI-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) term paper (approx. 15 pages) orc) oral examination of one candidate each (approx. 20 minutes)Language of assessment: German and/or Englishcreditable for bonus,--,--,150 h,--,-- +Information Systems and Artificial Intelligence 1,12-M-KI1-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) orc) term paper (approx. 15 to 20 pages)Language of assessment: German and/or EnglishAssessment offered: In the semester in which the course is offeredcreditable for bonus,--,--,150 h,--,-- +Information Systems and Artificial Intelligence 2,12-M-KI2-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),a) written examination (approx. 60 minutes) orb) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) orc) term paper (approx. 15 to 20 pages)Language of assessment: German and/or EnglishAssessment offered: In the semester in which the course is offeredcreditable for bonus,--,--,150 h,--,-- +Vertical Storytelling,12-M-VS-221-m01,Faculty of Business Management and Economics,nan,10,numerical grade,1 semester,nan,--,--,S (2),"portfolio (approx. 5 pages)Assessment offered: every year, summer semester",--,--,300 h,--,-- +Organizational Economics and Digital Transformation,12-M-OEDT-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: EnglishCreditable for bonus,--,--,150 h,--,-- +Policy Evaluation Methods,12-M-PEM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Labor Economics,5,numerical grade,1 semester,graduate,"This course offers an introduction to the fundamentals of causal inference and to widely used research desi-gns in the social sciences. In the first part a framework for understanding causality is introduced. Specifically, the epistemological differences between association, intervention and counterfactuals are explained. Then it is shown why experiments are paramount in generating causal knowledge and which assumptions are needed for which level of the causal hierarchy. Finally, we will discuss two widely used approaches to causality in the social sciences, i.e. potential outcomes and directed acyclic graphs.The second part is devoted to the research designs regressions analysis, difference-in-differences, instrumen-tal variables, and regression discontinuity. The emphasis is how these research designs are for example applied to answer important questions in labour economics such as the effects of a minimum wage increase on employ-ment or the effect of children on female labour supply and wages.The assumptions each research design requires in order to identify a causal effect will be at center stage of the lecture. Therefore the emphasis is to teach students what one needs to estimate in order to answer a given que-stion. Further, the research designs are discussed such that students will be able to evaluate and apply these re-search designs to other questions and fields.","At the end of the course, students should be able to understand basic concepts and methods of causal infe-rence, as well as read, interpret, and assess the credibility of scientific publications. In addition, the course ser-ves as preparation for advanced statistics and econometrics courses.",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages)Language of assessment: Englishcreditable for bonus,--,Research track module in Masters programme IEP,150 h,--,-- +Topics in Empirical Economics,12-M-TE-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2)Module taught in: English,portfolio (approx. 50 hours)Prüfungssprache: EnglischCreditable for bonus,"12 *WA1(1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects.(2) Places on all courses of the module with a restricted number of places will be allocated in the same procedu-re.(3) A waiting list will be maintained and places re-allocated by lot as they become available.",--,150 h,--,-- +Master Thesis Information Systems,12-WI-MA-192-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,30,numerical grade,1 semester,graduate,"Students will complete their degree with a Masters thesis in which they will be required to independently rese-arch and write on a topic in the area of business management and economics, drawing on the subject-specific knowledge they have acquired and adhering to the principles of good scientific practice. This thesis may either take the form of an analysis and structured presentation of the existing literature on a certain topic or may, as is often the case, also include a presentation of the students own original achievements, e. g. new algorithms de-veloped by students, surveys, the prototypical demonstration of a concept they developed or the application and (further) development of a theoretical model.","In the master thesis students prove that they can plan and carry out a science-based work to solve a particular problem within a specified period autonomously and to document the results in accordance with the professio-nal scientific standards in writing. Students are able to understand relevant contributions to research and pro-fessional practice, critically analyze and assess the relevance to their own specific questions. They can assess and recognize major lines of development and dynamics of the subject and therefore also the need to retrain continuously.",--,Masters thesis (approx. 60 to 80 pages)Language of assessment: German and/or English,--,Time to complete: 6 months,900 h,--,-- diff --git a/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..75d9e00e5e6ae7f8fb14584927d026c282de8e2b Binary files /dev/null and b/04_finetuning_approaches/MS_IS_all_modules_orginal_to_clean_cleaned.xlsx differ diff --git a/04_finetuning_approaches/finetuned_sqa_tryout.ipynb b/04_finetuning_approaches/finetuned_sqa_tryout.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..857e4b8e26089f2d86b03cdd3287118c5d84d974 --- /dev/null +++ b/04_finetuning_approaches/finetuned_sqa_tryout.ipynb @@ -0,0 +1,63 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import pipeline\n", + "import pandas as pd\n", + "import torch\n", + "\n", + "\n", + "table = pd.read_excel(\"MS_IS_50_modules_cleaned.xlsx\")\n", + "table = table.astype(str)\n", + "\n", + "tqa = pipeline(task=\"table-question-answering\", model=\"google/tapas-large-finetuned-wtq\")" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Programming with neural nets']\n" + ] + } + ], + "source": [ + "question = \"Which modules titles are about programming?\"\n", + "c = tqa(table, query=question)['cells']\n", + "\n", + "print(c)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/04_finetuning_approaches/generate_training_question.ipynb b/04_finetuning_approaches/generate_training_question.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..99bd5a0e1e187f25ac8556f3315fc5acefd0138c --- /dev/null +++ b/04_finetuning_approaches/generate_training_question.ipynb @@ -0,0 +1,786 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 0 duplicated abbreviations.\n" + ] + }, + { + "data": { + "text/plain": [ + "'CSV and Excel files saved at felix_playground_SQA_Training/MS_IS_all_modules_cleaned.csv and felix_playground_SQA_Training/MS_IS_all_modules_cleaned.xlsx respectively.'" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "def clean_and_save(file_path):\n", + " df = pd.read_excel(file_path)\n", + " df = df.astype(str)\n", + " df = df.replace('\\n', '', regex=True)\n", + " df = df.replace(\"'\", '\"')\n", + " df = df.replace(\"'\", \"\", regex=True)\n", + " df = df.apply(lambda x: x.str.strip() if x.dtype == \"object\" else x)\n", + " df = df.drop_duplicates()\n", + " csv_file_path = file_path.replace(\".xlsx\", \"_cleaned.csv\")\n", + " df.to_csv(csv_file_path, index=False)\n", + " excel_file_path = file_path.replace(\".xlsx\", \"_cleaned.xlsx\")\n", + " print(f\"There are {df.duplicated(subset=['Abbreviation']).sum()} duplicated abbreviations.\")\n", + " df = df.drop_duplicates(subset=['Abbreviation'], keep='first')\n", + " df.to_excel(excel_file_path, index=False)\n", + " return f\"CSV and Excel files saved at {csv_file_path} and {excel_file_path} respectively.\"\n", + "\n", + "clean_and_save(\"felix_playground_SQA_Training/MS_IS_all_modules.xlsx\")" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'pd' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[1], line 29\u001b[0m\n\u001b[0;32m 25\u001b[0m training_data\u001b[39m.\u001b[39mto_excel(\u001b[39m'\u001b[39m\u001b[39mfelix_playground_SQA_Training/module_guide_sq_abbreviation.xlsx\u001b[39m\u001b[39m'\u001b[39m, index\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n\u001b[0;32m 27\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mTraining data created and saved as \u001b[39m\u001b[39m'\u001b[39m\u001b[39mtraining_data.xlsx\u001b[39m\u001b[39m'\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m---> 29\u001b[0m create_training_data_abbreviation(\u001b[39m\"\u001b[39;49m\u001b[39mfelix_playground_SQA_Training/MS_IS_all_modules_cleaned.xlsx\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n", + "Cell \u001b[1;32mIn[1], line 5\u001b[0m, in \u001b[0;36mcreate_training_data_abbreviation\u001b[1;34m(file_path)\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcreate_training_data_abbreviation\u001b[39m(file_path):\n\u001b[0;32m 4\u001b[0m \u001b[39m# Read the cleaned excel file\u001b[39;00m\n\u001b[1;32m----> 5\u001b[0m df \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mread_excel(file_path)\n\u001b[0;32m 7\u001b[0m \u001b[39m# Create a new dataframe for training data\u001b[39;00m\n\u001b[0;32m 8\u001b[0m training_data \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame(columns\u001b[39m=\u001b[39m[\u001b[39m'\u001b[39m\u001b[39mid\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mannotator\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mposition\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mquestion\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mtable_file\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39manswer_coordinates\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39manswer_text\u001b[39m\u001b[39m'\u001b[39m])\n", + "\u001b[1;31mNameError\u001b[0m: name 'pd' is not defined" + ] + } + ], + "source": [ + "import random\n", + "\n", + "def create_training_data_abbreviation(file_path):\n", + " # Read the cleaned excel file\n", + " df = pd.read_excel(file_path)\n", + " \n", + " # Create a new dataframe for training data\n", + " training_data = pd.DataFrame(columns=['id', 'annotator', 'position', 'question', 'table_file', 'answer_coordinates', 'answer_text'])\n", + " \n", + " # Define a list of possible question formulations\n", + " \n", + " \n", + " for i, row in df.iterrows():\n", + " new_row = {'id': f'ms-is-01', 'annotator': 0, 'position': 0, 'question': '', 'table_file': '', 'answer_coordinates': '', 'answer_text': ''}\n", + " question_formulations = [ f\"What is the abbreviation of {row['Module title']}?\",f\"What is the code for {row['Module title']}?\",f\"What is the ID of {row['Module title']}?\",f\"What is the abbreviation of the module {row['Module title']}?\"]\n", + " question = random.choice(question_formulations).format(row=row)\n", + " new_row['question'] = question\n", + " table_file = f\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.csv\"\n", + " new_row['table_file'] = table_file\n", + " answer_coordinates = f\"['({i}, {df.columns.get_loc('Abbreviation')})']\"\n", + " new_row['answer_coordinates'] = answer_coordinates\n", + " answer_text = f\"['{row['Abbreviation']}']\"\n", + " new_row['answer_text'] = answer_text\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + " training_data.to_excel('felix_playground_SQA_Training/module_guide_sq_abbreviation.xlsx', index=False)\n", + " \n", + " return \"Training data created and saved as 'training_data.xlsx'.\"\n", + "\n", + "create_training_data_abbreviation(\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.xlsx\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\1598320022.py:55: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n" + ] + }, + { + "data": { + "text/plain": [ + "\"Training data created and saved as 'questions_content.xlsx'.\"" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def create_training_data_content(file_path):\n", + " # Read the cleaned excel file\n", + " df = pd.read_excel(file_path)\n", + "\n", + " # Create a new dataframe for training data\n", + " training_data = pd.DataFrame(\n", + " columns=[\n", + " \"id\",\n", + " \"annotator\",\n", + " \"position\",\n", + " \"question\",\n", + " \"table_file\",\n", + " \"answer_coordinates\",\n", + " \"answer_text\",\n", + " ]\n", + " )\n", + "\n", + " # Define a list of possible question formulations\n", + " for i, row in df.iterrows():\n", + " # Create a new row for the training data\n", + " new_row = {\n", + " \"id\": f\"ms-is-01\",\n", + " \"annotator\": 0,\n", + " \"position\": 0,\n", + " \"question\": \"\",\n", + " \"table_file\": \"\",\n", + " \"answer_coordinates\": \"\",\n", + " \"answer_text\": \"\",\n", + " }\n", + "\n", + " question_formulations = [\n", + " f\"What is the content of {row['Module title']}?\",\n", + " f\"What is the description of {row['Module title']}?\",\n", + " f\"What is {row['Module title']} about?\",\n", + " f\"Give me the content of {row['Module title']}?\",\n", + " f\"Give me the content of the module {row['Module title']}? \",\n", + " ]\n", + "\n", + " question = random.choice(question_formulations).format(row=row)\n", + " new_row[\"question\"] = question\n", + "\n", + " # Set the table file\n", + " table_file = f\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.csv\"\n", + " new_row[\"table_file\"] = table_file\n", + "\n", + " # Set the answer coordinates\n", + " answer_coordinates = f\"['({i}, {df.columns.get_loc('Contents')})']\"\n", + " new_row[\"answer_coordinates\"] = answer_coordinates\n", + "\n", + " # Set the answer text\n", + " answer_text = f\"['{row['Contents']}']\"\n", + " new_row[\"answer_text\"] = answer_text\n", + "\n", + " # Append the new row to the training data\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "\n", + " # Save the training data as an excel file\n", + " training_data.to_excel(\"felix_playground_SQA_Training/module_guide_sqa_contents.xlsx\", index=False)\n", + "\n", + " return \"Training data created and saved as 'questions_content.xlsx'.\"\n", + "\n", + "create_training_data_content(\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.xlsx\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "C:\\Users\\FelixNeubauer\\AppData\\Local\\Temp\\ipykernel_19396\\3422203238.py:58: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", + " training_data = training_data.append(new_row, ignore_index=True)\n" + ] + }, + { + "data": { + "text/plain": [ + "\"Training data created and saved as 'questions_ETCS.xlsx'.\"" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def create_training_data_ETCS(file_path):\n", + " # Read the cleaned excel file\n", + " df = pd.read_excel(file_path)\n", + "\n", + " # Create a new dataframe for training data\n", + " training_data = pd.DataFrame(\n", + " columns=[\n", + " \"id\",\n", + " \"annotator\",\n", + " \"position\",\n", + " \"question\",\n", + " \"table_file\",\n", + " \"answer_coordinates\",\n", + " \"answer_text\",\n", + " ]\n", + " )\n", + "\n", + " # Define a list of possible question formulations\n", + " for i, row in df.iterrows():\n", + " # Create a new row for the training data\n", + " new_row = {\n", + " \"id\": f\"ms-is-01\",\n", + " \"annotator\": 0,\n", + " \"position\": 0,\n", + " \"question\": \"\",\n", + " \"table_file\": \"\",\n", + " \"answer_coordinates\": \"\",\n", + " \"answer_text\": \"\",\n", + " }\n", + " \n", + " question_formulations = [\n", + " f\"How many credits does {row['Module title']} have?\",\n", + " f\"What is the credit value of {row['Module title']}?\",\n", + " f\"how many credits do I get for {row['Module title']}?\",\n", + " f\"How many etcs has {row['Module title']}?\",\n", + " f\"how many credits has {row['Module title']} have?\",\n", + " f\"hw many etcs does {row['Module title']} have?\",\n", + " f\"Give me the amount of ects for {row['Module title']}?\",\n", + " f\"give me the ects points of module {row['Module title']}? \",\n", + " ]\n", + "\n", + " question = random.choice(question_formulations).format(row=row)\n", + " new_row[\"question\"] = question\n", + "\n", + " # Set the table file\n", + " table_file = f\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.csv\"\n", + " new_row[\"table_file\"] = table_file\n", + "\n", + " # Set the answer coordinates\n", + " answer_coordinates = f\"['({i}, {df.columns.get_loc('ETCS')})']\"\n", + " new_row[\"answer_coordinates\"] = answer_coordinates\n", + "\n", + " # Set the answer text\n", + " answer_text = f\"['{row['ETCS']}']\"\n", + " new_row[\"answer_text\"] = answer_text\n", + "\n", + " # Append the new row to the training data\n", + " training_data = training_data.append(new_row, ignore_index=True)\n", + "\n", + " # Save the training data as an excel file\n", + " training_data.to_excel(\"felix_playground_SQA_Training/module_guide_sqa_etcs.xlsx\", index=False)\n", + "\n", + " return \"Training data created and saved as 'questions_ETCS.xlsx'.\"\n", + "\n", + "\n", + "create_training_data_ETCS(\"felix_playground_SQA_Training/MS_IS_all_modules_cleaned.xlsx\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "enterpriseai2", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/04_finetuning_approaches/module_guide_sq_30_questions.xlsx b/04_finetuning_approaches/module_guide_sq_30_questions.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..4d474e157366bd04926b76ce32150fd032a9065d Binary files /dev/null and b/04_finetuning_approaches/module_guide_sq_30_questions.xlsx differ diff --git a/04_finetuning_approaches/module_guide_sqa.xlsx b/04_finetuning_approaches/module_guide_sqa.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..6196b361d6921f9e6275b95477b3b0322317daa5 Binary files /dev/null and b/04_finetuning_approaches/module_guide_sqa.xlsx differ diff --git a/04_finetuning_approaches/module_guide_sqa_contents.xlsx b/04_finetuning_approaches/module_guide_sqa_contents.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..b7e0ce16a0f6d93173cfe5abdce85e21d8ba786a Binary files /dev/null and b/04_finetuning_approaches/module_guide_sqa_contents.xlsx differ diff --git a/04_finetuning_approaches/module_guide_sqa_etcs.xlsx b/04_finetuning_approaches/module_guide_sqa_etcs.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..5745207d376aa9b01651164f0bd064e448453366 Binary files /dev/null and b/04_finetuning_approaches/module_guide_sqa_etcs.xlsx differ diff --git a/04_finetuning_approaches/qa_catalog.xlsx b/04_finetuning_approaches/qa_catalog.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..f59dc753d7bcb642c026d2d6e3caea2276e7cfb3 Binary files /dev/null and b/04_finetuning_approaches/qa_catalog.xlsx differ diff --git a/04_finetuning_approaches/sqa_train_set_28_examples.xlsx b/04_finetuning_approaches/sqa_train_set_28_examples.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..ffa1d2299dc4f4362aec17ac6367bb5e63ebda35 Binary files /dev/null and b/04_finetuning_approaches/sqa_train_set_28_examples.xlsx differ diff --git a/0915NC_Studienplaetze.jpg b/0915NC_Studienplaetze.jpg new file mode 100644 index 0000000000000000000000000000000000000000..9fcb7224b4012b5ab8e68dd28940880a62ed57bb Binary files /dev/null and b/0915NC_Studienplaetze.jpg differ diff --git a/09_archive_and_discarded_approaches/MS_IS_all_modules.csv b/09_archive_and_discarded_approaches/MS_IS_all_modules.csv new file mode 100644 index 0000000000000000000000000000000000000000..9c2fb8c7555a2c63c448076bb8a2235e272d7079 --- /dev/null +++ b/09_archive_and_discarded_approaches/MS_IS_all_modules.csv @@ -0,0 +1,2138 @@ +Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I +Information Processing within Organizations,12-IV-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This course provides students with an in-depth overview of the structure and the application areas of business +management information systems in enterprises and public institutions. + +Outline of syllabus: +1. What is software: concepts, categories, application +2. Software life cycle: duration, phases, steps +3. As-is analysis: tasks, problems +4. To-be concept: system design, data design, dialog design, function design +5. Object orientation: paradigm shift +6. Change management: meaning, methodologies, project management +7. Office automation: tasks, areas of application","After completing the course ""Integrated Information Processing"", students will be able to +(i) understand the importance of integration in enterprises, especially in information systems; +(ii) assess the progress of development of a software project, estimate cycle costs, know and consider require- +ments, which brings a software implementation with; +(iii) select the correct procedures or practices in an as-is analysis and target conception and practically apply +(with participation in the exercise); +(iv) understand the importance of change management and project management and know the appropriate me- +thods for specific applications.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +IT-Management,12-M-ITM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"Content: +This course provides students with an in-depth overview of aims, tasks and appropriate methods of IT manage- +ment. + +Outline of syllabus: +1. Organisation and distinction +2. IT strategy +3. IT organisation +4. Management of IT systems +5. Enterprise Architecture Management +6. IT project management +7. IT security +8. IT law +9. IT controlling + +Reading: + +• Hofmann/Schmidt: Masterkurs IT-Management, Wiesbaden. +• Tiemeyer: Handbuch IT-Management, Munich. +• Hanschke: Strategisches Management der IT-Landschaft, Munich.","After completing the course ""IT Management"", students will be able to +1. overview the different aspects to be considered regarding a purposeful IT management; +2. understand and apply appropriate methods and tools; +3. independently perform system search and selection in a team project (only after participation in the practice + +lessons).",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Project Seminar,12-PS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,15,numerical grade,1 semester,graduate,"Content: +In small project teams of 4 to 10 members, students will spend several months actively working on a specific and +realistic problem with practical relevance. They will progress through several project stages including as-is analy- +sis, to-be conception and implementation of an IS solution. The project teams will be required to work indepen- +dently and will only receive advice and minor support from research assistants. + +Reading: +will vary according to topic","After completing the course ""Projektseminar"", students will be able to +1. analyze business tasks and requirements and generate fitting IS solutions; +2. apply project management methods; +3. internalize stress, time and conflict management by means of practical teamwork.",S (2),"project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution +(approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1 +Language of assessment: German, English +Creditable for bonus",--,--,450 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), +data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua- +ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me- +thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).","The students possess theoretical and practical knowledge in the area of information retrieval and have acquired +the technical know-how to create a search engine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program +quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IS,ES,GE",150 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo- +dern computer systems, as well as the measures implemented to protect against these attacks. In the course, +the following topics are discussed: + +• x86-64 instruction set architecture and assembly language +• Runtime attacks (code injection, code reuse, defenses) +• Web security +• Blockchains and smart contracts +• Side-channel attacks +• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con- +cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci- +ses allow students to gain hands-on experience with attacks and analysis of systems from an attacker's perspec- +tive.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, LR, HCI, ES. +Basic programming knowledge in C is required.",150 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,"The students possess a fundamental and applicable knowledge about advanced topics in software engineering +with a focus on modern software architectures and fundamental approaches to model-driven software enginee- +ring.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, +propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, +search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia- +bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of +measured data, planning and evaluation of simulation experiments, special random processes, possibilities and +limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation +projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of +(technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu- +lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,ES,GE",240 h,--,-- +Advanced Programming,10-I=APR-182-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"With the knowledge of basic programming, taught in introductory lectures, it is possible to realize simpler pro- +grams. If more complex problems are to be tackled, suboptimal results like long, incomprehensible functions +and code duplicates occur. In this lecture, further knowledge is to be conveyed on how to give programs and co- +de a sensible structure. Also, further topics in the areas of software security and parallel programming are dis- +cussed.","Students learn advanced programming paradigms especially suited for space applications. Different patterns are +then implemented in multiple languages and their efficiency measured using standard metrics. In addition, par- +allel processing concepts are introduced culminating in the use of GPU architectures for extremely quick proces- +sing.","V (2) + Ü (2) +Module taught in: English","written examination (90 to 120 minutes) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Programming with neural nets,10-I=PNN-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for +NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) +and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite- +rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de- +tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili- +stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. +The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing mostly for English. They are able to solve problems through the methods +taught. They have gained experience in the application of text mining algorithms.","The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing. They are able to solve practical problems with the methods acquired in +class. They have gained experience in the application of text mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IT, HCI.",150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important +basics as well as the most recent approaches to image representation, image processing and image analysis are +taught. Actual models and methods of machine learning as well as their technical backgrounds are presented +and their respective applications in image processing are shown.","Students have fundamental knowledge of problems and techniques in the field of computer vision and are able +to independently identify and apply suitable methods for concrete problems.","V (2) + Ü (2) +Module taught in: English","Written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in- +formation systems and social media in the World Wide Web, but also for various social, economic and biologi- +cal systems. What can we learn from data that capture the interaction topology of such complex systems? What +is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do +these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most +influential actors in a social network? And how can we analyze time series data on systems with dynamic net- +work topologies? +Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts +for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to +practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari- +ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles +of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha- +stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma- +terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, +which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen +their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final +written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri- +ven modelling of complex technical, social, and biological systems. Students will understand how we can quan- +titatively model the topology of networked systems and how we can detect and characterize topological pat- +terns. Participants will learn how to use analytical methods to make statements about the expected properties of +very large networks that are generated based on different stochastic models. They further gain an analytical un- +derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree +distributions influence the robustness of systems, and how emergent network features emerge from simple ran- +dom processes.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): + +IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process +model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning +methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, +SVM), learning methods for special data types, further learning paradigms.","The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da- +ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of +the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use +or implementation of data mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE,SEC",150 h,--,-- +Business Software 1: IS-based Enterprise Management,12-GPU-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This module provides students with an overview of the structure of a business information system (SAP Business +ByDesign) in depth. +Outline of syllabus: +1. Integrated information systems: integration, standard software, system architecture +2. Working with standard business software +3. Consulting in integrated information systems: project management, project organisation, presentation skills +Description: +The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small +groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the +software, dealing with a wide variety of business processes. +If you would like to register for this course, please submit an application to the consultants (cover letter, CV, cer- +tificates; please also specify your degree programme and student ID number).","After completing the course ""Business Software 1"", students will be able to +(i) understand an ERP system in its depth; +(ii) understand the interaction of business processes; +(iii) execute business tasks and processes in an ERP system independently (after participation in the practice +lessons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +c) Term paper (15 to 20 pages) or +Creditable for bonus +Language of assessment: German and/or English +Assessment offered: Once a year, winter semester","20 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Software 2: Enterprise Resource Planning Systems,12-M-ERP-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Content: +This module provides students with an overview of the structure of business information systems in width as +well as the selection and implementation of business information systems in organisations. + +Outline of syllabus: +1. Integrated information systems: integration, standard software, system architectures, operating models +2. Selection of integrated information systems: methods, cost-benefit analysis +3. Implementation of integrated information systems: project management, project organisation, project marke- + +ting + +The lecture will be accompanied by an exercise that will present students with an opportunity to access, in small +groups, the enterprise resource planning system operated by the Chair in its ERP laboratory and to work with the +software, dealing with a wide variety of business processes.","After completing the course ""Business Software 2"", students will be able to +1. differentiate between system architectures and -philosophies; +2. understand the interaction of business processes; +3. come to a selection decision for an ERP system using a structured approach and compare different ERP sy- + +stems; + +4. execute business tasks and processes in an ERP system independently (after participation in the practice les- + +sons).",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +c) Term paper (15 to 20 pages) or +Creditable for bonus +Language of assessment: German and/or English +Assessment offered: Once a year, summer semester","20 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Advanced Seminar: Enterprise Systems,12-M-ES-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the fields of informati- +on systems and enterprise systems. + +Reading: +will vary according to topic","After completing the course ""Enterprise Systems"", students will be able to +1. understand the fundamentals of scientific literature reviews; +2. integrate elaborated content in a scientific thesis; +3. create presentations independently.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Decision Support Systems,12-M-DSS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course discusses advanced approaches for modelling and solving decision problems in business settings. +The acquired insights are used to design and implement decision support systems using standard software tools +(Python).","After successfully completing the course, students should be able to + +• Understand the structure of classic business decision problems +• Isolate key elements from general problem descriptions and convert them to quantitative decision models +• Solve different classes of optimization problems (linear, network, integer, multi-objective, non-linear, + +stochastic) + +• Implement decision support systems",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Analytical Information Systems,12-BI-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"The course provides an overview of the structure and applications of analytical information systems. A special fo- +cus is on individual quantitative methods of data analysis. On the one hand, methods from the areas of data pre- +paration and data manipulation as well as their practical application are introduced. On the other hand, an intro- +duction to methods and the application of machine learning methods for predictive analytics, in particular neural +networks and deep learning, is given.","The module provides students with knowledge of: + +• Data Manipulation +• Data Engineering +• Descriptive Analytics +• Predictive Analytics and Data Mining +• Supervised Learning +• Unsupervised Learning +• Neural Networks and Deep Learning +• Text Mining +• Big Data Technologies",V (2) + Ü (2),"Written examination (approx. 60 Minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +WM1: +Should the number of applications exceed the number of available places, places will be allocated as follows: +1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Business Analytics,12-M-BUA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the field of business +management decision models and methods and their application in the development of decision-support sy- +stems as well as analytical information systems and quantitative methods of data analysis. + +Students work on current topics using methods from machine learning, mathematical optimization and simulati- +on.","The module provides students with knowledge of: + +• Scientific literature +• Implementation of methods in code +• Integration of developed results in scientific papers +• Creating presentations and lectures",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +E-Business Strategies,12-M-IBS-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of strategic implications of digital technologies at the level of organisations, +industries and value networks. To this end, concepts and frameworks from strategic technology management are +applied to digital innovations and illustrated with numerous examples. In the accompanying exercise, case stu- +dies of well-known digital companies and their business models are analysed and discussed.","- Understand theoretical concepts of strategy development and implementation in the context of digital techno- +logies. + +- Apply different frames of reference and understand their strengths and weaknesses in the context of practical +application. + +- Transfer the concepts to real business situations",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Mobile and Ubiquitous Systems,12-M-MUS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,5,numerical grade,1 semester,graduate,"The module provides an overview of technologies and business applications of mobile & ubiquitous computing. +Concepts and applications are illustrated using numerous examples from mobile telecommunications to the In- +ternet of Things. In the accompanying exercise, corresponding case study texts are analysed and discussed.","- Understand the technological basics of mobile & ubiquitous computing. + +- Analysing business applications in processes, products/services and business models + +- Apply the concepts learned to real-life problems in a business context",Ü (2) + V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Seminar: E-Business Strategies,12-M-SEBS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Information Systems Engineering,10,numerical grade,1 semester,graduate,"In this course, students will acquire important knowledge and skills that will enable them to prepare a well-struc- +tured term paper and to present the results of their work with the help of relevant topics in the fields of web-ba- +sed platforms (electronic markets, Web 2.0 etc.) and strategic management of a company.","- Academic literature review + +- Integration of developed results in scientific papers + +- Creating presentations and talks",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Corporate Entrepreneurship,12-M-UGF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This module is a theory-led and practice-oriented primer on corporate entrepreneurship. It provides you with +knowledge useful for anyone aiming at working (or researching) in the field of corporate innovation and entrepre- +neurship or at pursuing an ‘intrapreneurial’ or entrepreneurial career. + +(1) Introduction to corporate entrepreneurship + +(2) Antecedents and forms of corporate entrepreneurship + +(3) Corporate strategy and corporate entrepreneurship + +(4) Organizational structure and corporate entrepreneurship + +(5) Human resource management and corporate entrepreneurship + +(6) Building supportive organizational cultures + +(7) Entrepreneurial control systems + +(8) Entrepreneurial leadership + +(9) The corporate entrepreneur as a champion and diplomat + +(10) The pay-off from corporate entrepreneurship + +(11) Corporate venture capital + +(12) Corporate entrepreneurship in nonprofit and government organizations + +(13) Universities and academic spin-offs + +(14) Wrap-up and Q&A","Educational aims + +• Clarify the role of corporate entrepreneurship +• Explain theoretical concepts and mechanisms behind corporate entrepreneurship +• Enable students to critically appraise alternative approaches to corporate entrepreneurship +• Enable students to evaluate the boundaries and risks of corporate entrepreneurship + +Learning outcomes + +On successful completion of this module students will be able to: + +• Create and evaluate concepts related to corporate entrepreneurship +• Assess the role of corporate entrepreneurship for creating and sustaining competitive advantage +• Make judgements about the organizational and managerial implications of corporate entrepreneurship +• Systematically choose between different routes of action","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of +one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, +groups of 3 approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Digital Entrepreneurship,12-M-UGF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This module provides an introduction into digital entrepreneurship and digital transformation. (1) Introduction +(2) Digital business models (3) Identifying and exploiting opportunities for digital entrepreneurship (4) Strategies +for creating competitive advantage in digital entrepreneurship (5) Digital marketing for entrepreneurs (6) Crowd- +funding for entrepreneurs (7) Design thinking (8) Lean startup (9) Platform ecosystems and online communities +(10) Digital strategy and digital transformation (11) The agile organization (12) Crowdsourcing (13) Cyberfraud (14) +Wrap-up and Q&A","Educational aims: Clarify the role of digital entrepreneurship and digital transformation. Explain theoretical con- +cepts and mechanisms behind digital entrepreneurship and digital transformation. Enable students to critically +appraise alternative approaches to digital entrepreneurship and digital transformation. Enable students to eva- +luate the boundaries and risks of digital entrepreneurship and digital transformation +Learning outcomes: On successful completion of this module students will be able to (1) Assess the role of di- +gital entrepreneurship and digital transformation for creating and sustaining competitive advantage, (2) Crea- +te and evaluate concepts related to digital entrepreneurship and digital transformation, (3) Make judgements +about the organizational and managerial implications of digital entrepreneurship and digital transformation, (4) +Systematically choose between different routes of action.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) log (15 to 20 pages) or c) oral examination (one candida- +te each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation +and present the key insights from their work.","Educational aims + +• Enable students to position their research +• Enable students to critically review a substantial body of literature in short time +• Enable students to develop a sound theoretical framework +• Enable students to create a research paper fully meeting academic standards + +Learning outcomes + +On successful completion of this module students will be able to: + +• Differentiate their research from previous work +• Adopt theoretical perspectives to understand complex phenomena +• Engage in comprehensive academic reasoning +• Articulate abstract and complex phenomena and relationships in written and oral form",S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Global Logistics & Supply Chain Management,12-M-GLSC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Global Logistics & Supply Chain Management"" acquaints students with advanced methods for the +planning of global production networks and demonstrates the application of these with the help of multiple case +studies.","After completing this course students can +(i) analyze and evaluate global production networks; +(ii) develop and apply appropriate methods to plan production networks; +(iii) evaluate the consequences of uncertainties in processes and apply concepts and methods to plan uncertain +processes.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Advanced Operations & Logistics Management,12-M-AOLM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Advanced Operations & Logistics Management"" acquaints students with advanced methods for the +planning of integrated production and logistics systems and demonstrates the application of these with the help +of multiple case studies","After completing this course students can +(i) analyze and evaluate integrated production and logistics systems; +(ii) develop and apply appropriate methods to plan complex production and logistics systems; +(iii) evaluate the consequences of uncertainties in processes, and +(iv) apply concepts and methods to plan uncertainties processes.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Seminar: Operations Management,12-M-SN-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,"With the help of topics from the area of ""Operations Management"", this course will provide students with know- +ledge and skills that will enable them to prepare a well-structured term paper and to present the key results of +their work.","Students will learn how to convince a critical audience by giving a presenation regarding a topic from the area +of Operations Management. By developing and giving a presentation as well as by answering questions the stu- +dents will practice their skills to deal with difficult communication situations and to argument for and against a +certain topic.",S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English",--,--,300 h,--,-- +Adaption and Continuous System Engineering,12-ACSE-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"Business Suite: The constantly changing environment with its organisational and IT-oriented developments +forces companies to adapt their standard business software solutions. With the help of dynamic adaptation +(Continuous System Engineering), this process of change can be supported effectively and efficiently. This mo- +dule discusses both the systematic implementation of adaptation steps (so-called customising) using the exam- +ple of the mySAP Business Suite and the concept of Continuous System Engineering using various practical ex- +amples. Business Apps: The course combines theory and practice in the area of cloud computing and ERP. Par- +ticipants gain an insight into the architecture of the ByDesign platform and are presented with an opportunity to +gain practical experience working with the corresponding software development kit. + +Content: + +• Fundamentals of cloud computing +• Cloud business solutions +• Architecture of the SAP Business ByDesign platform +• Platform adaption and extensibility +• Basics of software development in SAP Cloud Applications Studio +• Hands-on SDK: independently designing and developing a demo app","Business Suite: Students learn about the various ways of adapting a standard business software solution to the +special requirements of a company. They also develop a fundamental understanding of the dynamic adaptation +of business software libraries. Based on selected examples from the SAP Business Suite that the acquired know- +ledge will be deepened by using case studies. Business Apps: The course imparts knowledge and delivers skills +in cloud computing for businesses, ERP systems architecture and software development at the example of the +SAP Business ByDesign platform. The independent planning, implementation and documentation of a business +app trains important core competencies of technology-oriented Business Informatics.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) oral examination (one can- +didate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Business Service Platforms 2,12-AGP2-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The next generation of business service platforms leads to a transformation of traditional industrial enterprises +into service businesses that generate a large proportion of value in developed economies. New ICT technologies +such as cloud computing, the Internet of Things and semantic technologies will contribute to the success of the- +se businesses in a similar way as ERP contributed to the success of industrial enterprises. But we are still at the +beginning of the evolution of business service platforms, which will have to become more adaptable to support +special business models and allow differentiating customer service processes. +The course will discuss different case studies on services businesses. The digital transformation of the software +industry into a service industry is the most prominent of these case.","Be aware of the growing economic importance of the service sector. Understand that services businesses in are +facing a special productivity problem, which could not be adressed by the same processes applied in the ma- +nufacturing industries. Understand the new ICT technologies we have at hand today to deliver smart solutions +for this problem. Be aware of the diversity of services business today where we have no evidence that a general +standard can be found applicable to most subsectors similar to the standardization achieved for the manufactu- +ring industries after twenty years of research.",V (2),"Written examination (approx. 60 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,"-- + +_x000C_" +Business Service Platforms 1,12-BSA-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"A next generation of enterprise systems called business service platforms is emerging using new disruptive tech- +nologies such as cloud computing, big data and mobility. These business service platforms apply the concept of +product platforms to software. They will +1. be services based +2. be offered as a service in the cloud +3. address new classes of users and types of business especially in the service business +4. allow for a high degree of business adaptability and extensibility. +5. be supplemented by a broad offer of partner add-ons supporting accelerated innovation. +These new business service platforms will play a key role in the digital transformation of the software industry.","Be aware of the big business productivity progress enabled by BIS in the last 50 years. Understand the limitati- +ons of these systems in spite of the digital transformation of the software industry ahead. Be able to critically as- +sess the business potential of new IC technologies. Understand the business demand for change. Understand +the necessary organizational learning needed to leverage new technology for business change management.",V (2),"Written examination (approx. 60 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Abbreviation,"Business Processes Organisation, Business Software and Process Industries",Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"ERP systems have become key elements of successful companies. Business processes in companies can no lon- +ger be managed without using such ERP systems. In financial departments of companies, such systems have be- +en used for a long time, but business processes e. g. for logistical tasks have so far not been supported by ERP +solutions. This module explains how this issue could be resolved as well as what constraints and what depen- +dencies have to be considered.","After completing this module, students should be able to +(i) know about actual business processes in companies; +(ii) understand selected problems in the organization and design of logistical business processes and work out +solutions; +(iii) know and design basic data structures and data flows of an ERP system; +(iv) map businesss processes within an ERP system; +(v) consider the specifics of a certain industry (e. g. the process industry) when organizing business processes; +(vi) map the core business processes within an ERP system.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Work and Information,12-ITA-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This module discusses relevant principles, concepts and applications of business information processing and its +impact on organisational and process structures in today's business world.","The expertise gained from other modules related to business management issues can be interpreted and clas- +sified in a certain way by participating in this module. For decisions in regards to human resources planning, in- +vestment, and a company's strategy, the students will get to know all the relevant concepts and interdependen- +cies, which come with taking information processing into account as the so called ""fourth"" factor of production.",V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Work Order Planning for Automated Manufacturing,12-M-AGAF-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The idea of integration of business information systems is primarily practiced and developed as an ERP system +in terms of business application areas, their temporal overlap (data warehouse), their spatial relationship (sup- +ply network) and connection of legal tasks (eGovernment). However, linking the commercial view of incoming cu- +stomer orders with the logistic or more technical view of the scheduling of production orders and the resulting +consequences for the processes is a critical success factor.","Linking research and lectures of the Institute of Robotics and Telematics as well as the orientation of the Chair of +Business Integration allows students a conceptual as well as practical insight into the challenges of this in the +future essential part of the operational automation development.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Topics in Business Information Systems 1,12-M-ATW1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer- +sity of Wuerzburg.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap- +prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: +approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Business Information Systems 2,12-M-ATW2-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.","The competences depend on the individual module, which has been taken to transfer these credits to the Univer- +sity of Wuerzburg.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap- +prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: +approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Information systems research,12-M-ISR-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,"The course provides an overview of theoretical scientific foundations, theories, research topics and methods of +international research in business informatics.","The module provides students with knowledge of: +(i) Exploration of classical themes of WI / IS research; +(ii) Getting to know the relevant paradigms, theories and methods; +(iii) Recognition of the interfaces to other areas of business administration and management practice; +(iv) Gain experience in finding and evaluation of scientific literature",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) oral examination (one candidate each: approx. 15 to 20 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) +Creditable for bonus +Language of assessment: German and/or English","40 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Databases 2,10-I=DB2-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Data warehouses and data mining; web databases; introduction to Datalog.,"The students have advanced knowledge about relational databases, XML and data mining.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, HCI.",150 h,--,-- +Compiler Construction,10-I=CB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Lexical analysis, syntactic analysis, semantics, compiler generators, code generators, code optimisation.","The students possess knowledge in the formal description of programming languages and their compilation. +They are able to perform transformations between them with the help of finite automata, push-down automata +and compiler generators.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,GE",150 h,--,-- +Information Retrieval,10-I=IR-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"IR models (e. g. Boolean and vector space model, evaluation), processing of text (tokenising, text properties), +data structures (e. g. inverted index), query elements (e. g. query operations, relevance feedback, query langua- +ges and paradigms, structured queries), search engine (e. g. architecture, crawling, interfaces, link analysis), me- +thods to support IR (e. g. recommendation systems, text clustering and classification, information extraction).","The students possess theoretical and practical knowledge in the area of information retrieval and have acquired +the technical know-how to create a search engine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,HCI,GE",150 h,--,-- +Artificial Intelligence 1,10-I=KI1-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Intelligent agents, uninformed and heuristic search, constraint problem solving, search with partial information, +propositional and predicate logic and inference, knowledge representation.","The students possess theoretical and practical knowledge about artificial intelligence in the area of agents, +search and logic and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI",150 h,--,-- +Artificial Intelligence 2,10-I=KI2-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Planning, probabilistic closure and Bayesian networks, utility theory and decidability problems, learning from +observations, knowledge while learning, neural networks and statistical learning methods, reinforcement lear- +ning, processing of natural language.","The students possess theoretical and practical knowledge about artificial intelligence in the area of probabilistic +closure, learning and language processing and are able to assess possible applications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,SE,IS,HCI,GE",150 h,--,-- +E-Learning,10-I=EL-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Learning paradigms, learning system types, author systems, learning platforms, standards for learning systems, +intelligent tutoring systems, student models, didactics, problem-oriented learning and case-based training sy- +stems, adaptive tutoring systems, computer-supported cooperative learning, evaluation of learning systems.","The students possess a theoretical and practical knowledge about eLearning and are able to assess possible ap- +plications.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,HCI,GE",150 h,--,-- +Analysis and Design of Programs,10-I=PA-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Program analysis, model creation in software engineering, program quality, test of programs, process models.","The students are able to analyse programs, to use testing frameworks and metrics as well as to judge program +quality.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IS,ES,GE",150 h,--,-- +Professional Project Management,10-I=PM-182-m01,Institute of Computer Science,holder of the Chair of Computer Science III,5,numerical grade,1 semester,graduate,"Project goals, project assignment, project success criteria, business plan, environment analysis and stakeholder +management, initialisation, definition, planning, execution/control, finishing of projects, reporting, project com- +munication and marketing, project organisation, team building and development, opportunity and risk manage- +ment; conflict and crisis management, change and claim management; contract and procurement management, +quality management, work techniques, methods and tools; leadership and social skills in project management, +program management, multiproject management, project portfolio management, PMOs; peculiarities of software +projects; agile project management/SCRUM, combination of classic and agile methods.","The students possess practically relevant knowledge about the topics of production management and/or pro- +fessional project management. They are familiar with the critical success criteria and are able to initiate, define, +plan, control and review projects.",V (4),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IT, IS, ES, LR, HCI, GE.",150 h,--,-- +Algorithms for Geographic Information Systems,10-I=AGIS-161-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Algorithmic foundations of geographic information systems and their application in selected problems of acqui- +sition, processing, analysis and presentation of spatial information. Processes of discrete and continuous opti- +misation. Applications such as the creation of digital height models, working with GPS trajectories, tasks of spa- +tial planning as well as cartographic generalisation.","The students are able to formalise algorithmic problems in the field of geographic information systems as well as +to select and improve suitable approaches to solving these problems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IS,HCI",150 h,--,-- +Real-Time Interactive Systems,10-HCI=RIS-182-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"This course provides an introduction into the requirements, concepts, and engineering art of highly interactive +human-computer systems. Such systems are typically found in perceptual computing, Virtual, Augmented, Mixed +Reality, computer games, and cyber-physical systems. Lately, these systems are often termed Real-Time Interac- +tive Systems (RIS) due to their common aspects. +The course covers theoretical models derived from the requirements of the application area as well as common +hands-on and novel solutions necessary to tackle and fulfill these requirements. The first part of the course will +concentrate on the conceptual principles characterizing real-time interactive systems. Questions answered are: +What are the main requirements? How do we handle multiple modalities? How do we define the timeliness of +RIS? Why is it important? What do we have to do to assure timeliness? The second part will introduce a concep- +tual model of the mission-critical aspects of time, latencies, processes, and events necessary to describe a sy- +stem's behavior. The third part introduces the application state, it's requirements of distribution and coherence, +and the consequences these requirements have on decoupling and software quality aspects in general. The last +part introduces some potential solutions to data redundancy, distribution, synchronization, and interoperability. +Along the way, typical and prominent state-of-the-art approaches to reoccurring engineering tasks are discussed. +This includes pipeline systems, scene graphs, application graphs (aka field routing), event systems, entity and +component models, and others. Novel concepts like actor models and ontologies will be covered as alternative +solutions. The theoretical and conceptual discussions will be put into a practical context of today's commercial +and research systems, e.g., X3D, instant reality, Unity3d, Unreal Engine 4, and Simulator X.","After the course, the students will have a solid understanding of the boundary conditions defined by both, the +physiological and psychological characteristics of the human users as well as by the architectures and technolo- +gical characteristics of today's computer systems. Participants will gain a solid understanding about what they +can expect from today's technological solutions. They will be able to choose the appropriate approach and tools +to solve a given engineering task in this application area and they will have a well-founded basis enabling them +to develop alternative approaches for future real-time interactive systems.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): HCI. +Cf. Section 3 Subsection 3 Sentence 8 FSB (subject-specific provisions).",150 h,--,-- +Logic Programming,10-I=LP-172-m01,Institute of Computer Science,holder of the Chair of Computer Science I,5,numerical grade,1 semester,graduate,"Logic-relational programming paradigm, top-down evaluation with SLD(NF) resolution. Introduction to the logic +programming language Prolog: recursion, predicate-oriented programming, backtracking, cut, side effects, ag- +gregations. Connection to (deductive) databases. Comparison with Datalog, short introduction of advanced con- +cepts like constraint logic programming.","The students have fundamental and practicable knowledge of logic programming. They are able to implement +compact and declarative programs in Prolog, and to compare this approach to the traditional imperative pro- +gramming paradigm.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +SE, IT, IS.",150 h,--,-- +Machine Learning for Natural Language Processing,10-I=NLP-182-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture conveys advanced knowledge about methods in computational text processing. To this end, it pres- +ents state of the art models and techniques in the area of machine learning, as well as their technical back- +ground, and their respective applications in Natural Language Processing. As one important building block of +almost all modern NLP-models, different techniques for learning representations of words, so called Word Em- +beddings, are presented. Starting from this we cover, among others, models from the area of Deep Learning, li- +ke CNNs, RNNs and Sequence-to-Sequence architectures. The theoretical foundations of these models, like their +training with Backpropagation, are also covered in depth. For all models presented in the lecture, we show their +application to problems like sentiment analysis, text generation and machine translation in practice.","The participants have solid knowledge on problems and methods in the area of computational text processing +and are able to identify and apply suitable methods for a specific task.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IS, HCI.",150 h,--,-- +Medical Informatics,10-I=MI-161-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Electronic patient folder, coding of medical data, hospital information systems, operation of computers in infir- +mary and functional units, medical decision making and assistance systems, statistics and data mining in medi- +cal research, case-based training systems in medical training.","The students possess theoretical and practical knowledge about the application of computer science methods in +medicine.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,IS,HCI,GE",150 h,--,-- +Performance Engineering & Benchmarking of Computer Systems,10-I=PEB-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"Introduction to performance engineering of commercial software systems, performance measurement techni- +ques, benchmarking of commercial software systems, modelling for performance prediction, case studies.","The students possess a fundamental and applicable knowledge in the areas of performance metrics, measure- +ment techniques, multi-factorial variance analysis, data analysis with R, benchmark approaches, modelling with +queue networks, modelling methods, resource demand approximation, petri nets.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Programming with neural nets,10-I=PNN-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Overview over NN, implementation of important NN-architectures like FCN, CNN and LSTMs, practical example for +NN-architectures, among others in the area of image and language processing.","Knowledge about possible applications and limitations of NN, for important architectures (eg. FCN, CNN, LSTM) +and how they are implemented in NN-tools like Tensorflow/Keras, ability to program network structures from lite- +rature, to prepare data and solve concrete tasks for NN.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IT, IS, HCI, GE.",150 h,--,-- +Robotics 1,10-I=RO1-182-m01,Institute of Computer Science,holder of the Chair of Computer Science VII,8,numerical grade,1 semester,graduate,"History, applications and properties of robots, direct kinematics of manipulators: coordinate systems, rotations, +homogenous coordinates, axis coordinates, arm equation. Inverse kinematics: solution properties, end effec- +tor configuration, numerical and analytical approaches, examples of different robots for analytical approaches. +Workspace analysis and trajectory planning, dynamics of manipulators: Lagrange-Euler model, direct and inver- +se dynamics. Mobile robots: direct and inverse kinematics, propulsion system, tricycle, Ackermann steering, ho- +lonomes and non-holonome restrictions, kinematic classification of mobile robots, posture kinematic model. +Movement control and path planning: roadmap methods, cell decomposition methods, potential field methods. +Sensors: position sensors, speed sensors, distance sensors.","The students master the fundamentals of robot manipulators and vehicles and are, in particular, familiar with +their kinematics and dynamics as well as the planning of paths and task execution.","V (4) + Ü (2) +Module taught in: English","written examination (approx. 60 to 90 minutes) +Separate written examination for Master's students. +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IS, +ES, LR, HCI, GE.",240 h,--,-- +Security of Software Systems,10-I=SSS-172-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,"The lecture provides an overview of common software vulnerabilities, state-of-the-art attack techniques on mo- +dern computer systems, as well as the measures implemented to protect against these attacks. In the course, +the following topics are discussed: + +• x86-64 instruction set architecture and assembly language +• Runtime attacks (code injection, code reuse, defenses) +• Web security +• Blockchains and smart contracts +• Side-channel attacks +• Hardware security","Students gain a deep understanding of software security, from hardware and low-level attacks to modern con- +cepts such as blockchains. The lecture prepares for research in the area of security and privacy, while the exerci- +ses allow students to gain hands-on experience with attacks and analysis of systems from an attacker's perspec- +tive.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): SE, +IS, LR, HCI, ES. +Basic programming knowledge in C is required.",150 h,--,-- +Discrete Event Simulation,10-I=ST-161-m01,Institute of Computer Science,holder of the Chair of Computer Science III,8,numerical grade,1 semester,graduate,"Introduction to simulation techniques, statistical groundwork, creation of random numbers and random varia- +bles, random sample theory and estimation techniques, statistical analysis of simulation values, inspection of +measured data, planning and evaluation of simulation experiments, special random processes, possibilities and +limits of model creation and simulation, advanced concepts and techniques, practical execution of simulation +projects.","The students possess the methodic knowledge and the practical skills necessary for the stochastic simulation of +(technical) systems, the evaluation of results and the correct assessment of the possibilities and limits of simu- +lation methods.",V (4) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,IS,ES,GE",240 h,--,-- +Software Architecture,10-I=SAR-161-m01,Institute of Computer Science,holder of the Chair of Computer Science II,5,numerical grade,1 semester,graduate,Current topics in the area of aerospace.,"The students possess a fundamental and applicable knowledge about advanced topics in software engineering +with a focus on modern software architectures and fundamental approaches to model-driven software enginee- +ring.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES",150 h,--,-- +NLP and Text Mining,10-I=STM-162-m01,Institute of Computer Science,holder of the Chair of Computer Science VI,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of NLP and text mining, properties of text, sentence boundary de- +tection, tokenisation, collocation, N-gram models, morphology, hidden Markov models for tagging, probabili- +stic parsing, word sense disambiguation, term extraction methods, information extraction, sentiment analysis. +The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing mostly for English. They are able to solve problems through the methods +taught. They have gained experience in the application of text mining algorithms.","The students possess theoretical and practical knowledge about typical methods and algorithms in the area of +text mining and language processing. They are able to solve practical problems with the methods acquired in +class. They have gained experience in the application of text mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +IT, HCI.",150 h,--,-- +Project - Current Topics in Computer Science,10-I=PRJAK-162-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Completion of a project task (in Teams).,The project allows participants to work on a problem in computer science in teams.,P (4),"project report (10 to 15 pages) and presentation of project (15 to 30 minutes) +Each project is offered one time only. The project will not be repeated; there will not be another project with the +same topic. Assessment can, therefore, only be offered for the project offered in the respective semester. +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): AT, +SE, IT, IS, ES, LR, HCI, GE.",150 h,--,-- +International Marketing,12-M-IMM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +The module builds on the knowledge acquired during the Bachelor's degree programme or the Grundstudium +(stage I studies). It provides a systematic introduction to strategic marketing decisions in global and internatio- +nal contexts. These are explained mainly by Porter's diamond and cluster models. Another focus is on internatio- +nalisation strategies, which require country analyses and decisions on the selection of national markets as well +as a timing of the countries market development. In addition, the module discusses different strategies for mar- +ket entry and market development. + +Outline of syllabus: +1. Internationalisation of the economy and regional integration processes + +• Globalisation +• Competitiveness of countries, industries and companies in an international context + +2. International strategic marketing decisions + +• Market entry forms +• Market development strategies +• Timing strategies +• International organisation structures + +3. Theories and strategies of internationalisation + +• Foreign trade theory +• Multinational enterprise +• Internationalisation strategies + +Reading: +Meffert, H. / Burmann C. / Becker, C.: Internationales Marketing-Management, Stuttgart etc. (most recent editi- +on). +Berndt, R. / Fantapié-Altobelli C. / Sander M.: Internationales Marketing-Management, Berlin etc. (most recent +edition).","Students acquire in-depth skills in the field of strategic and operational management with particular attention to +the international context. Students achieve particular expertise in the analysis, assessment and implementation +of international business decisions and gain skills thus guiding the execution of marketing and management po- +sitions in globally-active companies.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Brand Management & Market Research,12-M-MM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +At the beginning of the 21st century, marketing - until then interpreted as a market-oriented corporate manage- +ment approach - was further developed to be seen as the entrepreneurial task of creating ""shared value"" for the +organisation on the one hand and - broadly speaking - for society on the other hand. This idea leads to high re- +quirements regarding the strategic sustainable positioning of the brand as well as brand management itself. + +Outline of syllabus: +1. Brand leadership and brand assessment +2. Brand leadership, identity and relevance according to David Aaker's approach +3. Brand strategies +4. Consumer behaviour +5. Market research methods and the development of brand strategies +6. Market research methods","Based on the theories of Meffert and Aaker, students will gain a profound understanding for brand leadership, +which will be deepened by many pracital implications and examples. Provided by cases studies and market re- +search tools, it's the defined goal of this lecture to convey an in-depth knowledge for consumer behavior and su- +stainable brand management.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Strategic Networks in Industry,12-M-MS-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"The primary object of this course is to gain a detailed understanding of strategic networks and of the phenome- +non of clustering in the industrial industry. The example of the international automotive industry is used for clari- +fication of the theoretical contents. +The focus is on marketing in industrial companies and also on CSR - CSR is considered the ""driver"" of sustaina- +ble innovations - as well as the different strategy types of sustainable innovations. +Outline of syllabus: +1. Strategic networks and clusters in industrial industries such as the automotive industry +2. Transaction types of Williamson as well as strategic cooperation between automobile manufacturers and sup- + +pliers + +3. Management of business types, in particular the business of suppliers in the automotive industry +4. Cluster and entrepreneurship activities +5. Sustainable innovation strategies","By the end of the course, students gain a profound understanding above the basics of network research. Further- +more students will aquire sectoral knowledge of the automotive industry as well as detailed cluster skills.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Strategic Marketing,12-M-SM-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Marke-,5,numerical grade,1 semester,graduate,"Description: +The module raises awareness in students of the relevance and necessity of strategic management in a competiti- +ve and dynamical competitive process. + +Content: +Based on the marketing strategies as well as the stakeholder and entrepreneurship approaches, this module +discusses the roots of the concept of strategy in marketing based on Drucker, Porter, Ansoff and Mintzberg. The +focus of the module is on thinking in competitive advantages, which is directly related to responsible leadership. + +Outline of syllabus: +1. Competitive dynamics requires strategy and leadership +2. Marketing strategies, stakeholder management and entrepreneurship +3. Objectives and tasks of corporate governance in management practice +4. Competitive forces, strategies and benefits according to Michael Porter +5. Growth strategies and marketing myths +6. Future technologies, new businesses and dynamic capabilities +7. Nature and principles of responsible management + +Reading: +Barnard, CI (1938): The Functions of the Executive, Harvard University Press, Cambridge, Massachusetts. +Eschenbach, R.; Eschenbach, S.; Kunesch, H. (2008): Strategische Konzepte: Management-Ansätze von Ansoff +bis Ulrich, 5th ed., Schäffer-Poeschel Stuttgart. +Freeman, RE (2010): Strategic Management: A Stakeholder Approach, Cambridge University Press. +Grant, R. M.; Nippa, M. (2006): Strategisches Management: Analyse, Entwicklung und Implementierung von Un- +ternehmensstrategien, 5th ed., Pearson Munich. +Hinterhuber, H. H. (2011): Strategische Unternehmensführung -- I. Strategisches Denken, 8th ed., Erich Schmidt +Verlag, Berlin. +Hungenberg, H. (2012): Strategisches Management in Unternehmen: Ziele -- Prozesse -- Verfahren, 7th ed., +Gabler, Wiesbaden. +Johnson, G.; Scholes, K.; Whittington, R. (2009): Fundamentals of Strategy, 1st ed., Financial Times and Prentice +Hall Harlow. +Kotler, P.; Berger, R.; Bickhoff, N. (2010): The Quintessence of Strategic Management, Springer, Heidelberg. +Laasch, O.; Conaway RN (2014): The Principles of Responsible Management: Global Sustainability, Responsibili- +ty, and Ethics, Cengage Stamford. +Meffert, H.; Burmannn, C.; Kirchgeorg, M. (2012): Marketing -- Grundlagen marktorientierter Unternehmensfüh- +rung, 11th ed., Gabler, Wiesbaden. +Meyer, M. (1995): Ökonomische Organisation der Industrie: Netzwerkarrangements zwischen Markt und Unter- +nehmung, Gabler, Wiesbaden. +Müller-Stewens, G.; Lechner, C. (2011): Strategisches Management -- Wie strategische Initiativen zum Wandel +führen, 4th ed., Schäffer-Poeschel Stuttgart. +Porter, M. (1999): Wettbewerb und Strategie, Econ Munich. (Original: Porter, M.: On Competition, Boston, 1998.) +Porter, M. (2014): Wettbewerbsvorteile -- Spitzenleistungen erreichen und behaupten, 8th ed., Campus Frank- +furt / New York. (Original: Porter, M.: Competitive Advantage, New York, 1985) + +Porter, M. (2013): Wettbewerbsstrategie -- Methoden zur Analyse von Branchen und Konkurrenten, 12th ed., +Campus, Frankfurt / New York. (Original: Porter, M.: Competitive Strategy, New York, 1980) +Welge, M. K.; Al-Laham, A. (2012): Strategisches Management: Grundlagen -- Prozesse -- Implementierung, 6th +ed., Springer Wiesbaden.","The students have a deeper understanding of the sustainable corporate management and have the basics of the +competitive process and competitive dynamics available. In addition, they can use the acquired knowledge, whi- +le taking into account the conventional problems of the strategic and sustainable management, to solve busi- +ness case studys on their own.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Industrial Management 4,12-M-BE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This course will develop the objectives, principles and structure of electronically supported procurement proces- +ses with a special focus on catalogue-based procurement systems, electronic tendering systems, electronic (re- +verse) auctions, e-marketplaces, supplier relationship management systems and eSupply chain management sy- +stems.","The students will be able to describe and evaluate both the potentials and goals of electronic supported pro- +curement systens and will be able to design appropriate systems for real-life applications. Students will get in- +sight into the essentials of operational procurement management, especially e-procurement with a focus on ca- +talog-based procurement systems, electronic tendering systems, electronic (reverse) auctions, e-marketplaces, +supplier relationship management systems and eSupply chain management systems. After completing this mo- +dule, students can define and analyze the related tasks and processes and show or develop theory-based and +application-oriented possible solutions at a high professional level.",V (2) + Ü (2),"a) Written examination (approx. 40 to 60 minutes) or +b) Presentation (approx. 20 Minutes) and term paper (15 to 20 pages), weighted 1:1 or +c) Term paper (30 to 40 pages) or +d) entirely or partly computerised written examination (approx. 60 minutes) or +e) Portfolio (approx. 20 pages) +Creditable for bonus +Language of assessment: German and/or English","20 places. +(1) A total of 15 places will be allocated to students of the Master's degree programmes Management as well as +International Economic Policy. +Should the number of applications exceed 15, these places will be allocated by lot. A waiting list will be maintai- +ned and places re-allocated by lot as they become available. +(2) A total of 5 places will be allocated to students of the Master's degree programme Information Systems. +Should the number of applications exceed 5, these places will be allocated by lot. A waiting list will be maintai- +ned and places re-allocated by lot as they become available. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.","Module can be taught in form of E Learning course, seminar, workshop etc.",150 h,--,-- +Industrial Management 2,12-M-LA-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module analyses and classifies approaches of production planning and control. In addition, it develops +methods and models of lot sizing and scheduling. The focus is on the determination of optimal production and +transport volumes as well as the planning of orders and manufacturing orders.","Students learn essential concepts, principles and methods of production planning and control with emphasis on +the determination of optimal production and transport volumes as well as the planning of production and order +sequences. Then, based on this expertise related knowledge broadening and deepening, essential competen- +cies are conveyed, which allow the imaging of realistic situations and problems using mathematical and quanti- +tative models for the derivation and assessment of alternative courses of action. After completion of the modu- +le students can answer, analyze and structure questions of production planning and control, goal-oriented. They +can also arrange the planning areas in the overall business context and have an in-depth overview of the produc- +tion planning and control.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Industrial Management 1,12-M-SBM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"The course addresses central issues of strategic supply management. The supply function of the company +(purchasing, materials management, procurement logistics) and its strategic importance is analysed and basic +methods are developed that are relevant in this area.","Students learn the principles of performance-oriented optimization of all procurement activities to develop long- +term, competitively sensitive potential for success. After completion of the module students are able to prepa- +re structured, to goal-oriented analyze and to respond to performance-oriented issues of strategic procurement +based on key instruments. Students are able to accurately classify the tasks of the procurement and to describe +and discuss their strategic importance and dominate essential methods and procedures used in this area to ap- +ply.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Industrial Management 3,12-M-SPM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Industrial,5,numerical grade,1 semester,graduate,"This module will discuss contents and procedures of strategic production management and, in particular, plan- +ning and control concepts. +Students will become familiar with the essentials of strategic production management. Theoretical and analyti- +cal models will be used for analysing both economic and ecological issues. In addition, the module will discuss +principles of value structure optimisation and will develop competences regarding the development of integra- +ted mathematical models.","After completion of the module students are able to process, to analyze and answer questions of operations +strategy structured and goal-oriented in a global context using appropriate methods. Furthermore, they know +the main strategic tasks and objectives in production management and evaluate and apply planning and control +concepts for the production in realistic application situations.","V (2) + Ü (2) +Course type: might also be offered as eLearning, seminary, workshop, etc.","a) written examination (approx. 40 to 60 minutes) or b) presentation (approx. 20 minutes) and term paper (15 to +20 pages), weighted 1:1 or c) term paper (approx. 30 to 40 pages) or d) entirely or partly computerised written ex- +amination (approx. 60 minutes) or e) portfolio (approx 20 pages) +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Legal Foundations of Risk Management and Compliance,12-M-RM1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,2,numerical grade,1 semester,graduate,"Content: This module analyses the presentation of opportunities and risks in financial reports, i. e. annual or in- +terim reports, in conjunction with selected value-based management and profitability analysis approaches. + +Outline of syllabus: +1. Basics of financial reporting and risk management; +2. Practice of risk reporting; +3. Profitability analysis according to Penman; +4. Value-based management and risk management; +5. Residual income and business valuation; +6. Analysis of equity risk; +7. Analysis of credit risk; +8. Risk management monitoring by audit committees and auditors. + +Reading list to be provided in class.","After completing the course, the students will be able +1. to present the relation between risk management and financial reporting; +2. to analyze and solve independently complex problems with respect to the presentation of opportunities and + +risk in financial reports based on national and international standards; + +3. to identify the relation between risks and value-based management; +4. to evaluate independently selected research results concerning risk reporting and desing own research- or + +practice-oriented projects.",V (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus","30 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,60 h,--,-- +Financial Statement Analysis and Business Valuation,12-M-UA-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,5,numerical grade,1 semester,graduate,"Fundamental investing involves valuation, and much of the information for valuation is contained in financial +statements. This module provides a basic understanding of financial statement analysis, particularly on how to +extract value-relevant information from financial statements, carry out financial statement analysis, and use fi- +nancial data to value corporations. The module also provides the necessary tools to gain insights into what ge- +nerates value in a corporation.","Students can understand publicly traded companies' financial statements (US GAAP/IFRS), identify value-rele- +vant information in financial statements, and use this information for valuation. They know the relevant techni- +ques to evaluate financial statements and understand the fundamental role of financial information in the valua- +tion process. Students can apply valuation technics to real-world cases and recommend investment decisions.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Philosophy of Science and Ethics in Business Management and Economics,12-M-WEW-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Financial Accounting,10,numerical grade,1 semester,graduate,"This module will take the form of a seminar. Participants will independently work on a problem in economic poli- +cy or will review an important publication on a topic in economics.",Students are able to present the status of a current project in a talk as well as to discuss and defend it.,S (2),"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1 +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Risk Management - Concepts and Systems,12-RM-KS-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Accoun-,5,numerical grade,1 semester,graduate,"Concepts: The course will provide students with an overview of the main goals, contents, methods and instru- +ments of opportunity and risk management in industrial and commercial enterprises. Systems: The course will +provide students with an overview of the design and functionality of essential information systems for risk mana- +gement.","Concepts: After completion of the module students have a sound understanding of basic concepts, processes, +methods and tools of risk management. They are able to justify the duties and functions of risk management in +the company in theory and practice. They can also evaluate proposed solutions for the design of a risk manage- +ment system, analyze selected issues of risk management and building on that, develop their own solutions. Sy- +stems: After completing this module, students can +(i) judge legal, organizational and methodological requirements for the implementation of risk management pro- +cesses in a risk management information system (RMIS); +(ii) understand the technical basis for RMIS; +(iii) estimate the different characteristics of various information systems for the RM; +(iv) understand the workings of RMIS.",V (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu- +tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) +Language of assessment: German and/or English +creditable for bonus","25 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,150 h,--,-- +Discounted Cashflow,12-M-CF1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The module covers discounted cash flow (DCF) methods under certainty as well as uncertainty in the context of +the valuation of unlevered and levered companies. Furthermore, tax aspects as well as their influence on the +company value are considered. + +Syllabus: + +1. Introduction +2. DCF Theory under certainty + +1. NPV without taxes +2. NPV with personal taxes +3. NPV with corporate taxes +3. DCF Theory under uncertainty + +1. DCF basics +2. Valuation of unlevered companies +3. Valuation of levered companies + +4. Practice of DCF methods","After completion of this module, the students will know a variety of discounted cashflow techniques and are able +to apply properly them in order to evaluate projects or firms.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Portfolio and Capital Market Theory,12-M-CF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module conveys profound knowledge of individual portfolio choices and on this basis the most important +capital market theory (namely capital asset pricing model) is introduced, including its assumptions, implications +and extensions. + +Syllabus: + +1. Modern Portfolio Selection + +1. 2 Asset-Case +2. Multiple-Asset-Case +3. Critique of Portfolio Theory + +2. Capital Asset Pricing Model + +1. Assumptions and Derivation +2. Implications + +3. Empirical Aspects, Extensions and Alternatives","This module enables the students + +(i) to explain and to determine the optimal capital market position of an investor given the different investment +opportunities and individual utility function; + +(ii) to understand and use the central CAPM propositions for valuating risky assets.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Risk Management and Corporate Finance,12-M-CF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"This module deals with the valuation and use of classical derivatives in financial markets. In particular, futures, +swaps and options are considered as well as their possible applications in the context of financial risk manage- +ment. In particular, students will be introduced to the theory involved in pricing options, as well as important va- +luation parameters. In addition, some established risk measures such as value-at-risk are discussed. +1. Introduction +2. Futures & Forwards +3. Swaps +4. Options +5. Measures of risk","Upon completion of this module students will be able to, + +(i) independently determine the fair value of the derivatives discussed, as well as + +(ii) to understand and evaluate common capital market hedging strategies.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Risk measurement and risk valuation: Concepts and applications for banks,12-M-CF5-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Corporate Finance,5,numerical grade,1 semester,graduate,"The course augments the usual consideration of symmetric risk metrics by introducing metrics for downside risks +and the concept of risk as a capital requirement. The focus for applications in banks lies in the treatment of risks +with regard of supervisory regulations.","After completing the course “Risk measurement and risk valuation: Concepts and applications for banks” the +students are able +1. to judge the appropriateness and problems of asymmetric risk measures, +2. to address essential risks in banks and to understand their handling by supervisory regulations as well as +3. to realize the concept of risk as a capital requirement being the systematic base for these aspects in the ban- + +king sector.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Economics of Tax Planning,12-M-SP-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This course deals with tax effects on fundamental economic decisions. Taxes are integrated into standard mo- +dels for investment decisions, financing decisions, firm valuation, dividend policy and remuneration of employ- +ees. Therefore, the interaction of corporate and personal income taxes is analysed. +A reading list in English is available on request.","This course enables students to +(i) combine their knowledge of tax law with microeconomic analyses in the areas of corporate and personal fi- +nance; +(ii) analyze the effect of taxes on fundamental economic decisions, e.g. investment and financing decisions, eva- +luation of investment, financial assets, forms of remuneration for employees including managing and assessing; +(iii) read and discuss research and policy papers in the field of taxation.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one +candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Tax Accounting,12-M-STB-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Taxation,5,numerical grade,1 semester,graduate,"This module introduces the various methods of income recognition in the German Income Tax Code (Einkommen- +steuergesetz, EStG). It discusses the main reporting and valuation provisions as well as the specific problems +and techniques of income calculation for partnerships.","Students have in-depth knowledge of tax accounting of companies and are able to solve moderate to complex +problems of tax accounting in particular of sole proprietorships and partnerships using legal source.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) or c) oral examination of one +candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Incentives in Organizations,12-M-AO-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"Based on the classical principal-agent theory, this course discusses methodological and empirical aspects of in- +centives in organisations. It uses contents from advanced text books and original (mainly empirical) research ar- +ticles. + +Outline of syllabus + +1. Principal-agent theory + +2. Do top managers earn too much? (application) + +3. Performance-based payment + +4. Implementation of performance-based payment in companies (application) + +5. Seniority payment (with application) + +6. Financial incentives to work after retirement (with application) + +7. Efficiency wages (with case study) + +8. Team incentives (with case study)","Students acquire a working knowledge of key incentive models models, selected empirical applications and the +necessary econometric background. This enables them to identify the advantages and disadvantages of different +incentive systems that are applied in the enterprise context, to make informed management analyses and to cri- +tically evaluate current controversies and developments as well as to conduct their own research.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Human Resource Management and Industrial Relations,12-M-HRM-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Human Resource Management and,5,numerical grade,1 semester,graduate,"The lecture ""Human Resource Management and Industrial Relations"" introduces advanced theories, estimation +techniques and empirical results from the areas of human resources management and institutional frameworks +such as ithe different actors in ndustrial relations. + +Syllabus + +Introduction: Human Resource Management & Industrial Relationships + +Chapter 1: The employment contract [formal model] + +Chapter 2: Motivation [formal model] + +Chapter 3: Employee resistance against reorganisations [empirical study] + +Chapter 4: The role of works councils [formal model] + +Chapter 5: Works councils and the employer wage structure [empirical study] + +Chapter 6: The behaviour of labour unions [formal model] + +Chapter7: Learning process of employers [formal model and empirical study] + +Chapter8: Demographic challenges of HRM [formal model and empirical study]","The aim of the lectures is to enable students to understand and apply advanced theories, estimation techniques +and empirical results in the area human resource management and industrial relations on the basis of scientifc +literature.",V (2) + Ü (2),"a) Written examination (approx. 60 minutes) or +b) Term paper (approx. 15 pages) +Language of assessment: German and/or English","There are no restrictions with regard to available places for students of the Master's degree programmes Mana- +gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo- +mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca- +ted to students of other subjects; should the number of applications exceed the number of available places, the- +se places will be allocated by lot.",--,150 h,--,-- +Advanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation +and present the key insights from their work.","Educational aims + +• Enable students to position their research +• Enable students to critically review a substantial body of literature in short time +• Enable students to develop a sound theoretical framework +• Enable students to create a research paper fully meeting academic standards + +Learning outcomes + +On successful completion of this module students will be able to: + +• Differentiate their research from previous work +• Adopt theoretical perspectives to understand complex phenomena +• Engage in comprehensive academic reasoning +• Articulate abstract and complex phenomena and relationships in written and oral form",S (2),"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1 +Assessment offered: Once a year, winter semester +Language of assessment: German and/or English","20 places. (1) Should the number of applications exceed the number of available places, places will be allocated +by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted +number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo- +cated by lot as they become available.",--,300 h,--,-- +Corporate Strategy,12-M-UGF2-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,"This theory-led and application-oriented module provides you with critical knowledge and skills related to cor- +porate strategy—essential for anyone aspiring to take on leadership roles in their future career, may it be in the +private or public sector. The module goes beyond basic knowledge about strategic management provided by ba- +chelor-level modules. + +(1) Developing strategies in pursuit of competitive advantage + +(2) Corporate diversification + +(3) Vertical integration and outsourcing + +(4) Mergers & acquisitions + +(5) Dynamic strategies + +(6) Cooperative strategies + +(7) Corporate spin-offs and spin-outs + +(8) Internationalization strategies (I) + +(9) Internationalization strategies (II) + +(10) Strategic change + +(11) Corporate strategies and new technologies + +(12) Corporate governance and corporate social responsibility + +(13) Corporate communication and crisis management + +(14) Wrap-up and Q&A","Educational aims + +• Clarify the role of corporate strategy +• Explain theoretical concepts and mechanisms behind corporate strategy +• Enable students to critically appraise alternative approaches to corporate strategy +• Enable students to evaluate the boundaries and risks of corporate strategy + +Learning outcomes + +On successful completion of this module students will be able to: + +• Assess the role of corporate strategy for creating and sustaining competitive advantage +• Create and evaluate concepts related to corporate strategy +• Make judgements about the organizational and managerial implications of corporate strategy + +• Systematically choose between different routes of action","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) or c) oral examination of +one candicate each (approx. 10 to 15 minutes) or oral examination in groups (groups of 2 approx. 20 minutes, +groups of 3 approx. 30 minutes) +Language of assessment: English",--,--,150 h,--,-- +Change Management,12-M-CHA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly +analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis- +cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa- +tion is a universal principle. The module covers projects like merging two departments, restarting a department +with team building, conducting an employee survey, or developing a new mission statement. The majority of the +projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive +emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in- +struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles +in these processes and are able to use their knowledge for own future projects as well as to create their own so- +lutions in change processes.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Accounting in the Company Management,12-M-CIU-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"Within the module, theoretical basics of change management are covered. In addition, we present and jointly +analyze existing change projects in detail. We try to answer related questions, too. For example, the module dis- +cusses how to involve stakeholders in change, what motivates them to embrace change, and whether participa- +tion is a universal principle. The module covers projects like merging two departments, restarting a department +with team building, conducting an employee survey, or developing a new mission statement. The majority of the +projects are taken from the social sector, but can be transferred to industry and SMEs.","After participating the lecture, students will be able to understand the occurrence of resistance and massive +emotional reactions in change processes. Change processes can be critically analyzed and the use of typical in- +struments in change processes can be questioned. Students are able to identify the typical pitfalls and hurdles +in these processes and are able to use their knowledge for own future projects as well as to create their own so- +lutions in change processes.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Strategic Managerial Accounting,12-M-INST-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on accounting instruments, which are applied in the context of strategic management of +enterprises. First, it addresses important drivers of strategic decisions from a microeconomic perspective, such +as the emergence of cost and quality advantages in competition as well as scale and experience curve effects. +Second, the module covers analytical and heuristic techniques of planning and control. In the context of these +techniques, instruments of target costing, life cycle cost analysis, benchmarking and business wargaming are +discussed with regard to their theoretical foundation and fields of application.","Initially, knowledge about fundamental requirements concerning instruments of decision-making and behavior +control within enterprises is acquired. What is more, the module conveys obtaining knowledge about the strengt- +hs and weaknesses and therewith fields of application and limits of prevalent instruments of strategic corporate +management used by practitioners.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +"Coordination, Budgeting and Incentives in Organizations",12-M-KOBO-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"This module focuses on accounting-based instruments to control behavior in decentralized enterprises. The +course first discusses the role of accounting in the context of decision-making and behavioral controlling as well +as informational analyses. Afterwards, the most common instruments of behavioral controlling (budgeting, va- +lue-oriented management, transfer prices) are discussed with regard to theory and practice.","This module aims to provide knowledge in the context of behavioral control in enterprises. Knowledge about re- +quirements on instruments used for behavioral control are discussed and competences for deployment, struc- +ture and development of coordination tools are provided.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Project Management and Control,12-M-PROM-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on the discussion and critical examination of instruments and methods used in the context +of project management and control within enterprises. Both classic and agile approaches to project manage- +ment are considered. It covers characteristic features and structures of projects, their possible success factors, +methods and instruments of control and management of projects in various project phases. The theoretical basis +as well as potential applications of these instruments are discussed.","Initially, knowledge about fundamental requirements concerning instruments of project management and con- +trol is acquired. What is more, the module conveys knowledge about strengths and weaknesses and therewith +fields of application and limits of commonly used instruments and methods of practitioners. Competences wi- +thin the configuration and development of the project management and control as well as skills within the practi- +cal use are obtained.",S (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Accounting and Capital Markets,12-M-REKA-182-m01,Faculty of Business Management and Economics,"Holder of the Chair of Business Management, Management",5,numerical grade,1 semester,graduate,"The module focuses on financial and management accounting, their functions, possible configurations as well +as their impact on internal and external recipients under consideration of the institutional setting. In this con- +text, an economic perspective has priority over detailed legal arrangements and regulations by the standard set- +ters. Based on the theoretical foundations of information economics as well as decision-making and balance +sheet theories, typical issues concerning cost and managerial accounting as well as financial accounting and pu- +blicity are discussed.","Initially, a fundamental knowledge about the conception and impact of management and financial accounting +as information systems is acquired. In the following, the module mainly sharpens the understanding of the eco- +nomic impacts of the configuration of management and financial accounting. What is more, extensive knowled- +ge about possible impacts of changes in institutional general frameworks is covered. For example, changes in +valuation standards, publicity rules or regulations about the distribution of profits in enterprises and on capital +markets are considered.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Analytics & Decision Making,12-M-MADM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"The course ""Managerial Analytics & Decision Making"" discusses quantitative methods to structure and solve +a diverse set of management problems and demonstrates the application of modern methods with the help of +multiple case studies.","After completing this course students can +(i) better understand and structure problems; +(ii) apply important theoretical and empirical frameworks to practical problems that evaluate good and bad deci- +sion making; +(iii) implement advanced analytical methods to support decision making under risk.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Strategic Management of Global Supply Chains,12-M-SMGS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,"Description: +In the course ""Strategic Management of Global Supply Chains"", students will become familiar with the basic +principles of building an efficient global supply chain and will apply what they have learned working on multiple +case studies.","After completing this course students +(i) can apply the basic methods and concepts of supply chain management to practical settings and evaluate the +results, and +(ii) understand the effects of global value chains onto strategic company decisions.","V (2) + Ü (2) +Module taught in: English","written examination (approx 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Strategic Decisions and Competition,12-M-SDC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"1. Strategic situations and decision making + +2. Analyzing strategic situations with game theory + +1. Noncooperative simultaneous move games +2. Nash equilibrium +3. Models of oligopoly markets + +3. Dynamic Games + +1. Two(-multi) stage games and subgame perfect equilibrium +2. Role of commitment in dynamic situations +3. Models of advertising +4. Wage bargaining and unions + +4. Repeated Games + +1. Emergence of coordination in long interactions +2. Collusion between competing firms +3. Time consistent monetary policy + +5. Static games of incomplete Information + +1. Bayesian Nash equilibrium +2. Auctions + +6. Dynamic games of incomplete information + +1. Moral hazard and nonlinear pricing +2. Perfect Bayesian equilibrium +3. Signalling games +4. Job-market signalling +5. Corporate investment and capital structure","After successful completion of this class, the students should be familiar with economic models that can be +used to shape managerial strategy and aid in making decisions in strategic situations. Especially, by making use +of simple two stage games, they should be able to formulate dynamic policies in a wide variety of strategic situa- +tions. The students will acquire an intuitive understanding of the underlying economic mechanisms which emer- +ge from the analysis of game theoretic models for a wide variety of strategic situations arising in industrial eco- +nomics, marketing, organization, finance, trade and labor. Moreover, they will acquire skills which enable them +to make predictions in strategic situations by making use of simple mathematical models. By means of comple- +ting case based exercises, they will learn to transform real life business situations to an appropriate economic +model. Based on an analysis of this model, they will be able to devise optimal strategies and derive the corre- +sponding managerial implications. + +The course will be taught in English.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Theory of Industrial Organization,12-M-TI1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Theory of industrial organisation: +1. Monopoly pricing + +• Nonlinear pricing and mechanism design +• Dynamic pricing: experience goods, durable goods + +2. Oligopoly pricing + +• Static price and quantity competition in homogeneous and differentiated goods markets +• Comparative statics +• Equilibrium market structure + +3. Dynamic competition in oligopoly markets + +• Subgame perfect equilibrium and models of dynamic competition +• Repeated games and collusion +4. Strategic behaviour by incumbent firms +• Entry deterrence and predation +• Signalling and reputation + +5. Behavioral Industrial Organization + +• Reference Dependent Preferences and Framing Effects +• Time inconsistent behavior + +The course will be taught in English.","Students which complete this class will acquire a working knowledge of advanced theoretical models of compe- +tition in oligopoly markets as well as sophisticated pricing techniques in monopoly markets. They will learn the +conditions under which the predictions of these models are valid. They will become familiar with applications of +advanced game theoretic tools, such as dynamic models of competition, for studying interactions between firms +in markets. By means of comprehensive exercises, they will apply the methods they learn in class to practical- +ly relevant problems. They will be in a position to read academic papers on related topics, assess the strengths +and weaknesses of an approach, summarize and comment on these papers and suggest possible extensions.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +European Competition Policy,12-M-WPE-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Industrial Economics,5,numerical grade,1 semester,graduate,"Outline of syllabus: +1. Legal environment, competition laws +2. Market definition + +• Qualitative methods +• Simple quantitative methods +• Hypothetical monopoly test + +3. Horizontal agreements and collusion: repeated games and factors affecting likelihood of collusion +4. Horizontal mergers and collusion + +• Economic theory +• Efficiency effects +• Coordinated effects + +5. Vertical relations and contracts + +• Economic analysis of contracts +• ""More economic approach"" + +6. Abuse of dominant position + +• Classification of abusive conduct +• Economic analysis of abusive conduct and theory of harm + +The course will be taught in English.","After completion of the module students can use the advanced concepts introduced in the lecture of competiti- +on policy, including the legal framework, the trace models and methods for the study of competition policy issu- +es, as well as understand the approach of European competition policy in high profile cases. When they are con- +fronted with practical problems, they can refer to these cases, and the same logic to practical examples apply by +draining the relevant economic theories that identify variables to be measured and methodologies for assessing, +and based on that adequate conclusions for appropriate cases. They will sufficiently understand the subject in +order to open up that build upon literature in journals and being able to think critically.","V (2) +Module taught in: English","a) Written examination (approx. 60 to 120minutes) or +b) Term paper (15 to 20 pages) +Creditable for bonus +Language of assessment: English","There are no restrictions with regard to available places for students of the Master's degree programmes Mana- +gement, International Economic Policy, Information Systems, Wirtschaftsmathematik (Mathematics for Econo- +mics) and Chinese and Economics as well as China Business and Economics. A total of 20 places will be alloca- +ted to students of other subjects; should the number of applications exceed the number of available places, the- +se places will be allocated by lot.",--,150 h,--,-- +Econometrics 1,12-M-OE1-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Econometrics,5,numerical grade,1 semester,graduate,"Description: +This module deals with the basic concept and methodology of the ordinary least squares (OLS) regression mo- +del. In particular, model assumptions and properties are discussed and formally motivated. In addition, the mo- +dule examines linear restrictions on the model's explanatory variables as well as dummy variables and introdu- +ces tests to verify simple and multiple linear restrictions. + +Linear algebra is used as formal aid. + +Outline of syllabus: +1. Random variables +2. Important distributions +3. Point estimates +4. Simple linear regression model +5. Model assumptions +6. Model properties +7. Simple hypothesis tests +8. Multiple linear regression model +9. Linear restrictions +10. Dummy variables +11. Multiple hypothesis tests","The students acquire knowledge of the basics, concepts and methods used in the classical linear regression mo- +del and understand the role of econometrics in science and data analysis. In particular, they learn how to analy- +tically derive, calculate and interpret the coefficients, standard errors and p-values of a classic regression output +of the multiple regression model. Furthermore, they are able to formally state and motivate the assumptions and +properties of OLS and know how to deal with transformed and dummy variables. Additionally, students will be +able to test multiple linear restrictions on the parameters and will be able to apply these tests to real economic, +business and social science questions. +The competences acquired in this course serve as a prerequisite for ""Econometrics II"", ""Econometrics III"", ""Micro- +econometrics"" und ""Financial Econometrics"".","V (2) + Ü (2) +Module taught in: German (winter semester), English (summer semester)","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Advanced Microeconomics,12-M-AM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Contract Theory and Information Eco-,5,numerical grade,1 semester,graduate,"In a nutshell, microeconomic theory considers the behavior of individual economic agents and builds from this +foundation to a theory of aggregate economic outcomes, which then can be applied for conducting welfare ana- +lysis and giving policy advice. This lecture addresses the core building block of this thought complex: individu- +al decision making and behavior. Specifically, students will come to understand in detail the standard models of +riskless consumer choice, choice under risk and intertemporal choice and learn about the empirical challenges +and limitations of these models. + +Throughout the lecture, we will work with precise mathematical formalizations of the ideas that we want to think +and talk about. In consequence, a solid understanding of the mathematical toolbox of standard microeconomics +(e.g., differential calculus and constrained optimization; basic set theory; integration by parts) will be helpful as +it will allow to focus on the underlying economic intuition. However, every required mathematical concept will be +introduced and explained along the way, such that a strong interest in formal economic analysis is more import- +ant than an advanced mathematical background. + +The exposition is primarily based on the standard graduate textbooks + +• Mas-Colell, Whinston and Green (1995): “Microeconomic Theory” +• Jehle and Reny (2001): “Advanced Microeconomic Theory”","After completing the course students will be able to + +• explain essential findings of microeconomic theory, +• apply the involved methods to given stylized examples on their own, +• recognize in which real life situations and how the results can be applied.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Management and Economics 1,12-M-APW1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical +methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or presentation (approx. 30 to 45 +minutes) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Management and Economics 2,12-M-APW2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 to 90 minutes) or b) written examination (questions concerning mathematical +methodology; approx. 120 minutes) or c) term paper (approx. 15 to 20 pages) or d) presentation (approx. 30 to 45 +minutes) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 1,12-M-AWI1-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi- +ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration +(approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of +2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination +(approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Selected Topics in Business Information Systems 2,12-M-AWI2-161-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.","V (2) + Ü (2) +Course type: alternatively S instead of V + Ü","a) written examination (approx. 60 minutes) or b) written examination consisting entirely or partly of multi- +ple/single choice questions (approx. 60 minutes) or c) presentation (15 to 20 minutes) with written elaboration +(approx. 20 pages), weighted 1:2 or d) oral examination (one candidate each: approx. 10 to 15 minutes; groups of +2: approx. 20 minutes; groups of 3: approx. 30 minutes) or e) entirely or partly computerised written examination +(approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Digital Marketing I,12-M-DM1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Digitalization is rapidly changing our lives, including all types of business relationships. Therefore, new opportu- +nities and approaches have emerged in all areas of the marketing mix: Managers can choose from a wide variety +of new communication channels, such as social media networks, blogs, or messengers, and can engage in influ- +encer marketing and search engine optimization. They increasingly rely on online customer co-creation or crowd- +sourcing and create a wide variety of new digital products and services, often related to completely new busi- +ness models. Through price crawlers and price setting tools customers‘ price search behaviors have significant- +ly changed, requiring new price setting techniques. Artificial intelligence enables managers to automize and op- +timize many of these marketing processes, thus offering new opportunities and challenges for companies. Over- +all, digital marketing offers a tremendous variety of concepts and approaches to seize respective opportunities +and deal with related challenges, which will be largely highlighted and discussed in this course.","This course provides a broad overview about these new approaches of digital marketing. It explains the underly- +ing concepts of digital marketing and illustrates these approaches and concepts along numerous case studies. +After attending this course, students will have a broad as well as in-depth understanding of digital marketing +and its tools. Morever, they will understand of how to implement these tools successfully in business practice.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Digital Marketing II,12-M-DM2-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"Students are required to put themselves in the following business situation: + +A large corporation has just recruited you and your team members as the new heads of the marketing depart- +ment in one of the firm’s divisions in order to manage its general and digital marketing activities. Specifically, +it is your task to manage the corporation’s digital product portfolio, segmentation and positioning as well as its +marketing mix strategy over a period of 10 years. + +Structure of the class: + +• Long-term business simulation game (details see below) that students will play in groups +• Lectures and discussion rounds on strategic approaches to succeed over a duration of 10 periods","Studierende lernen in diesem Kurs, zentrale Konzepte des Online- und Offline-Marketings gezielt und bezogen +auf die jeweilige Unternehmenssituation anzuwenden. Der Kurs bildet somit die Brücke zwischen Theorievermitt- +lung und entsprechende Anwendung in der Unternehmenspraxis.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +E-Commerce I,12-M-EC1-182-m01,Faculty of Business Management and Economics,Holder of the Junior Professorship of Digital Marketing and,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches +and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in- +dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat- +egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti- +ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre- +sentations where the students (in groups) will either apply selected lecture topics to real-world business cases +or present the core aspects of research articles dealing with e-commerce topics in general.","This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as- +sessing business strategies.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +E-Commerce II,12-M-EC2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"E-commerce is a highly relevant field for almost all types of companies. However, the ecommerce approaches +and strategies applied by companies differ strongly depending on the respective firm context (e.g., in terms of in- +dustry, types of customers, types of products). In this seminar, students analyze the specific e-commerce strat- +egy of a selected firm. In doing so, they evaluate the strategies’ current and future potential and make suggesti- +ons for improvements and for addressing future trends. Furthermore, each lecture session will contain short pre- +sentations where the students (in groups) will either apply selected lecture topics to real-world business cases +or present the core aspects of research articles dealing with e-commerce topics in general.","This class enables students to gain insights into real-life e-commerce strategies and to train their abilities in as- +sessing business strategies.","V (2) +Module taught in: English","a) written examination (approx. 60 to 120 minutes) or b) term paper (15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +Real-Time Process Analytics,12-M-RTP-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The course teaches advanced approaches to process analytics. Students will learn to model and measure pro- +cesses and process execution based on past and present data.","After successfully completing the course, students should be able to +• Understand process modeling and process execution in an SOA +• OLAP analysis in a process warehouse +• Business Rules for BPM +• Complex Event Processing +• Event-driven BPM using CEP and Business Rules","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Data Science,12-M-TDS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"Data science is concerned with extracting knowledge and valuable insights from data assets. It is an emerging +field that is currently in high demand in both academia and industry. This course provides a practical introducti- +on to the full spectrum of data science techniques spanning data acquisition and processing, data visualization +and presentation, creation and evaluation of machine learning models. + +The course focuses on the practical aspects of data science, with emphasis on the implementation and use of +the above techniques. Students will complete programming homework assignments that emphasize practical +understanding of the methods described in the course.","Topics covered include: + +• Data acquisition and processing +• graph and network models +• text analysis +• working with geospatial data +• Usage of machine learning models (supervised and unsupervised)","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Information Systems 1,12-M-TIF1-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; +groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Topics in Information Systems 2,12-M-TIF2-182-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"This module serves the purpose of transferring credits from + +• courses taken at other German or non-German universities +• additional courses offered on a short-term basis +• courses offered by new Chairs that are yet to be included in the FSB (subject-specific provisions) + +The holders of the respective Chairs will ensure that the courses are eligible for credit transfer.","As a result of accrediting multiple kinds of modules, a description of acquired skills cannot be given.",V (2) + Ü (2),"a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: 10 to 15 minutes; +groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes) or c) term paper (approx. 15 to 20 pages) +Assessment offered: In the semester in which the course is offered +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Stochastic Models for Risk Analysis,12-RM-RA-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Point and interval estimation for the value at risk Point and interval estimation for the conditional value at risk +Prediction of value at risk in time series Risk of forecasts in time series, in particular exponential smoothing un- +der covariates Conditional heteroscedasticity: ARCH, GARCH, EGARCH, DVEC, BEKK, DCC Aggregated losses and +their empirical analysis Empirical analysis of statistical distributions Nonparametric bounds for the value at risk +and conditional value at risk Empirical estimation of nonparametric bounds for value at risk and conditional va- +lue at risk Market model: definition, derivation, parameters, empirical analysis Capital asset pricing model: de- +finition, parameters, empirical analysis Asset portfolios: definition, risk parameters Estimation of portfolio para- +meters: variance, value at risk, conditional value at risk, shortfall Optimum portfolios: concepts, theory, numeri- +cal analysis","The student is able to estimate risk measures and the parameters of risk models from data. In particular, the stu- +dent knows software packages and routines which enable empirical risk evaluation in a business context.",Ü (2) + V (2),Written examination (approx. 60 minutes),"30 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Stochastic Models for Risk Assessment,12-RM-RW-192-m01,Faculty of Business Management and Economics,Dean of Studies Mathematik (Mathematics),5,numerical grade,1 semester,graduate,"Etymological background of the risk concept Definitions of risk Basic concepts and terminology of stochastic risk +modelling: risk phenomenon, risk object, risk variable, risk source, risk factor, risk cause, direct peril, indirect +peril, loss under risk, profit under risk, loss variable, profit variable, risk distribution, risk indicator, risk parame- +ter Classification of business risks Risk policy, risk management Risk analysis: risk identification, risk descrip- +tion, risk exploration, risk-relevant measurements, risk evaluation, risk assessment, risk modelling Risk mana- +gement: risk minimisation, risk protection, risk avoidance, risk mitigation, bearing of risk, risk prevention Risk +control, risk monitoring Norms and standards of risk management: ISO 31000, ONR 49000 -- 49004, IEC/ISO +31010, COSO II, AIRMIC, IRM, ALARM FMEA (Failure Mode and Effect Analysis) as a tool of risk analysis and risk +assessment: historical and thematic background, methodology, discussion of the FMEA assessment methodo- +logy Risk matrix, risk diagram Score diagram Stochastic risk parameters and risk measures as distribution para- +meters Probability distributions: Gaussian, Laplace, Student's t, extreme value, logistic, exponential, Weibull, +gamma, negative Gaussian, Burr, hyperbolic, generalised hyperbolic Elementary stochastic risk measures: va- +riance, standard deviation, signal-to-noise ratio, coefficient of variation, Sharpe ratio, nonconformance probabi- +lity, expected shortfall, shortfall probability, risk parameters under reference values, Stone family Value at Risk +and Conditional Value at Risk: definition, formal representations, values under special probability distributions +Axioms of risk measures: distribution invariance, subadditivity, superadditivity, additivity, comonotonous additi- +vity, nonnegative homogeneity, translation invariance, convexity, continuity, coherence","The student knows the schemes and concepts of risk analysis, risk assessment, risk measurement, and the +theoretical background. The student knows the concepts of advanced stochastic risk modeling. In a practical +business situation, the student is able to identify an appropriate scheme of risk assessment and corresponding +meaningful risk measures.",V (2) + Ü (2),Written examination (approx. 60 minutes),"30 places. +Should the number of applications exceed the number of available places, places will be allocated as follows: +(1) Master's students of Information Systems will be given preferential consideration. +(2) The remaining places will be allocated to students of other subjects. +(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number +of available places, places will be allocated by lot among applicants from this group.",--,150 h,--,-- +Communication in Business and Economics,12-M-BUC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"The lecture names introductory relevant communication models. Furthermore, the theoretical models of PR are +discussed. The added value of communication for companies, business, politics, and science is explained. The +discrepancy between journalism and PR is discussed, as well as the basic elements, instruments, goals, and +forms of PR. The preparation and implementation of press meetings, conferences, campaigns, and events will +be systematically explained, and the central aspects of corporate communications will be outlined. The exerci- +se deals with the practical implementation of journalistic styles in the various media and provides an overview of +the possibilities and concepts of PR work across different media and target groups.","After participating in the module courses, students are able to understand and apply PR and its forms, elements +as well as methods and in a holistic context. Students learn professional competencies in the field of (business) +communication with regard to reflection, argumentation, and exchange as a PR consultant in different areas. In +addition, students will be able to apply concrete PR instruments in practice and prepare them professionally.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 minutes) +Language of assessment: English +creditable for bonus",--,--,150 h,--,-- +"Business Communication in Print, Online and Social Media",12-M-ECC-182-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"This module focuses on the relationship of offer characteristics with benefit aspects for the end consumer and +the business models on the part of the providers. Starting from the basics of editorial work and professional text +management, the new forms of communication management in social networks are presented. The focus of the +lecture is on the use of social media in campaigns (Facebook, Twitter, Instagram, Tiktok). There will also be exer- +cises on various Web 2.0 applications (e.g. online social networks) and on the collection and interpretation of +online market research data. However, crisis communication of companies will also be covered in particular opi- +nion-makers on the web as well as protest culture on the web.","By participating in the module courses, students acquire job-specific skills in research and interviewing. Stu- +dents are able to collect and organize information according to criteria of topicality and relevance. In addition, +students are taught journalistic expertise so that they are able to recognize the forms of presentation of news, re- +ports, and background reports with their media characteristics and communicative functions in different media +genres and create them themselves. Students will be able to prototype and design a social media campaign, de- +scribe the editorial and technical approach including feedback, response, and customer engagement. In additi- +on, students will be able to design counter-strategies for corporate communication crises.",V (2) + Ü (2),"written examination (approx. 60 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Managerial Practice Lectures,12-M-VGP-202-m01,Faculty of Business Management and Economics,Holder of the Professorship of Economic Journalism,5,numerical grade,1 semester,graduate,"In this lecture, we invite board members of publicly listed companies, SMEs and Startups to discuss contempo- +rary challenges of corporate management. + +Students gain sustainable insights into current management practices, challenges of corporate management in +various industries, and discuss pressing managerial issues with C-level executives. In individual and group as- +signments, students are required to connect management theories with the managerial challenges of the spea- +kers. + +Managers of the different companies are required to address the following questions that will foster a detailed +discussion at the end of each lecture: + +- What are the current challenges facing your company? + +- Which strategies do you employ to respond to these challenges? + +- How have leadership concepts and approaches changed in your company?","After participating in this module, students should be able to combine theoretical approaches with current chal- +lenges in management. The students obtain a realistic insight into a cross-section of the German economy. +Through discussions reports and group presentations students’ social skills are trained in addition to professio- +nal skills.",S (2),"portfolio (approx. 15 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Advanced Topics in Data Science,12-M-ATDS-211-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Analytics,5,numerical grade,1 semester,graduate,"In this course, students work on advanced data science projects. The course covers the entire data science work- +flow from data collection to data preparation to modeling, evaluation and deployment. By following a top-down +teaching approach, students are enabled to apply complex machine learning models from the beginning.","As part of the course work, students will acquire knowledge and skills in the following areas: +1. Becoming familiar with the principles and frameworks in the research area of Data Science. +2. Apply machine learning and deep learning frameworks to structured and unstructured data +3. Design, implementation and evaluation of key algorithms within an end-to-end workflow in the field of Data + +Science + +4. Application of Jupyter notebooks and their infrastructure (collection, storage, retrieval, and analysis of data) +5. Understanding of a data-driven & analytical approach to decision problems","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or +b) term paper (approx. 15 pages) +Language of assessment: German and/or English +Assessment offered: Only when announced in the semester in which the courses are offered +creditable for bonus",--,--,150 h,--,-- +International Marketing Strategy,12-M-IMS-211-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,5,numerical grade,1 semester,graduate,"The objective of this simulation course is to develop hands-on skills of how to make international marketing de- +cisions. Emphasis is put on the computer simulation game Country Manager which focuses on the managerial is- +sues arising when companies plan and execute market entry into new countries. This exercise allows students to +experience the challenges pertaining to corresponding decisions by playing the role of a responsible manager for +a major consumer products company. Students have to decide on the countries to enter, the mode of entry, the +segments to target, and every aspect of the marketing mix (price, promotion, place and product) and will get im- +mediate feedback on the consequences of their actions.","After completion of the course, participants should have gained a broad appreciation of critical decisions in in- +ternational marketing.",S (2),"a) written examination (40 to 60 minutes) or +b) term paper (15 to 20 pages) and presentation (approx. 20 minutes) (weighted 2:1) or +c) term paper (30 to 40 pages) or +d) portfolio (approx. 20 pages) +Language of assessment: German and/or English",--,--,150 h,--,-- +Economist Practice Lectures,12-M-VWP-211-m01,Faculty of Business Management and Economics,"Holder of the Senior Professorship for Economics, Money",5,numerical grade,1 semester,graduate,"The content of the seminar is the active participation in as well as the follow-up of the lectures of economists +from different national and international fields of activity, which are organized for the event. + +The invitation of speakers from practice strengthens the practical orientation of the scientifically founded and at +the same time internationally oriented education at the faculty of economics of the University of Würzburg. + +In this way, students will gain lasting insights into the fields of activity of economists, gain an insight into prac- +tical activities, discuss these with high-ranking economists and combine them with theoretical economic know- +ledge gained during their studies.","By participating in the seminar, Master's students of the faculty of economics and business administration +should get to know the different fields of activity of economists and the questions that determine the daily work +of the speakers in the course of the lectures. + +In addition, the participants of the seminar will have the opportunity to apply the knowledge of economics they +have acquired during their studies. For this purpose, in addition to a discussion with the speakers following the +respective lecture, a debating workshop is offered to the participants of the seminar, in which the students are to +learn economic argumentation and debate management. The learned contents and competencies will be tested +at the end of the semester.",S (2),"a) oral examination (one candidate each: approx. 10 to 15 minutes, groups of 2: approx. 20 minutes, groups of 3: +approx. 30 minutes) or +b) term paper (approx. 10 pages) and presentation (approx. 15 minutes); (weighted 2:1) or +c) written examination (approx. 60 minutes) +Language of assessment: German and/or English",--,--,150 h,--,-- +Enterprise AI,12-M-EAI-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) term paper (approx. 15 pages) or +c) oral examination of one candidate each (approx. 20 minutes) +Language of assessment: German and/or English +creditable for bonus",--,--,150 h,--,-- +Information Systems and Artificial Intelligence 1,12-M-KI1-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) or +c) term paper (approx. 15 to 20 pages) +Language of assessment: German and/or English +Assessment offered: In the semester in which the course is offered +creditable for bonus",--,--,150 h,--,-- +Information Systems and Artificial Intelligence 2,12-M-KI2-221-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"a) written examination (approx. 60 minutes) or +b) oral examination in groups of up to 3 candidates (approx. 10 minutes per candidate) or +c) term paper (approx. 15 to 20 pages) +Language of assessment: German and/or English +Assessment offered: In the semester in which the course is offered +creditable for bonus",--,--,150 h,--,-- +Vertical Storytelling,12-M-VS-221-m01,Faculty of Business Management and Economics,nan,10,numerical grade,1 semester,nan,--,--,S (2),"portfolio (approx. 5 pages) +Assessment offered: every year, summer semester",--,--,300 h,--,-- +Organizational Economics and Digital Transformation,12-M-OEDT-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Policy Evaluation Methods,12-M-PEM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Labor Economics,5,numerical grade,1 semester,graduate,"This course offers an introduction to the fundamentals of causal inference and to widely used research desi- +gns in the social sciences. In the first part a framework for understanding causality is introduced. Specifically, +the epistemological differences between association, intervention and counterfactuals are explained. Then it is +shown why experiments are paramount in generating causal knowledge and which assumptions are needed for +which level of the causal hierarchy. Finally, we will discuss two widely used approaches to causality in the social +sciences, i.e. potential outcomes and directed acyclic graphs. + +The second part is devoted to the research designs regressions analysis, difference-in-differences, instrumen- +tal variables, and regression discontinuity. The emphasis is how these research designs are for example applied +to answer important questions in labour economics such as the effects of a minimum wage increase on employ- +ment or the effect of children on female labour supply and wages. + +The assumptions each research design requires in order to identify a causal effect will be at center stage of the +lecture. Therefore the emphasis is to teach students what one needs to estimate in order to answer a given que- +stion. Further, the research designs are discussed such that students will be able to evaluate and apply these re- +search designs to other questions and fields.","At the end of the course, students should be able to understand basic concepts and methods of causal infe- +rence, as well as read, interpret, and assess the credibility of scientific publications. In addition, the course ser- +ves as preparation for advanced statistics and econometrics courses.","V (2) + Ü (2) +Module taught in: English","a) written examination (approx. 60 minutes) or b) term paper (approx. 15 pages) +Language of assessment: English +creditable for bonus",--,Research track module in Master's programme IEP,150 h,--,-- +Topics in Empirical Economics,12-M-TE-231-m01,Faculty of Business Management and Economics,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","portfolio (approx. 50 hours) +Prüfungssprache: Englisch +Creditable for bonus","12 *WA1(1) Should the number of applications exceed the number of available places, places will be allocated by +lot among all applicants irrespective of their subjects. +(2) Places on all courses of the module with a restricted number of places will be allocated in the same procedu- +re. +(3) A waiting list will be maintained and places re-allocated by lot as they become available.",--,150 h,--,-- +Systems Benchmarking,10-I=SB-212-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,nan,--,--,V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +creditable for bonus +Language of assessment: German and/or English",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +SE,IT,ES,HCI,GE",150 h,--,-- +Computer Vision,10-xtAI=CV-202-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,"The lecture provides knowledge about current methods and algorithms in the field of computer vision. Important +basics as well as the most recent approaches to image representation, image processing and image analysis are +taught. Actual models and methods of machine learning as well as their technical backgrounds are presented +and their respective applications in image processing are shown.","Students have fundamental knowledge of problems and techniques in the field of computer vision and are able +to independently identify and apply suitable methods for concrete problems.","V (2) + Ü (2) +Module taught in: English","Written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Image Processing and Computational Photography,10-I=IP-222-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Multilingual NLP,10-I=MNLP-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +Creditable for bonus",--,--,150 h,--,-- +Statistical Network Analysis,10-I=SNA-232-m01,Institute of Computer Science,holder of the Chair of Computer Science XV,5,numerical grade,1 semester,graduate,"Networks matter! This holds for technical infrastructures like communication or transportation networks, for in- +formation systems and social media in the World Wide Web, but also for various social, economic and biologi- +cal systems. What can we learn from data that capture the interaction topology of such complex systems? What +is the role of individual nodes and how can we discover significant patterns in the structure of networks? How do +these structures influence dynamical process like diffusion or the spreading of epidemics? Which are the most +influential actors in a social network? And how can we analyze time series data on systems with dynamic net- +work topologies? +Addressing those questions, the course combines a series of lectures -- which introduce fundamental concepts +for the statistical modelling of complex networks -- with weekly exercises that show how we can apply them to +practical network analysis tasks. Topics covered include foundations of graph theory, centrality and modulari- +ty measures, aggregate statistical characteristics of large networks, random graphs and statistical ensembles +of complex networks, generating function analysis of expected graph properties, scale-free networks, stocha- +stic dynamics in networks, spectral analysis, as well as the modelling of time-varying networks. The course ma- +terial consists of annotated slides for lectures as well as a accompanying git-Repository of jupyter notebooks, +which implement and validate the theoretical concepts covered in the lectures. Students can test and deepen +their knowledge through weekly exercise sheets. The successful completion of the course requires to pass a final +written exam.","The course will equip participants with statistical network analysis techniques that are needed for the data-dri- +ven modelling of complex technical, social, and biological systems. Students will understand how we can quan- +titatively model the topology of networked systems and how we can detect and characterize topological pat- +terns. Participants will learn how to use analytical methods to make statements about the expected properties of +very large networks that are generated based on different stochastic models. They further gain an analytical un- +derstanding of how the structure of networks shapes dynamical processes, how statistical fluctuations in degree +distributions influence the robustness of systems, and how emergent network features emerge from simple ran- +dom processes.","V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): + +IN",150 h,--,-- +Operations Research,10-I=OR-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: German and/or English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): IN",150 h,--,-- +Machine Learning for Networks 1,10-I=MLN1-232-m01,Institute of Computer Science,nan,5,numerical grade,1 semester,nan,--,--,"V (2) + Ü (2) +Module taught in: English","written examination (approx. 60 to 120 minutes) +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +AT,IT,SE,KI,HCI,IN",150 h,--,-- +Data Science,10-I=DM-232-m01,Institute of Computer Science,holder of the Chair of Computer Science IX,5,numerical grade,1 semester,graduate,"Foundations in the following areas: definition of data mining and knowledge discovery in databases, process +model, relationship to data warehouse and OLAP data preprocessing, data visualisation, unsupervised learning +methods (cluster- and association methods), supervised learning (e. g. Bayes classification, KNN, decision trees, +SVM), learning methods for special data types, further learning paradigms.","The students possess a theoretical and practical knowledge of typical methods and algorithms in the area of da- +ta mining and machine learning. They are able to solve practical knowledge discovery problems with the help of +the knowledge acquired in this course and by using the KDD process. They have acquired experience in the use +or implementation of data mining algorithms.",V (2) + Ü (2),"written examination (approx. 60 to 120 minutes). +If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral +examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap- +prox. 15 minutes per candidate). +Language of assessment: German and/or English +creditable for bonus",--,"Focuses available for students of the Master's programme Informatik (Computer Science, 120 ECTS credits): +IT,KI,HCI,GE,SEC",150 h,--,-- +Master Thesis Information Systems,12-WI-MA-192-m01,Faculty of Business Management and Economics,Dean of the Faculty of Business Management and Econo-,30,numerical grade,1 semester,graduate,"Students will complete their degree with a Master's thesis in which they will be required to independently rese- +arch and write on a topic in the area of business management and economics, drawing on the subject-specific +knowledge they have acquired and adhering to the principles of good scientific practice. This thesis may either +take the form of an analysis and structured presentation of the existing literature on a certain topic or may, as is +often the case, also include a presentation of the students' own original achievements, e. g. new algorithms de- +veloped by students, surveys, the prototypical demonstration of a concept they developed or the application and +(further) development of a theoretical model.","In the master thesis students prove that they can plan and carry out a science-based work to solve a particular +problem within a specified period autonomously and to document the results in accordance with the professio- +nal scientific standards in writing. Students are able to understand relevant contributions to research and pro- +fessional practice, critically analyze and assess the relevance to their own specific questions. They can assess +and recognize major lines of development and dynamics of the subject and therefore also the need to retrain +continuously.",--,"Master's thesis (approx. 60 to 80 pages) +Language of assessment: German and/or English",--,Time to complete: 6 months,900 h,--,-- diff --git a/09_archive_and_discarded_approaches/MS_IS_all_modules_cleaned.xlsx b/09_archive_and_discarded_approaches/MS_IS_all_modules_cleaned.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..de4185e0b5c9ff6c17206cc77a37304a221a8cfd Binary files /dev/null and b/09_archive_and_discarded_approaches/MS_IS_all_modules_cleaned.xlsx differ diff --git a/09_archive_and_discarded_approaches/playground_finetune_and_mlflow.ipynb b/09_archive_and_discarded_approaches/playground_finetune_and_mlflow.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b20d94152fce12d95e8a284a24f3b89dca914763 --- /dev/null +++ b/09_archive_and_discarded_approaches/playground_finetune_and_mlflow.ipynb @@ -0,0 +1,725 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "EPrYJOn81f0D" + }, + "source": [ + "## First Application Of Tapas Model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "data = pd.read_excel(\"DataExtraction/MS_IS_all_modules.xlsx\")\n", + "data.head()\n", + "\n", + "\n", + "from transformers import TapasForQuestionAnswering, TapasTokenizer\n", + "from transformers import pipeline\n", + "\n", + "tqa = pipeline(task='table-question-answering', model='google/tapas-base-finetuned-wtq')\n", + "\n", + "\n", + "table = pd.read_excel(\"DataExtraction/MS_IS_all_modules.xlsx\")\n", + "table = table.astype(str)\n", + "\n", + "query = [\"What's the module title of the module with abbreviation 12-IV-161-m01?\"]\n", + "query = [\"What ist the workload of Module title IT-Management?\"]\n", + "answer = tqa(table=table, query=query)\n", + "print(answer['answer'].strip())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# FT Versuch" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "'int' object is not subscriptable", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[101], line 28\u001b[0m\n\u001b[0;32m 24\u001b[0m answer_coordinates \u001b[39m=\u001b[39m [(\u001b[39m1\u001b[39m, \u001b[39m1\u001b[39m, \u001b[39m1\u001b[39m, \u001b[39m1\u001b[39m)] \u001b[39m# Example coordinates for the answer\u001b[39;00m\n\u001b[0;32m 27\u001b[0m \u001b[39m# Tokenize the training data using the TapasTokenizer\u001b[39;00m\n\u001b[1;32m---> 28\u001b[0m inputs \u001b[39m=\u001b[39m tokenizer(\n\u001b[0;32m 29\u001b[0m table\u001b[39m=\u001b[39;49mdf,\n\u001b[0;32m 30\u001b[0m queries\u001b[39m=\u001b[39;49mqueries,\n\u001b[0;32m 31\u001b[0m answer_text\u001b[39m=\u001b[39;49manswer_text,\n\u001b[0;32m 32\u001b[0m answer_coordinates\u001b[39m=\u001b[39;49manswer_coordinates,\n\u001b[0;32m 33\u001b[0m padding\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mmax_length\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[0;32m 34\u001b[0m truncation\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[0;32m 35\u001b[0m return_tensors\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mpt\u001b[39;49m\u001b[39m\"\u001b[39;49m\n\u001b[0;32m 36\u001b[0m )\n\u001b[0;32m 38\u001b[0m \u001b[39m# Define the training arguments\u001b[39;00m\n\u001b[0;32m 39\u001b[0m training_args \u001b[39m=\u001b[39m TrainingArguments(\n\u001b[0;32m 40\u001b[0m output_dir\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39m./results\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m# output directory\u001b[39;00m\n\u001b[0;32m 41\u001b[0m num_train_epochs\u001b[39m=\u001b[39m\u001b[39m3\u001b[39m, \u001b[39m# total number of training epochs\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 47\u001b[0m logging_steps\u001b[39m=\u001b[39m\u001b[39m10\u001b[39m,\n\u001b[0;32m 48\u001b[0m )\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:650\u001b[0m, in \u001b[0;36mTapasTokenizer.__call__\u001b[1;34m(self, table, queries, answer_coordinates, answer_text, add_special_tokens, padding, truncation, max_length, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)\u001b[0m\n\u001b[0;32m 647\u001b[0m is_batched \u001b[39m=\u001b[39m \u001b[39misinstance\u001b[39m(queries, (\u001b[39mlist\u001b[39m, \u001b[39mtuple\u001b[39m))\n\u001b[0;32m 649\u001b[0m \u001b[39mif\u001b[39;00m is_batched:\n\u001b[1;32m--> 650\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbatch_encode_plus(\n\u001b[0;32m 651\u001b[0m table\u001b[39m=\u001b[39;49mtable,\n\u001b[0;32m 652\u001b[0m queries\u001b[39m=\u001b[39;49mqueries,\n\u001b[0;32m 653\u001b[0m answer_coordinates\u001b[39m=\u001b[39;49manswer_coordinates,\n\u001b[0;32m 654\u001b[0m answer_text\u001b[39m=\u001b[39;49manswer_text,\n\u001b[0;32m 655\u001b[0m add_special_tokens\u001b[39m=\u001b[39;49madd_special_tokens,\n\u001b[0;32m 656\u001b[0m padding\u001b[39m=\u001b[39;49mpadding,\n\u001b[0;32m 657\u001b[0m truncation\u001b[39m=\u001b[39;49mtruncation,\n\u001b[0;32m 658\u001b[0m max_length\u001b[39m=\u001b[39;49mmax_length,\n\u001b[0;32m 659\u001b[0m pad_to_multiple_of\u001b[39m=\u001b[39;49mpad_to_multiple_of,\n\u001b[0;32m 660\u001b[0m return_tensors\u001b[39m=\u001b[39;49mreturn_tensors,\n\u001b[0;32m 661\u001b[0m return_token_type_ids\u001b[39m=\u001b[39;49mreturn_token_type_ids,\n\u001b[0;32m 662\u001b[0m return_attention_mask\u001b[39m=\u001b[39;49mreturn_attention_mask,\n\u001b[0;32m 663\u001b[0m return_overflowing_tokens\u001b[39m=\u001b[39;49mreturn_overflowing_tokens,\n\u001b[0;32m 664\u001b[0m return_special_tokens_mask\u001b[39m=\u001b[39;49mreturn_special_tokens_mask,\n\u001b[0;32m 665\u001b[0m return_offsets_mapping\u001b[39m=\u001b[39;49mreturn_offsets_mapping,\n\u001b[0;32m 666\u001b[0m return_length\u001b[39m=\u001b[39;49mreturn_length,\n\u001b[0;32m 667\u001b[0m verbose\u001b[39m=\u001b[39;49mverbose,\n\u001b[0;32m 668\u001b[0m \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs,\n\u001b[0;32m 669\u001b[0m )\n\u001b[0;32m 670\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m 671\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mencode_plus(\n\u001b[0;32m 672\u001b[0m table\u001b[39m=\u001b[39mtable,\n\u001b[0;32m 673\u001b[0m query\u001b[39m=\u001b[39mqueries,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 689\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[0;32m 690\u001b[0m )\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:768\u001b[0m, in \u001b[0;36mTapasTokenizer.batch_encode_plus\u001b[1;34m(self, table, queries, answer_coordinates, answer_text, add_special_tokens, padding, truncation, max_length, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)\u001b[0m\n\u001b[0;32m 761\u001b[0m \u001b[39mif\u001b[39;00m return_offsets_mapping:\n\u001b[0;32m 762\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mNotImplementedError\u001b[39;00m(\n\u001b[0;32m 763\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mreturn_offset_mapping is not available when using Python tokenizers. \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 764\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mTo use this feature, change your tokenizer to one deriving from \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 765\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mtransformers.PreTrainedTokenizerFast.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 766\u001b[0m )\n\u001b[1;32m--> 768\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_batch_encode_plus(\n\u001b[0;32m 769\u001b[0m table\u001b[39m=\u001b[39;49mtable,\n\u001b[0;32m 770\u001b[0m queries\u001b[39m=\u001b[39;49mqueries,\n\u001b[0;32m 771\u001b[0m answer_coordinates\u001b[39m=\u001b[39;49manswer_coordinates,\n\u001b[0;32m 772\u001b[0m answer_text\u001b[39m=\u001b[39;49manswer_text,\n\u001b[0;32m 773\u001b[0m add_special_tokens\u001b[39m=\u001b[39;49madd_special_tokens,\n\u001b[0;32m 774\u001b[0m padding\u001b[39m=\u001b[39;49mpadding,\n\u001b[0;32m 775\u001b[0m truncation\u001b[39m=\u001b[39;49mtruncation,\n\u001b[0;32m 776\u001b[0m max_length\u001b[39m=\u001b[39;49mmax_length,\n\u001b[0;32m 777\u001b[0m pad_to_multiple_of\u001b[39m=\u001b[39;49mpad_to_multiple_of,\n\u001b[0;32m 778\u001b[0m return_tensors\u001b[39m=\u001b[39;49mreturn_tensors,\n\u001b[0;32m 779\u001b[0m return_token_type_ids\u001b[39m=\u001b[39;49mreturn_token_type_ids,\n\u001b[0;32m 780\u001b[0m return_attention_mask\u001b[39m=\u001b[39;49mreturn_attention_mask,\n\u001b[0;32m 781\u001b[0m return_overflowing_tokens\u001b[39m=\u001b[39;49mreturn_overflowing_tokens,\n\u001b[0;32m 782\u001b[0m return_special_tokens_mask\u001b[39m=\u001b[39;49mreturn_special_tokens_mask,\n\u001b[0;32m 783\u001b[0m return_offsets_mapping\u001b[39m=\u001b[39;49mreturn_offsets_mapping,\n\u001b[0;32m 784\u001b[0m return_length\u001b[39m=\u001b[39;49mreturn_length,\n\u001b[0;32m 785\u001b[0m verbose\u001b[39m=\u001b[39;49mverbose,\n\u001b[0;32m 786\u001b[0m \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs,\n\u001b[0;32m 787\u001b[0m )\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:835\u001b[0m, in \u001b[0;36mTapasTokenizer._batch_encode_plus\u001b[1;34m(self, table, queries, answer_coordinates, answer_text, add_special_tokens, padding, truncation, max_length, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)\u001b[0m\n\u001b[0;32m 832\u001b[0m queries[idx] \u001b[39m=\u001b[39m query\n\u001b[0;32m 833\u001b[0m queries_tokens\u001b[39m.\u001b[39mappend(query_tokens)\n\u001b[1;32m--> 835\u001b[0m batch_outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_batch_prepare_for_model(\n\u001b[0;32m 836\u001b[0m table,\n\u001b[0;32m 837\u001b[0m queries,\n\u001b[0;32m 838\u001b[0m tokenized_table\u001b[39m=\u001b[39;49mtable_tokens,\n\u001b[0;32m 839\u001b[0m queries_tokens\u001b[39m=\u001b[39;49mqueries_tokens,\n\u001b[0;32m 840\u001b[0m answer_coordinates\u001b[39m=\u001b[39;49manswer_coordinates,\n\u001b[0;32m 841\u001b[0m padding\u001b[39m=\u001b[39;49mpadding,\n\u001b[0;32m 842\u001b[0m truncation\u001b[39m=\u001b[39;49mtruncation,\n\u001b[0;32m 843\u001b[0m answer_text\u001b[39m=\u001b[39;49manswer_text,\n\u001b[0;32m 844\u001b[0m add_special_tokens\u001b[39m=\u001b[39;49madd_special_tokens,\n\u001b[0;32m 845\u001b[0m max_length\u001b[39m=\u001b[39;49mmax_length,\n\u001b[0;32m 846\u001b[0m pad_to_multiple_of\u001b[39m=\u001b[39;49mpad_to_multiple_of,\n\u001b[0;32m 847\u001b[0m return_tensors\u001b[39m=\u001b[39;49mreturn_tensors,\n\u001b[0;32m 848\u001b[0m prepend_batch_axis\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[0;32m 849\u001b[0m return_attention_mask\u001b[39m=\u001b[39;49mreturn_attention_mask,\n\u001b[0;32m 850\u001b[0m return_token_type_ids\u001b[39m=\u001b[39;49mreturn_token_type_ids,\n\u001b[0;32m 851\u001b[0m return_overflowing_tokens\u001b[39m=\u001b[39;49mreturn_overflowing_tokens,\n\u001b[0;32m 852\u001b[0m return_special_tokens_mask\u001b[39m=\u001b[39;49mreturn_special_tokens_mask,\n\u001b[0;32m 853\u001b[0m return_length\u001b[39m=\u001b[39;49mreturn_length,\n\u001b[0;32m 854\u001b[0m verbose\u001b[39m=\u001b[39;49mverbose,\n\u001b[0;32m 855\u001b[0m )\n\u001b[0;32m 857\u001b[0m \u001b[39mreturn\u001b[39;00m BatchEncoding(batch_outputs)\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:890\u001b[0m, in \u001b[0;36mTapasTokenizer._batch_prepare_for_model\u001b[1;34m(self, raw_table, raw_queries, tokenized_table, queries_tokens, answer_coordinates, answer_text, add_special_tokens, padding, truncation, max_length, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, prepend_batch_axis, **kwargs)\u001b[0m\n\u001b[0;32m 888\u001b[0m \u001b[39mfor\u001b[39;00m index, example \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(\u001b[39mzip\u001b[39m(raw_queries, queries_tokens, answer_coordinates, answer_text)):\n\u001b[0;32m 889\u001b[0m raw_query, query_tokens, answer_coords, answer_txt \u001b[39m=\u001b[39m example\n\u001b[1;32m--> 890\u001b[0m outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mprepare_for_model(\n\u001b[0;32m 891\u001b[0m raw_table,\n\u001b[0;32m 892\u001b[0m raw_query,\n\u001b[0;32m 893\u001b[0m tokenized_table\u001b[39m=\u001b[39;49mtokenized_table,\n\u001b[0;32m 894\u001b[0m query_tokens\u001b[39m=\u001b[39;49mquery_tokens,\n\u001b[0;32m 895\u001b[0m answer_coordinates\u001b[39m=\u001b[39;49manswer_coords,\n\u001b[0;32m 896\u001b[0m answer_text\u001b[39m=\u001b[39;49manswer_txt,\n\u001b[0;32m 897\u001b[0m add_special_tokens\u001b[39m=\u001b[39;49madd_special_tokens,\n\u001b[0;32m 898\u001b[0m padding\u001b[39m=\u001b[39;49mPaddingStrategy\u001b[39m.\u001b[39;49mDO_NOT_PAD\u001b[39m.\u001b[39;49mvalue, \u001b[39m# we pad in batch afterwards\u001b[39;49;00m\n\u001b[0;32m 899\u001b[0m truncation\u001b[39m=\u001b[39;49mtruncation,\n\u001b[0;32m 900\u001b[0m max_length\u001b[39m=\u001b[39;49mmax_length,\n\u001b[0;32m 901\u001b[0m pad_to_multiple_of\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m, \u001b[39m# we pad in batch afterwards\u001b[39;49;00m\n\u001b[0;32m 902\u001b[0m return_attention_mask\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m, \u001b[39m# we pad in batch afterwards\u001b[39;49;00m\n\u001b[0;32m 903\u001b[0m return_token_type_ids\u001b[39m=\u001b[39;49mreturn_token_type_ids,\n\u001b[0;32m 904\u001b[0m return_special_tokens_mask\u001b[39m=\u001b[39;49mreturn_special_tokens_mask,\n\u001b[0;32m 905\u001b[0m return_length\u001b[39m=\u001b[39;49mreturn_length,\n\u001b[0;32m 906\u001b[0m return_tensors\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m, \u001b[39m# We convert the whole batch to tensors at the end\u001b[39;49;00m\n\u001b[0;32m 907\u001b[0m prepend_batch_axis\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[0;32m 908\u001b[0m verbose\u001b[39m=\u001b[39;49mverbose,\n\u001b[0;32m 909\u001b[0m prev_answer_coordinates\u001b[39m=\u001b[39;49manswer_coordinates[index \u001b[39m-\u001b[39;49m \u001b[39m1\u001b[39;49m] \u001b[39mif\u001b[39;49;00m index \u001b[39m!=\u001b[39;49m \u001b[39m0\u001b[39;49m \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m,\n\u001b[0;32m 910\u001b[0m prev_answer_text\u001b[39m=\u001b[39;49manswer_text[index \u001b[39m-\u001b[39;49m \u001b[39m1\u001b[39;49m] \u001b[39mif\u001b[39;49;00m index \u001b[39m!=\u001b[39;49m \u001b[39m0\u001b[39;49m \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m,\n\u001b[0;32m 911\u001b[0m )\n\u001b[0;32m 913\u001b[0m \u001b[39mfor\u001b[39;00m key, value \u001b[39min\u001b[39;00m outputs\u001b[39m.\u001b[39mitems():\n\u001b[0;32m 914\u001b[0m \u001b[39mif\u001b[39;00m key \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m batch_outputs:\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1248\u001b[0m, in \u001b[0;36mTapasTokenizer.prepare_for_model\u001b[1;34m(self, raw_table, raw_query, tokenized_table, query_tokens, answer_coordinates, answer_text, add_special_tokens, padding, truncation, max_length, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, prepend_batch_axis, **kwargs)\u001b[0m\n\u001b[0;32m 1245\u001b[0m encoded_inputs[\u001b[39m\"\u001b[39m\u001b[39mattention_mask\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m attention_mask\n\u001b[0;32m 1247\u001b[0m \u001b[39mif\u001b[39;00m answer_coordinates \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39mand\u001b[39;00m answer_text \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1248\u001b[0m labels \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mget_answer_ids(column_ids, row_ids, table_data, answer_text, answer_coordinates)\n\u001b[0;32m 1249\u001b[0m numeric_values \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_numeric_values(raw_table, column_ids, row_ids)\n\u001b[0;32m 1250\u001b[0m numeric_values_scale \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_numeric_values_scale(raw_table, column_ids, row_ids)\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1825\u001b[0m, in \u001b[0;36mTapasTokenizer.get_answer_ids\u001b[1;34m(self, column_ids, row_ids, tokenized_table, answer_texts_question, answer_coordinates_question)\u001b[0m\n\u001b[0;32m 1818\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mupdate_answer_coordinates:\n\u001b[0;32m 1819\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_find_answer_ids_from_answer_texts(\n\u001b[0;32m 1820\u001b[0m column_ids,\n\u001b[0;32m 1821\u001b[0m row_ids,\n\u001b[0;32m 1822\u001b[0m tokenized_table,\n\u001b[0;32m 1823\u001b[0m answer_texts\u001b[39m=\u001b[39m[\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtokenize(at) \u001b[39mfor\u001b[39;00m at \u001b[39min\u001b[39;00m answer_texts_question],\n\u001b[0;32m 1824\u001b[0m )\n\u001b[1;32m-> 1825\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_get_answer_ids(column_ids, row_ids, answer_coordinates_question)\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1811\u001b[0m, in \u001b[0;36mTapasTokenizer._get_answer_ids\u001b[1;34m(self, column_ids, row_ids, answer_coordinates)\u001b[0m\n\u001b[0;32m 1809\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_get_answer_ids\u001b[39m(\u001b[39mself\u001b[39m, column_ids, row_ids, answer_coordinates):\n\u001b[0;32m 1810\u001b[0m \u001b[39m \u001b[39m\u001b[39m\"\"\"Maps answer coordinates of a question to token indexes.\"\"\"\u001b[39;00m\n\u001b[1;32m-> 1811\u001b[0m answer_ids, missing_count \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_get_all_answer_ids(column_ids, row_ids, answer_coordinates)\n\u001b[0;32m 1813\u001b[0m \u001b[39mif\u001b[39;00m missing_count:\n\u001b[0;32m 1814\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mCouldn\u001b[39m\u001b[39m'\u001b[39m\u001b[39mt find all answers\u001b[39m\u001b[39m\"\u001b[39m)\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1737\u001b[0m, in \u001b[0;36mTapasTokenizer._get_all_answer_ids\u001b[1;34m(self, column_ids, row_ids, answer_coordinates)\u001b[0m\n\u001b[0;32m 1733\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_to_coordinates\u001b[39m(answer_coordinates_question):\n\u001b[0;32m 1734\u001b[0m \u001b[39mreturn\u001b[39;00m [(coords[\u001b[39m1\u001b[39m], coords[\u001b[39m0\u001b[39m]) \u001b[39mfor\u001b[39;00m coords \u001b[39min\u001b[39;00m answer_coordinates_question]\n\u001b[0;32m 1736\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_all_answer_ids_from_coordinates(\n\u001b[1;32m-> 1737\u001b[0m column_ids, row_ids, answers_list\u001b[39m=\u001b[39m(_to_coordinates(answer_coordinates))\n\u001b[0;32m 1738\u001b[0m )\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1734\u001b[0m, in \u001b[0;36mTapasTokenizer._get_all_answer_ids.._to_coordinates\u001b[1;34m(answer_coordinates_question)\u001b[0m\n\u001b[0;32m 1733\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_to_coordinates\u001b[39m(answer_coordinates_question):\n\u001b[1;32m-> 1734\u001b[0m \u001b[39mreturn\u001b[39;00m [(coords[\u001b[39m1\u001b[39m], coords[\u001b[39m0\u001b[39m]) \u001b[39mfor\u001b[39;00m coords \u001b[39min\u001b[39;00m answer_coordinates_question]\n", + "File \u001b[1;32mc:\\Users\\michi\\Anaconda3\\envs\\enterpriseai2\\lib\\site-packages\\transformers\\models\\tapas\\tokenization_tapas.py:1734\u001b[0m, in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 1733\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_to_coordinates\u001b[39m(answer_coordinates_question):\n\u001b[1;32m-> 1734\u001b[0m \u001b[39mreturn\u001b[39;00m [(coords[\u001b[39m1\u001b[39;49m], coords[\u001b[39m0\u001b[39m]) \u001b[39mfor\u001b[39;00m coords \u001b[39min\u001b[39;00m answer_coordinates_question]\n", + "\u001b[1;31mTypeError\u001b[0m: 'int' object is not subscriptable" + ] + } + ], + "source": [ + "import pandas as pd\n", + "from transformers import TapasForQuestionAnswering, TapasTokenizer\n", + "from torch.utils.data import DataLoader, TensorDataset\n", + "from transformers import AdamW, get_linear_schedule_with_warmup\n", + "from transformers import TrainingArguments, Trainer\n", + "import torch\n", + "\n", + "# Load the pre-trained model and tokenizer\n", + "model = TapasForQuestionAnswering.from_pretrained('google/tapas-base-finetuned-wtq')\n", + "tokenizer = TapasTokenizer.from_pretrained('google/tapas-base-finetuned-wtq')\n", + "\n", + "# Prepare your own training data in the format expected by the model\n", + "table = [\n", + " ['Name', 'Age', 'Gender'],\n", + " ['John', '25', 'Male'],\n", + " ['Jane', '30', 'Female']\n", + "]\n", + "\n", + "\n", + "df = pd.DataFrame(table[1:], columns=table[0])\n", + "\n", + "queries = [\"What's the Age of John?\"]\n", + "answer_text = [\"25\"]\n", + "answer_coordinates = [(1, 1, 1, 1)] \n", + "\n", + "\n", + "# Tokenize the training data using the TapasTokenizer\n", + "inputs = tokenizer(\n", + " table=df,\n", + " queries=queries,\n", + " answer_text=answer_text,\n", + " answer_coordinates=answer_coordinates,\n", + " padding=\"max_length\",\n", + " truncation=True,\n", + " return_tensors=\"pt\"\n", + ")\n", + "\n", + "# Define the training arguments\n", + "training_args = TrainingArguments(\n", + " output_dir='./results', \n", + " num_train_epochs=3, \n", + " per_device_train_batch_size=16, \n", + " per_device_eval_batch_size=64, \n", + " warmup_steps=500, \n", + " weight_decay=0.01, \n", + " logging_dir='./logs', \n", + " logging_steps=10,\n", + ")\n", + "\n", + "# Define the trainer\n", + "trainer = Trainer(\n", + " model=model, \n", + " args=training_args, \n", + " train_dataset=inputs, \n", + " data_collator=lambda data: {'input_ids': torch.stack([x['input_ids'] for x in data]),\n", + " 'attention_mask': torch.stack([x['attention_mask'] for x in data]),\n", + " 'token_type_ids': torch.stack([x['token_type_ids'] for x in data]),\n", + " 'labels': torch.stack([x['labels'] for x in data])},\n", + " tokenizer=tokenizer, # tokenizer to be used for tokenization\n", + ")\n", + "\n", + "trainer.train()\n", + "\n", + "trainer.save_model('./fine-tuned-model')\n", + "tokenizer.save_pretrained('./fine-tuned-tokenizer')\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import mlflow\n", + "\n", + "# Start an MLflow run\n", + "mlflow.start_run()\n", + "\n", + "# Log your hyperparameters\n", + "mlflow.log_params({\n", + " \"learning_rate\": 1e-5,\n", + " \"batch_size\": 32,\n", + " \"num_epochs\": 1\n", + "})\n", + "\n", + "# Step 4: Model Training\n", + "# ...\n", + "\n", + "# Set up your training loop\n", + "for epoch in range(num_epochs):\n", + " model.train()\n", + " # ...\n", + "\n", + " for batch in DataLoader(dataset, batch_size=batch_size, shuffle=True):\n", + " # ...\n", + "\n", + " # Compute the loss\n", + " loss = outputs.loss\n", + "\n", + " # Log the loss metric\n", + " mlflow.log_metric(\"loss\", loss.item(), step=epoch)\n", + "\n", + " # ...\n", + "\n", + "# Step 5: Fine-tuning Parameters\n", + "# ...\n", + "\n", + "# Log your trained model as an artifact\n", + "mlflow.pytorch.log_model(model, \"tapas_model\")\n", + "\n", + "# End the MLflow run\n", + "mlflow.end_run()\n" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "name": "Fine-tuning TapasForQuestionAnswering on SQA.ipynb", + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": 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a/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_0.xlsx b/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_0.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..f2d5fcc7bb53ef3eb248080446698dd941071e20 Binary files /dev/null and b/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_0.xlsx differ diff --git a/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_1.xlsx b/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_1.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..9feb0ee02748e351c64b8dc05e53c941788a0d53 Binary files /dev/null and b/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_1.xlsx differ diff --git a/09_archive_and_discarded_approaches/table_QA_tryout_Felix/MS_IS_all_modules_orginal_15_2.xlsx 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https://pytorch-geometric.com/whl/torch-1.8.0+cpu.html\n", + "# pip install sentence-transformers\n", + "\n", + "from datasets import load_dataset\n", + "import pandas as pd\n", + "\n", + "table0 = pd.read_excel(\"MS_IS_all_modules_orginal_15_0.xlsx\")\n", + "table0 = table0.astype(str)\n", + "table1 = pd.read_excel(\"MS_IS_all_modules_orginal_15_1.xlsx\")\n", + "table1 = table1.astype(str)\n", + "table2 = pd.read_excel(\"MS_IS_all_modules_orginal_15_2.xlsx\") \n", + "table2 = table2.astype(str)\n", + "\n", + "# store all tables in the tables list\n", + "tables = []\n", + "tables.append(table0)\n", + "tables.append(table1)\n", + "tables.append(table2)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Module titleAbbreviationModule coordinatorModule offered byETCSMethod of gradingDurationModule levelContentsIntended learning outcomesCoursesMethod of assessmentAllocation of placesAdditional informationWorkloadTeaching cycleReferred to in LPO I
0Digital Entrepreneurship12-M-UGF3-182-m01Faculty of Business Management and EconomicsHolder of the Chair of Entrepreneurship and St...5numerical grade1 semestergraduateThis module provides an introduction into digi...Educational aims: Clarify the role of digital ...V (2) + Ü (2)Module taught in: Englisha) written examination (approx. 60 to 120 minu...----150 h----
1Advanced Seminar: Entrepreneurship and Management12-M-SAS-182-m01Faculty of Business Management and EconomicsHolder of the Chair of Entrepreneurship and St...10numerical grade1 semestergraduateStudents develop seminar papers on varying top...Educational aims• Enable students to position ...S (2)term paper (approx. 20 pages) and presentation...20 places. (1) Should the number of applicatio...--300 h----
2Global Logistics & Supply Chain Management12-M-GLSC-182-m01Faculty of Business Management and EconomicsHolder of the Chair of Logistics and Quantitat...5numerical grade1 semestergraduateThe course \"Global Logistics & Supply Chain Ma...After completing this course students can(i) a...V (2) + Ü (2)Module taught in: Englisha) written examination (approx. 60 minutes) or...----150 h----
3Advanced Operations & Logistics Management12-M-AOLM-182-m01Faculty of Business Management and EconomicsHolder of the Chair of Logistics and Quantitat...5numerical grade1 semestergraduateThe course \"Advanced Operations & Logistics Ma...After completing this course students can(i) a...V (2) + Ü (2)Module taught in: Englisha) written examination (approx. 60 minutes) or...----150 h----
4Seminar: Operations Management12-M-SN-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...10numerical grade1 semestergraduateWith the help of topics from the area of \"Oper...Students will learn how to convince a critical...S (2)term paper (approx. 20 to 25 pages) and presen...----300 h----
5Adaption and Continuous System Engineering12-ACSE-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduateBusiness Suite: The constantly changing enviro...Business Suite: Students learn about the vario...V (2) + Ü (2)a) written examination (approx. 60 minutes) or...20 places. (1) Should the number of applicatio...--150 h----
6Business Service Platforms 212-AGP2-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateThe next generation of business service platfo...Be aware of the growing economic importance of...V (2)Written examination (approx. 60 minutes)Credit...40 places.Should the number of applications ex...--150 h----_x000C_
7Business Service Platforms 112-BSA-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateA next generation of enterprise systems called...Be aware of the big business productivity prog...V (2)Written examination (approx. 60 minutes)Credit...40 places.Should the number of applications ex...--150 h----
8Business Processes Organisation, Business Soft...12-GLP-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduateERP systems have become key elements of succes...After completing this module, students should ...V (2) + Ü (2)written examination (approx. 60 minutes)Langua...20 places. (1) Should the number of applicatio...--150 h----
9Work and Information12-ITA-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduateThis module discusses relevant principles, con...The expertise gained from other modules relate...V (2)a) written examination (approx. 60 minutes) or...----150 h----
10Work Order Planning for Automated Manufacturing12-M-AGAF-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateThe idea of integration of business informatio...Linking research and lectures of the Institute...V (2) + Ü (2)written examination (approx. 60 minutes)Langua...----150 h----
11Topics in Business Information Systems 112-M-ATW1-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateThis course is a dummy module, e. g. for cours...The competences depend on the individual modul...V (2) + Ü (2)Course type: alternatively S inst...a) written examination (approx. 60 minutes) or...----150 h----
12Topics in Business Information Systems 212-M-ATW2-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateThis course is a dummy module, e. g. for cours...The competences depend on the individual modul...V (2) + Ü (2)Course type: alternatively S inst...a) written examination (approx. 60 minutes) or...----150 h----
13Information systems research12-M-ISR-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...5numerical grade1 semestergraduateThe course provides an overview of theoretical...The module provides students with knowledge of...V (2) + Ü (2)a) Written examination (approx. 60 minutes) or...40 places.Should the number of applications ex...--150 h----
14Databases 210-I=DB2-161-m01Institute of Computer ScienceDean of Studies Informatik (Computer Science)5numerical grade1 semestergraduateData warehouses and data mining; web databases...The students have advanced knowledge about rel...V (2) + Ü (2)written examination (approx. 60 to 120 minutes...--Focuses available for students of the Masters ...150 h----
\n", + "
" + ], + "text/plain": [ + " Module title Abbreviation \\\n", + "0 Digital Entrepreneurship 12-M-UGF3-182-m01 \n", + "1 Advanced Seminar: Entrepreneurship and Management 12-M-SAS-182-m01 \n", + "2 Global Logistics & Supply Chain Management 12-M-GLSC-182-m01 \n", + "3 Advanced Operations & Logistics Management 12-M-AOLM-182-m01 \n", + "4 Seminar: Operations Management 12-M-SN-161-m01 \n", + "5 Adaption and Continuous System Engineering 12-ACSE-161-m01 \n", + "6 Business Service Platforms 2 12-AGP2-192-m01 \n", + "7 Business Service Platforms 1 12-BSA-192-m01 \n", + "8 Business Processes Organisation, Business Soft... 12-GLP-161-m01 \n", + "9 Work and Information 12-ITA-161-m01 \n", + "10 Work Order Planning for Automated Manufacturing 12-M-AGAF-161-m01 \n", + "11 Topics in Business Information Systems 1 12-M-ATW1-161-m01 \n", + "12 Topics in Business Information Systems 2 12-M-ATW2-161-m01 \n", + "13 Information systems research 12-M-ISR-192-m01 \n", + "14 Databases 2 10-I=DB2-161-m01 \n", + "\n", + " Module coordinator \\\n", + "0 Faculty of Business Management and Economics \n", + "1 Faculty of Business Management and Economics \n", + "2 Faculty of Business Management and Economics \n", + "3 Faculty of Business Management and Economics \n", + "4 Faculty of Business Management and Economics \n", + "5 Faculty of Business Management and Economics \n", + "6 Faculty of Business Management and Economics \n", + "7 Faculty of Business Management and Economics \n", + "8 Faculty of Business Management and Economics \n", + "9 Faculty of Business Management and Economics \n", + "10 Faculty of Business Management and Economics \n", + "11 Faculty of Business Management and Economics \n", + "12 Faculty of Business Management and Economics \n", + "13 Faculty of Business Management and Economics \n", + "14 Institute of Computer Science \n", + "\n", + " Module offered by ETCS Method of grading \\\n", + "0 Holder of the Chair of Entrepreneurship and St... 5 numerical grade \n", + "1 Holder of the Chair of Entrepreneurship and St... 10 numerical grade \n", + "2 Holder of the Chair of Logistics and Quantitat... 5 numerical grade \n", + "3 Holder of the Chair of Logistics and Quantitat... 5 numerical grade \n", + "4 Holder of the Chair of Business Management and... 10 numerical grade \n", + "5 holder of the Chair of Business Management and... 5 numerical grade \n", + "6 Holder of the Chair of Business Management and... 5 numerical grade \n", + "7 Holder of the Chair of Business Management and... 5 numerical grade \n", + "8 holder of the Chair of Business Management and... 5 numerical grade \n", + "9 holder of the Chair of Business Management and... 5 numerical grade \n", + "10 Holder of the Chair of Business Management and... 5 numerical grade \n", + "11 Holder of the Chair of Business Management and... 5 numerical grade \n", + "12 Holder of the Chair of Business Management and... 5 numerical grade \n", + "13 Holder of the Chair of Business Management and... 5 numerical grade \n", + "14 Dean of Studies Informatik (Computer Science) 5 numerical grade \n", + "\n", + " Duration Module level \\\n", + "0 1 semester graduate \n", + "1 1 semester graduate \n", + "2 1 semester graduate \n", + "3 1 semester graduate \n", + "4 1 semester graduate \n", + "5 1 semester graduate \n", + "6 1 semester graduate \n", + "7 1 semester graduate \n", + "8 1 semester graduate \n", + "9 1 semester graduate \n", + "10 1 semester graduate \n", + "11 1 semester graduate \n", + "12 1 semester graduate \n", + "13 1 semester graduate \n", + "14 1 semester graduate \n", + "\n", + " Contents \\\n", + "0 This module provides an introduction into digi... \n", + "1 Students develop seminar papers on varying top... \n", + "2 The course \"Global Logistics & Supply Chain Ma... \n", + "3 The course \"Advanced Operations & Logistics Ma... \n", + "4 With the help of topics from the area of \"Oper... \n", + "5 Business Suite: The constantly changing enviro... \n", + "6 The next generation of business service platfo... \n", + "7 A next generation of enterprise systems called... \n", + "8 ERP systems have become key elements of succes... \n", + "9 This module discusses relevant principles, con... \n", + "10 The idea of integration of business informatio... \n", + "11 This course is a dummy module, e. g. for cours... \n", + "12 This course is a dummy module, e. g. for cours... \n", + "13 The course provides an overview of theoretical... \n", + "14 Data warehouses and data mining; web databases... \n", + "\n", + " Intended learning outcomes \\\n", + "0 Educational aims: Clarify the role of digital ... \n", + "1 Educational aims• Enable students to position ... \n", + "2 After completing this course students can(i) a... \n", + "3 After completing this course students can(i) a... \n", + "4 Students will learn how to convince a critical... \n", + "5 Business Suite: Students learn about the vario... \n", + "6 Be aware of the growing economic importance of... \n", + "7 Be aware of the big business productivity prog... \n", + "8 After completing this module, students should ... \n", + "9 The expertise gained from other modules relate... \n", + "10 Linking research and lectures of the Institute... \n", + "11 The competences depend on the individual modul... \n", + "12 The competences depend on the individual modul... \n", + "13 The module provides students with knowledge of... \n", + "14 The students have advanced knowledge about rel... \n", + "\n", + " Courses \\\n", + "0 V (2) + Ü (2)Module taught in: English \n", + "1 S (2) \n", + "2 V (2) + Ü (2)Module taught in: English \n", + "3 V (2) + Ü (2)Module taught in: English \n", + "4 S (2) \n", + "5 V (2) + Ü (2) \n", + "6 V (2) \n", + "7 V (2) \n", + "8 V (2) + Ü (2) \n", + "9 V (2) \n", + "10 V (2) + Ü (2) \n", + "11 V (2) + Ü (2)Course type: alternatively S inst... \n", + "12 V (2) + Ü (2)Course type: alternatively S inst... \n", + "13 V (2) + Ü (2) \n", + "14 V (2) + Ü (2) \n", + "\n", + " Method of assessment \\\n", + "0 a) written examination (approx. 60 to 120 minu... \n", + "1 term paper (approx. 20 pages) and presentation... \n", + "2 a) written examination (approx. 60 minutes) or... \n", + "3 a) written examination (approx. 60 minutes) or... \n", + "4 term paper (approx. 20 to 25 pages) and presen... \n", + "5 a) written examination (approx. 60 minutes) or... \n", + "6 Written examination (approx. 60 minutes)Credit... \n", + "7 Written examination (approx. 60 minutes)Credit... \n", + "8 written examination (approx. 60 minutes)Langua... \n", + "9 a) written examination (approx. 60 minutes) or... \n", + "10 written examination (approx. 60 minutes)Langua... \n", + "11 a) written examination (approx. 60 minutes) or... \n", + "12 a) written examination (approx. 60 minutes) or... \n", + "13 a) Written examination (approx. 60 minutes) or... \n", + "14 written examination (approx. 60 to 120 minutes... \n", + "\n", + " Allocation of places \\\n", + "0 -- \n", + "1 20 places. (1) Should the number of applicatio... \n", + "2 -- \n", + "3 -- \n", + "4 -- \n", + "5 20 places. (1) Should the number of applicatio... \n", + "6 40 places.Should the number of applications ex... \n", + "7 40 places.Should the number of applications ex... \n", + "8 20 places. (1) Should the number of applicatio... \n", + "9 -- \n", + "10 -- \n", + "11 -- \n", + "12 -- \n", + "13 40 places.Should the number of applications ex... \n", + "14 -- \n", + "\n", + " Additional information Workload Teaching cycle \\\n", + "0 -- 150 h -- \n", + "1 -- 300 h -- \n", + "2 -- 150 h -- \n", + "3 -- 150 h -- \n", + "4 -- 300 h -- \n", + "5 -- 150 h -- \n", + "6 -- 150 h -- \n", + "7 -- 150 h -- \n", + "8 -- 150 h -- \n", + "9 -- 150 h -- \n", + "10 -- 150 h -- \n", + "11 -- 150 h -- \n", + "12 -- 150 h -- \n", + "13 -- 150 h -- \n", + "14 Focuses available for students of the Masters ... 150 h -- \n", + "\n", + " Referred to in LPO I \n", + "0 -- \n", + "1 -- \n", + "2 -- \n", + "3 -- \n", + "4 -- \n", + "5 -- \n", + "6 --_x000C_ \n", + "7 -- \n", + "8 -- \n", + "9 -- \n", + "10 -- \n", + "11 -- \n", + "12 -- \n", + "13 -- \n", + "14 -- " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tables[2]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SentenceTransformer(\n", + " (0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel \n", + " (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})\n", + " (2): Normalize()\n", + ")" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import torch\n", + "from sentence_transformers import SentenceTransformer\n", + "\n", + "# set device to GPU if available\n", + "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n", + "# load the table embedding model from huggingface models hub\n", + "retriever = SentenceTransformer(\"deepset/all-mpnet-base-v2-table\", device=device)\n", + "retriever\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def _preprocess_tables(tables: list):\n", + " processed = []\n", + " # loop through all tables\n", + " for table in tables:\n", + " # convert the table to csv and \n", + " processed_table = \"\\n\".join([table.to_csv(index=False)])\n", + " # add the processed table to processed list\n", + " processed.append(processed_table)\n", + " return processed\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### The formatted table may not make sense to us, but the embedding model is trained to understand it and generate accurate embeddings." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Module title,Abbreviation,Module coordinator,Module offered by,ETCS,Method of grading,Duration,Module level,Contents,Intended learning outcomes,Courses,Method of assessment,Allocation of places,Additional information,Workload,Teaching cycle,Referred to in LPO I\\r\\nDigital Entrepreneurship,12-M-UGF3-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,5,numerical grade,1 semester,graduate,This module provides an introduction into digital entrepreneurship and digital transformation. (1) Introduction (2) Digital business models (3) Identifying and exploiting opportunities for digital entrepreneurship (4) Strategies for creating competitive advantage in digital entrepreneurship (5) Digital marketing for entrepreneurs (6) Crowd-funding for entrepreneurs (7) Design thinking (8) Lean startup (9) Platform ecosystems and online communities (10) Digital strategy and digital transformation (11) The agile organization (12) Crowdsourcing (13) Cyberfraud (14) Wrap-up and Q&A,\"Educational aims: Clarify the role of digital entrepreneurship and digital transformation. Explain theoretical con-cepts and mechanisms behind digital entrepreneurship and digital transformation. Enable students to critically appraise alternative approaches to digital entrepreneurship and digital transformation. Enable students to eva-luate the boundaries and risks of digital entrepreneurship and digital transformationLearning outcomes: On successful completion of this module students will be able to (1) Assess the role of di-gital entrepreneurship and digital transformation for creating and sustaining competitive advantage, (2) Crea-te and evaluate concepts related to digital entrepreneurship and digital transformation, (3) Make judgements about the organizational and managerial implications of digital entrepreneurship and digital transformation, (4) Systematically choose between different routes of action.\",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 to 120 minutes) or b) log (15 to 20 pages) or c) oral examination (one candida-te each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: English,--,--,150 h,--,--\\r\\nAdvanced Seminar: Entrepreneurship and Management,12-M-SAS-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Entrepreneurship and Strategy,10,numerical grade,1 semester,graduate,\"Students develop seminar papers on varying topics in the domain of entrepreneurship, strategy, and innovation and present the key insights from their work.\",Educational aims• Enable students to position their research• Enable students to critically review a substantial body of literature in short time• Enable students to develop a sound theoretical framework• Enable students to create a research paper fully meeting academic standardsLearning outcomesOn successful completion of this module students will be able to:• Differentiate their research from previous work• Adopt theoretical perspectives to understand complex phenomena• Engage in comprehensive academic reasoning• Articulate abstract and complex phenomena and relationships in written and oral form,S (2),\"term paper (approx. 20 pages) and presentation (15 to 30 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English\",\"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.\",--,300 h,--,--\\r\\nGlobal Logistics & Supply Chain Management,12-M-GLSC-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,\"The course \"\"Global Logistics & Supply Chain Management\"\" acquaints students with advanced methods for the planning of global production networks and demonstrates the application of these with the help of multiple case studies.\",After completing this course students can(i) analyze and evaluate global production networks;(ii) develop and apply appropriate methods to plan production networks;(iii) evaluate the consequences of uncertainties in processes and apply concepts and methods to plan uncertain processes.,V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,--\\r\\nAdvanced Operations & Logistics Management,12-M-AOLM-182-m01,Faculty of Business Management and Economics,Holder of the Chair of Logistics and Quantitative Methods,5,numerical grade,1 semester,graduate,\"The course \"\"Advanced Operations & Logistics Management\"\" acquaints students with advanced methods for the planning of integrated production and logistics systems and demonstrates the application of these with the help of multiple case studies\",\"After completing this course students can(i) analyze and evaluate integrated production and logistics systems;(ii) develop and apply appropriate methods to plan complex production and logistics systems;(iii) evaluate the consequences of uncertainties in processes, and(iv) apply concepts and methods to plan uncertainties processes.\",V (2) + Ü (2)Module taught in: English,a) written examination (approx. 60 minutes) or b) term paper (approx. 15 to 20 pages)Language of assessment: Englishcreditable for bonus,--,--,150 h,--,--\\r\\nSeminar: Operations Management,12-M-SN-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,10,numerical grade,1 semester,graduate,\"With the help of topics from the area of \"\"Operations Management\"\", this course will provide students with know-ledge and skills that will enable them to prepare a well-structured term paper and to present the key results of their work.\",Students will learn how to convince a critical audience by giving a presenation regarding a topic from the area of Operations Management. By developing and giving a presentation as well as by answering questions the stu-dents will practice their skills to deal with difficult communication situations and to argument for and against a certain topic.,S (2),\"term paper (approx. 20 to 25 pages) and presentation (approx. 20 minutes), weighted 2:1Assessment offered: Once a year, winter semesterLanguage of assessment: German and/or English\",--,--,300 h,--,--\\r\\nAdaption and Continuous System Engineering,12-ACSE-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"Business Suite: The constantly changing environment with its organisational and IT-oriented developments forces companies to adapt their standard business software solutions. With the help of dynamic adaptation (Continuous System Engineering), this process of change can be supported effectively and efficiently. This mo-dule discusses both the systematic implementation of adaptation steps (so-called customising) using the exam-ple of the mySAP Business Suite and the concept of Continuous System Engineering using various practical ex-amples. Business Apps: The course combines theory and practice in the area of cloud computing and ERP. Par-ticipants gain an insight into the architecture of the ByDesign platform and are presented with an opportunity to gain practical experience working with the corresponding software development kit.Content:• Fundamentals of cloud computing• Cloud business solutions• Architecture of the SAP Business ByDesign platform• Platform adaption and extensibility• Basics of software development in SAP Cloud Applications Studio• Hands-on SDK: independently designing and developing a demo app\",\"Business Suite: Students learn about the various ways of adapting a standard business software solution to the special requirements of a company. They also develop a fundamental understanding of the dynamic adaptation of business software libraries. Based on selected examples from the SAP Business Suite that the acquired know-ledge will be deepened by using case studies. Business Apps: The course imparts knowledge and delivers skills in cloud computing for businesses, ERP systems architecture and software development at the example of the SAP Business ByDesign platform. The independent planning, implementation and documentation of a business app trains important core competencies of technology-oriented Business Informatics.\",V (2) + Ü (2),a) written examination (approx. 60 minutes) or b) term paper (approx. 20 pages) or c) oral examination (one can-didate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus,\"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.\",--,150 h,--,--\\r\\nBusiness Service Platforms 2,12-AGP2-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"The next generation of business service platforms leads to a transformation of traditional industrial enterprises into service businesses that generate a large proportion of value in developed economies. New ICT technologies such as cloud computing, the Internet of Things and semantic technologies will contribute to the success of the-se businesses in a similar way as ERP contributed to the success of industrial enterprises. But we are still at the beginning of the evolution of business service platforms, which will have to become more adaptable to support special business models and allow differentiating customer service processes.The course will discuss different case studies on services businesses. The digital transformation of the software industry into a service industry is the most prominent of these case.\",\"Be aware of the growing economic importance of the service sector. Understand that services businesses in are facing a special productivity problem, which could not be adressed by the same processes applied in the ma-nufacturing industries. Understand the new ICT technologies we have at hand today to deliver smart solutions for this problem. Be aware of the diversity of services business today where we have no evidence that a general standard can be found applicable to most subsectors similar to the standardization achieved for the manufactu-ring industries after twenty years of research.\",V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,\"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.\",--,150 h,--,--_x000C_\\r\\nBusiness Service Platforms 1,12-BSA-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"A next generation of enterprise systems called business service platforms is emerging using new disruptive tech-nologies such as cloud computing, big data and mobility. These business service platforms apply the concept of product platforms to software. They will1. be services based2. be offered as a service in the cloud3. address new classes of users and types of business especially in the service business4. allow for a high degree of business adaptability and extensibility.5. be supplemented by a broad offer of partner add-ons supporting accelerated innovation.These new business service platforms will play a key role in the digital transformation of the software industry.\",Be aware of the big business productivity progress enabled by BIS in the last 50 years. Understand the limitati-ons of these systems in spite of the digital transformation of the software industry ahead. Be able to critically as-sess the business potential of new IC technologies. Understand the business demand for change. Understand the necessary organizational learning needed to leverage new technology for business change management.,V (2),Written examination (approx. 60 minutes)Creditable for bonusLanguage of assessment: German and/or English,\"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.\",--,150 h,--,--\\r\\n\"Business Processes Organisation, Business Software and Process Industries\",12-GLP-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"ERP systems have become key elements of successful companies. Business processes in companies can no lon-ger be managed without using such ERP systems. In financial departments of companies, such systems have be-en used for a long time, but business processes e. g. for logistical tasks have so far not been supported by ERP solutions. This module explains how this issue could be resolved as well as what constraints and what depen-dencies have to be considered.\",\"After completing this module, students should be able to(i) know about actual business processes in companies;(ii) understand selected problems in the organization and design of logistical business processes and work out solutions;(iii) know and design basic data structures and data flows of an ERP system;(iv) map businesss processes within an ERP system;(v) consider the specifics of a certain industry (e. g. the process industry) when organizing business processes;(vi) map the core business processes within an ERP system.\",V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or Englishcreditable for bonus,\"20 places. (1) Should the number of applications exceed the number of available places, places will be allocated by lot among all applicants irrespective of their subjects. (2) Places on all courses of the module with a restricted number of places will be allocated in the same procedure. (3) A waiting list will be maintained and places re-allo-cated by lot as they become available.\",--,150 h,--,--\\r\\nWork and Information,12-ITA-161-m01,Faculty of Business Management and Economics,holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"This module discusses relevant principles, concepts and applications of business information processing and its impact on organisational and process structures in todays business world.\",\"The expertise gained from other modules related to business management issues can be interpreted and clas-sified in a certain way by participating in this module. For decisions in regards to human resources planning, in-vestment, and a companys strategy, the students will get to know all the relevant concepts and interdependen-cies, which come with taking information processing into account as the so called \"\"fourth\"\" factor of production.\",V (2),a) written examination (approx. 60 minutes) or b) oral examination (one candidate each: approx. 15 to 20 minu-tes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or English,--,--,150 h,--,--\\r\\nWork Order Planning for Automated Manufacturing,12-M-AGAF-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"The idea of integration of business information systems is primarily practiced and developed as an ERP system in terms of business application areas, their temporal overlap (data warehouse), their spatial relationship (sup-ply network) and connection of legal tasks (eGovernment). However, linking the commercial view of incoming cu-stomer orders with the logistic or more technical view of the scheduling of production orders and the resulting consequences for the processes is a critical success factor.\",Linking research and lectures of the Institute of Robotics and Telematics as well as the orientation of the Chair of Business Integration allows students a conceptual as well as practical insight into the challenges of this in the future essential part of the operational automation development.,V (2) + Ü (2),written examination (approx. 60 minutes)Language of assessment: German and/or English,--,--,150 h,--,--\\r\\nTopics in Business Information Systems 1,12-M-ATW1-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.\",\"The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.\",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,\"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus\",--,--,150 h,--,--\\r\\nTopics in Business Information Systems 2,12-M-ATW2-161-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"This course is a dummy module, e. g. for courses in the area of business informatics taken abroad.\",\"The competences depend on the individual module, which has been taken to transfer these credits to the Univer-sity of Wuerzburg.\",V (2) + Ü (2)Course type: alternatively S instead of V + Ü,\"a) written examination (approx. 60 minutes) or b) presentation (15 to 20 minutes) and written elaboration (ap-prox. 20 pages), weighted 1:2 or c) oral examination (one candidate each: approx. 10 to 15 minutes; groups of 2: approx. 20 minutes; groups of 3: approx. 30 minutes)Language of assessment: German and/or Englishcreditable for bonus\",--,--,150 h,--,--\\r\\nInformation systems research,12-M-ISR-192-m01,Faculty of Business Management and Economics,Holder of the Chair of Business Management and Business,5,numerical grade,1 semester,graduate,\"The course provides an overview of theoretical scientific foundations, theories, research topics and methods of international research in business informatics.\",\"The module provides students with knowledge of:(i) Exploration of classical themes of WI / IS research;(ii) Getting to know the relevant paradigms, theories and methods;(iii) Recognition of the interfaces to other areas of business administration and management practice;(iv) Gain experience in finding and evaluation of scientific literature\",V (2) + Ü (2),\"a) Written examination (approx. 60 minutes) orb) oral examination (one candidate each: approx. 15 to 20 minutes, groups of 2: approx. 20 minutes, groups of 3: approx. 30 minutes)Creditable for bonusLanguage of assessment: German and/or English\",\"40 places.Should the number of applications exceed the number of available places, places will be allocated as follows:(1) Masters students of Information Systems will be given preferential consideration.(2) The remaining places will be allocated to students of other subjects.(3) When places are allocated in accordance with (1) and (2) and the number of applications exceeds the number of available places, places will be allocated by lot among applicants from this group.\",--,150 h,--,--\\r\\nDatabases 2,10-I=DB2-161-m01,Institute of Computer Science,Dean of Studies Informatik (Computer Science),5,numerical grade,1 semester,graduate,Data warehouses and data mining; web databases; introduction to Datalog.,\"The students have advanced knowledge about relational databases, XML and data mining.\",V (2) + Ü (2),\"written examination (approx. 60 to 120 minutes).If announced by the lecturer at the beginning of the course, the written examination may be replaced by an oral examination of one candidate each (approx. 20 minutes) or an oral examination in groups of 2 candidates (ap-prox. 15 minutes per candidate).Language of assessment: German and/or Englishcreditable for bonus\",--,\"Focuses available for students of the Masters programme Informatik (Computer Science, 120 ECTS credits): SE, IS, HCI.\",150 h,--,--\\r\\n'" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# format all the dataframes in the tables list\n", + "processed_tables = _preprocess_tables(tables)\n", + "# display the formatted table\n", + "processed_tables[2]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "import pinecone\n", + "\n", + "# connect to pinecone environment\n", + "pinecone.init(\n", + " api_key=\"1d3ebed2-b4fa-4523-9cd4-722ac005fc6b\",\n", + " environment=\"us-west1-gcp-free\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# you can choose any name for the index\n", + "index_name = \"table-qa-module-catalogue-split\"\n", + "\n", + "# check if the table-qa index exists\n", + "if index_name not in pinecone.list_indexes():\n", + " # create the index if it does not exist\n", + " pinecone.create_index(\n", + " index_name,\n", + " dimension=768,\n", + " metric=\"cosine\"\n", + " )\n", + "\n", + "# connect to table-qa index we created\n", + "index = pinecone.Index(index_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "90c0c985ab4740c2959ffd263172225c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/1 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Module titleAbbreviationModule coordinatorModule offered byETCSMethod of gradingDurationModule levelContentsIntended learning outcomesCoursesMethod of assessmentAllocation of placesAdditional informationWorkloadTeaching cycleReferred to in LPO I
0Information Processing within Organizations12-IV-161-m01Faculty of Business Management and Economicsholder of the Chair of Business Management and...5numerical grade1 semestergraduate\\n\\nContent:\\nThis course provides students wi...After completing the course \"Integrated Inform...\\n\\nV (2) + Ü (2)\\n\\n\\n\\nwritten examination (approx. 60 minutes)\\n...\\n\\n--\\n\\n\\n\\n--\\n\\n\\n\\n150 h\\n\\n\\n\\n--\\n\\n\\n\\n--\\n\\n
1IT-Management12-M-ITM-161-m01Faculty of Business Management and EconomicsHolder of the Chair of Information Systems Eng...5numerical grade1 semestergraduate\\n\\nContent:\\nThis course provides students wi...After completing the course \"IT Management\", s...\\n\\nV (2) + Ü (2)\\n\\n\\n\\na) written examination (approx. 60 minutes...\\n\\n--\\n\\n\\n\\n--\\n\\n\\n\\n150 h\\n\\n\\n\\n--\\n\\n\\n\\n--\\n\\n
2Project Seminar12-PS-192-m01Faculty of Business Management and EconomicsHolder of the Chair of Business Management and...15numerical grade1 semestergraduate\\n\\nContent:\\nIn small project teams of 4 to 1...After completing the course \"Projektseminar\", ...\\n\\nS (2)\\n\\n\\n\\nproject: preparing a conceptual design (ap...\\n\\n--\\n\\n\\n\\n--\\n\\n\\n\\n450 h\\n\\n\\n\\n--\\n\\n\\n\\n--\\n\\n
3Information Retrieval10-I=IR-161-m01Institute of Computer ScienceDean of Studies Informatik (Computer Science)5numerical grade1 semestergraduate\\n\\nIR models (e. g. Boolean and vector space ...The students possess theoretical and practical...\\n\\nV (2) + Ü (2)\\n\\n\\n\\nwritten examination (approx. 60 to 120 min...\\n\\n--\\n\\n\\n\\nFocuses available for students of the Mast...\\n\\n150 h\\n\\n\\n\\n--\\n\\n\\n\\n--\\n\\n
4Analysis and Design of Programs10-I=PA-161-m01Institute of Computer Scienceholder of the Chair of Computer Science II5numerical grade1 semestergraduate\\n\\nProgram analysis, model creation in softwa...The students are able to analyse programs, to ...\\n\\nV (2) + Ü (2)\\n\\n\\n\\nwritten examination (approx. 60 to 120 min...\\n\\n--\\n\\n\\n\\nFocuses available for students of the Mast...\\n\\n150 h\\n\\n\\n\\n--\\n\\n\\n\\n--\\n\\n
\n", + "" + ], + "text/plain": [ + " Module title Abbreviation \\\n", + "0 Information Processing within Organizations 12-IV-161-m01 \n", + "1 IT-Management 12-M-ITM-161-m01 \n", + "2 Project Seminar 12-PS-192-m01 \n", + "3 Information Retrieval 10-I=IR-161-m01 \n", + "4 Analysis and Design of Programs 10-I=PA-161-m01 \n", + "\n", + " Module coordinator \\\n", + "0 Faculty of Business Management and Economics \n", + "1 Faculty of Business Management and Economics \n", + "2 Faculty of Business Management and Economics \n", + "3 Institute of Computer Science \n", + "4 Institute of Computer Science \n", + "\n", + " Module offered by ETCS Method of grading \\\n", + "0 holder of the Chair of Business Management and... 5 numerical grade \n", + "1 Holder of the Chair of Information Systems Eng... 5 numerical grade \n", + "2 Holder of the Chair of Business Management and... 15 numerical grade \n", + "3 Dean of Studies Informatik (Computer Science) 5 numerical grade \n", + "4 holder of the Chair of Computer Science II 5 numerical grade \n", + "\n", + " Duration Module level Contents \\\n", + "0 1 semester graduate \\n\\nContent:\\nThis course provides students wi... \n", + "1 1 semester graduate \\n\\nContent:\\nThis course provides students wi... \n", + "2 1 semester graduate \\n\\nContent:\\nIn small project teams of 4 to 1... \n", + "3 1 semester graduate \\n\\nIR models (e. g. Boolean and vector space ... \n", + "4 1 semester graduate \\n\\nProgram analysis, model creation in softwa... \n", + "\n", + " Intended learning outcomes Courses \\\n", + "0 After completing the course \"Integrated Inform... \\n\\nV (2) + Ü (2)\\n\\n \n", + "1 After completing the course \"IT Management\", s... \\n\\nV (2) + Ü (2)\\n\\n \n", + "2 After completing the course \"Projektseminar\", ... \\n\\nS (2)\\n\\n \n", + "3 The students possess theoretical and practical... \\n\\nV (2) + Ü (2)\\n\\n \n", + "4 The students are able to analyse programs, to ... \\n\\nV (2) + Ü (2)\\n\\n \n", + "\n", + " Method of assessment Allocation of places \\\n", + "0 \\n\\nwritten examination (approx. 60 minutes)\\n... \\n\\n--\\n\\n \n", + "1 \\n\\na) written examination (approx. 60 minutes... \\n\\n--\\n\\n \n", + "2 \\n\\nproject: preparing a conceptual design (ap... \\n\\n--\\n\\n \n", + "3 \\n\\nwritten examination (approx. 60 to 120 min... \\n\\n--\\n\\n \n", + "4 \\n\\nwritten examination (approx. 60 to 120 min... \\n\\n--\\n\\n \n", + "\n", + " Additional information Workload \\\n", + "0 \\n\\n--\\n\\n \\n\\n150 h\\n\\n \n", + "1 \\n\\n--\\n\\n \\n\\n150 h\\n\\n \n", + "2 \\n\\n--\\n\\n \\n\\n450 h\\n\\n \n", + "3 \\n\\nFocuses available for students of the Mast... \\n\\n150 h\\n\\n \n", + "4 \\n\\nFocuses available for students of the Mast... \\n\\n150 h\\n\\n \n", + "\n", + " Teaching cycle Referred to in LPO I \n", + "0 \\n\\n--\\n\\n \\n\\n--\\n\\n \n", + "1 \\n\\n--\\n\\n \\n\\n--\\n\\n \n", + "2 \\n\\n--\\n\\n \\n\\n--\\n\\n \n", + "3 \\n\\n--\\n\\n \\n\\n--\\n\\n \n", + "4 \\n\\n--\\n\\n \\n\\n--\\n\\n " + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "id = int(result[\"matches\"][0][\"id\"])\n", + "tables[id].head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### The table returned by the Pinecone index indeed has the answer to our query. Now we need a model that can read this table and extract the precise answer." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import pipeline, TapasTokenizer, TapasForQuestionAnswering\n", + "\n", + "model_name = \"google/tapas-base-finetuned-wtq\"\n", + "# load the tokenizer and the model from huggingface model hub\n", + "tokenizer = TapasTokenizer.from_pretrained(model_name)\n", + "model = TapasForQuestionAnswering.from_pretrained(model_name, local_files_only=False)\n", + "# load the model and tokenizer into a question-answering pipeline\n", + "pipe = pipeline(\"table-question-answering\", model=model, tokenizer=tokenizer, device=device)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'answer': 'AVERAGE > 5',\n", + " 'coordinates': [(1, 4)],\n", + " 'cells': ['5'],\n", + " 'aggregator': 'AVERAGE'}" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pipe(table=tables[id], query=query)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "def query_pinecone(query):\n", + " # generate embedding for the query\n", + " xq = retriever.encode([query]).tolist()\n", + " # query pinecone index to find the table containing answer to the query\n", + " result = index.query(xq, top_k=1)\n", + " # return the relevant table from the tables list\n", + " return tables[int(result[\"matches\"][0][\"id\"])]" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "def get_answer_from_table(table, query):\n", + " # run the table and query through the question-answering pipeline\n", + " answers = pipe(table=table, query=query)\n", + " return answers" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "query = \"Which modules are about IT?\"\n", + "table = query_pinecone(query)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'answer': 'AVERAGE > 5',\n", + " 'coordinates': [(1, 4)],\n", + " 'cells': ['5'],\n", + " 'aggregator': 'AVERAGE'}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_answer_from_table(table, query)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Download.jpeg b/Download.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..2a33017e4154c9b7c59ee0d7e02c617dbf4804a1 Binary files /dev/null and b/Download.jpeg differ diff --git a/README.md b/README.md index 3b0d2750fe1184578f18a5a12654513c8088d32b..c7d10ebdbd08dea769c22bc769a74b65ef6d06d6 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,6 @@ --- -title: Module Guide Assistant -emoji: 📉 -colorFrom: pink -colorTo: indigo +title: module-guide-assistant +app_file: frontend_app.py sdk: gradio sdk_version: 3.35.2 -app_file: app.py -pinned: false --- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference diff --git a/frontend_app.ipynb b/frontend_app.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..2e1c123fb7a6645193bb690a20a36d6462b11434 --- /dev/null +++ b/frontend_app.ipynb @@ -0,0 +1,282 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import gradio as gr\n", + "import pandas as pd\n", + "from transformers import TapasTokenizer, TapasForQuestionAnswering\n", + "from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering\n", + "from transformers import pipeline\n", + "import PIL\n", + "\n", + "# read the module_guide_tableQA\\0915NC_Studienplaetze.jpg as pil image\n", + "pil_image = PIL.Image.open(\"0915NC_Studienplaetze.jpg\")\n", + "# make that image a bit less high\n", + "pil_image = pil_image.resize((int(pil_image.width * 0.5), int(pil_image.height * 0.5)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def get_answer(\n", + " dropdown,\n", + " question,\n", + " view_as_table=False,\n", + " model=\"google/tapas-finetuned-wtq\",\n", + " #progress=gr.Progress(),\n", + "):\n", + " #progress(0, desc=\"Looking for answer in module guide...\")\n", + " df = pd.DataFrame()\n", + " if dropdown == \"Master Information Systems\":\n", + " df = pd.read_excel(\n", + " r\"03_extracted_final_modules\\MS_IS_all_modules_orginal_15_rows_cleaned.xlsx\"\n", + " )\n", + " elif dropdown == \"Bachelor Information Systems\":\n", + " df = pd.read_excel(r\"03_extracted_final_modules\\BA_IS_all_modules_15.xlsx\")\n", + " elif dropdown == \"Bachelor Management\":\n", + " df = pd.read_excel(r\"03_extracted_final_modules\\BA_MM_all_modules_15.xlsx\")\n", + " df = df.astype(str)\n", + " print(question)\n", + " question = str(question)\n", + " print(df.shape)\n", + " question = [question]\n", + "\n", + " if model == \"google/tapas-finetuned-wtq\":\n", + " tqa = pipeline(\n", + " task=\"table-question-answering\", model=\"google/tapas-base-finetuned-wtq\"\n", + " )\n", + " elif model == \"google/tapas-large-finetuned-wtq\":\n", + " tqa = pipeline(\n", + " task=\"table-question-answering\", model=\"google/tapas-large-finetuned-wtq\"\n", + " )\n", + "\n", + " results = tqa(table=df, query=question)\n", + " print(results)\n", + " cells_input = results[\"cells\"]\n", + " cells_input = str(cells_input)\n", + " cells_input = cells_input.replace(\"[\", \"\")\n", + " cells_input = cells_input.replace(\"]\", \"\")\n", + " cells_input = cells_input.replace(\"'\", \"\")\n", + "\n", + " print(cells_input)\n", + " print(results)\n", + " html_string_short = f\"

Short Answer:

{cells_input}

\"\n", + " row_numbers = [coord[0] for coord in results[\"coordinates\"]]\n", + " df_short = df.iloc[row_numbers]\n", + " df_short = df_short.dropna(axis=1, how=\"all\")\n", + " df_short = df_short.loc[:, (df_short != \"--\").any(axis=0)]\n", + " html_table = (\n", + " f\"

Complete Module(s):

{df_short.to_html(index=False)}

\"\n", + " )\n", + "\n", + " # check if there are more than 1 rows in df_short\n", + " html_string = \"\"\n", + " if df_short.shape[0] > 1 or view_as_table == True:\n", + " html_string = html_table\n", + " elif df_short.shape[0] == 1:\n", + " html_string = \"\"\"\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "

Detailed Module Information

\n", + "\n", + "
\n", + "

Module title:

\n", + "

Project Seminar

\n", + "
\n", + "
\n", + "

Abbreviation:

\n", + "

12-PS-192-m01

\n", + "
\n", + "
\n", + "

Module coordinator:

\n", + "

Faculty of Business Management and Economics

\n", + "
\n", + "
\n", + "

Module offered by:

\n", + "

Holder of the Chair of Business Management and Business

\n", + "
\n", + "
\n", + "

ETCS:

\n", + "

15

\n", + "
\n", + "
\n", + "

Method of grading:

\n", + "

numerical grade

\n", + "
\n", + "
\n", + "

Duration:

\n", + "

1 semester

\n", + "
\n", + "
\n", + "

Module level:

\n", + "

graduate

\n", + "
\n", + "
\n", + "

Contents:

\n", + "

In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analysis, to-be conception and implementation of an IS solution. The project teams will be required to work independently and will only receive advice and minor support from research assistants.

\n", + "
\n", + "
\n", + "

Intended learning outcomes:

\n", + "
    \n", + "
  • Analyze business tasks and requirements and generate fitting IS solutions
    • \n", + "
  • Apply project management methods
    • \n", + "
  • Internalize stress, time and conflict management by means of practical teamwork
    • \n", + "
\n", + "
\n", + "
\n", + "

Courses:

\n", + "

Project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1

\n", + "

Language of assessment: German, English

\n", + "

Creditable for bonus

\n", + "
\n", + "
\n", + "

Workload:

\n", + "

450 hours

\n", + "
\n", + " \n", + " \"\"\"\n", + " else:\n", + " html_string = \"\"\n", + "\n", + " return html_string_short, html_string\n", + "\n", + "\n", + "def change_html_link(dropdown_item):\n", + " html_link = \"\"\n", + " if dropdown_item == \"Master Information Systems\":\n", + " html_link = f'

View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

'\n", + " elif dropdown_item == \"Bachelor Information Systems\":\n", + " html_link = f'View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

'\n", + " elif dropdown_item == \"Bachelor Management\":\n", + " html_link = f'View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

'\n", + "\n", + " return html_link" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on local URL: http://127.0.0.1:7867\n", + "Running on public URL: https://a7a23badcaa31f041e.gradio.live\n", + "\n", + "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with gr.Blocks() as demo: \n", + " gr.HTML(\n", + " \"\"\"\n", + "
\n", + " \"Module\n", + "
\n", + " \"\"\"\n", + " )\n", + "\n", + " gr.HTML(\n", + " \"

Your Module Guide Assistant

\"\n", + " )\n", + " table = gr.Dropdown(\n", + " [\n", + " \"Master Information Systems\",\n", + " \"Bachelor Information Systems\",\n", + " \"Bachelor Management\",\n", + " ],\n", + " label=\"Select Module Guide\",\n", + " value=\"Master Information Systems\",\n", + " )\n", + " html_link = gr.HTML(\n", + " \"\"\"\n", + "

View complete PDF here: Master Information Systems

\n", + "

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

\n", + " \"\"\"\n", + " )\n", + "\n", + " table.change(change_html_link, table, html_link)\n", + " question = gr.Textbox(\n", + " label=\"Question\", value=\"How many ECTS credits does the project seminar have?\"\n", + " )\n", + " with gr.Accordion(\"Advanced Options\", open=False):\n", + " with gr.Group():\n", + " model_selction = gr.Dropdown(\n", + " [\n", + " \"google/tapas-finetuned-wtq\",\n", + " \"google/tapas-large-finetuned-wtq\",\n", + " ],\n", + " label=\"Select Model\",\n", + " value=\"google/tapas-finetuned-wtq\",\n", + " )\n", + " view_as_table_or_text = gr.Checkbox(\n", + " label=\"View detailed information as table\", value=False\n", + " )\n", + "\n", + " ask_btn = gr.Button(\"Ask The Assistant\")\n", + " gr.HTML(\"
\")\n", + " inputs = [table, question, view_as_table_or_text, model_selction]\n", + " output_question = gr.HTML(label=\"Answer\")\n", + " outout_full_module = gr.HTML(label=\"Detailed Description\")\n", + " outputs = [output_question, outout_full_module]\n", + " ask_btn.click(fn=get_answer, inputs=inputs, outputs=outputs, api_name=\"greet\")\n", + "\n", + "demo.launch(debug=True, share=True)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "enterpriseai2", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/frontend_app.py b/frontend_app.py new file mode 100644 index 0000000000000000000000000000000000000000..7791540a8ee69d9cdc4f657cb8a293b450d2c0eb --- /dev/null +++ b/frontend_app.py @@ -0,0 +1,226 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[ ]: + + +import gradio as gr +import pandas as pd +from transformers import TapasTokenizer, TapasForQuestionAnswering +from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering +from transformers import pipeline +import PIL + +# read the module_guide_tableQA\0915NC_Studienplaetze.jpg as pil image +pil_image = PIL.Image.open("0915NC_Studienplaetze.jpg") +# make that image a bit less high +pil_image = pil_image.resize((int(pil_image.width * 0.5), int(pil_image.height * 0.5))) + + +# In[ ]: + + +def get_answer( + dropdown, + question, + view_as_table=False, + model="google/tapas-finetuned-wtq", + #progress=gr.Progress(), +): + #progress(0, desc="Looking for answer in module guide...") + df = pd.DataFrame() + if dropdown == "Master Information Systems": + df = pd.read_excel( + r"03_extracted_final_modules\MS_IS_all_modules_orginal_15_rows_cleaned.xlsx" + ) + elif dropdown == "Bachelor Information Systems": + df = pd.read_excel(r"03_extracted_final_modules\BA_IS_all_modules_15.xlsx") + elif dropdown == "Bachelor Management": + df = pd.read_excel(r"03_extracted_final_modules\BA_MM_all_modules_15.xlsx") + df = df.astype(str) + print(question) + question = str(question) + print(df.shape) + question = [question] + + if model == "google/tapas-finetuned-wtq": + tqa = pipeline( + task="table-question-answering", model="google/tapas-base-finetuned-wtq" + ) + elif model == "google/tapas-large-finetuned-wtq": + tqa = pipeline( + task="table-question-answering", model="google/tapas-large-finetuned-wtq" + ) + + results = tqa(table=df, query=question) + print(results) + cells_input = results["cells"] + cells_input = str(cells_input) + cells_input = cells_input.replace("[", "") + cells_input = cells_input.replace("]", "") + cells_input = cells_input.replace("'", "") + + print(cells_input) + print(results) + html_string_short = f"

Short Answer:

{cells_input}

" + row_numbers = [coord[0] for coord in results["coordinates"]] + df_short = df.iloc[row_numbers] + df_short = df_short.dropna(axis=1, how="all") + df_short = df_short.loc[:, (df_short != "--").any(axis=0)] + html_table = ( + f"

Complete Module(s):

{df_short.to_html(index=False)}

" + ) + + # check if there are more than 1 rows in df_short + html_string = "" + if df_short.shape[0] > 1 or view_as_table == True: + html_string = html_table + elif df_short.shape[0] == 1: + html_string = """ + + + + +
+

Detailed Module Information

+ +
+

Module title:

+

Project Seminar

+
+
+

Abbreviation:

+

12-PS-192-m01

+
+
+

Module coordinator:

+

Faculty of Business Management and Economics

+
+
+

Module offered by:

+

Holder of the Chair of Business Management and Business

+
+
+

ETCS:

+

15

+
+
+

Method of grading:

+

numerical grade

+
+
+

Duration:

+

1 semester

+
+
+

Module level:

+

graduate

+
+
+

Contents:

+

In small project teams of 4 to 10 members, students will spend several months actively working on a specific and realistic problem with practical relevance. They will progress through several project stages including as-is analysis, to-be conception and implementation of an IS solution. The project teams will be required to work independently and will only receive advice and minor support from research assistants.

+
+
+

Intended learning outcomes:

+
    +
  • Analyze business tasks and requirements and generate fitting IS solutions
    • +
  • Apply project management methods
    • +
  • Internalize stress, time and conflict management by means of practical teamwork
    • +
+
+
+

Courses:

+

Project: preparing a conceptual design (approx. 150 hours), designing and implementing an approach to solution (approx. 300 hours) as well as presentation (approx. 20 minutes), weighted 1:2:1

+

Language of assessment: German, English

+

Creditable for bonus

+
+
+

Workload:

+

450 hours

+
+ + """ + else: + html_string = "" + + return html_string_short, html_string + + +def change_html_link(dropdown_item): + html_link = "" + if dropdown_item == "Master Information Systems": + html_link = f'

View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

' + elif dropdown_item == "Bachelor Information Systems": + html_link = f'View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

' + elif dropdown_item == "Bachelor Management": + html_link = f'View complete pdf here: {dropdown_item}

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

' + + return html_link + + +# In[20]: + + +with gr.Blocks() as demo: + gr.HTML( + """ +
+ Module Guide Header Image +
+ """ + ) + + gr.HTML( + "

Your Module Guide Assistant

" + ) + table = gr.Dropdown( + [ + "Master Information Systems", + "Bachelor Information Systems", + "Bachelor Management", + ], + label="Select Module Guide", + value="Master Information Systems", + ) + html_link = gr.HTML( + """ +

View complete PDF here: Master Information Systems

+

Ask whatever you want to know about the module guide here. You can ask formality-based and content-based questions.

+ """ + ) + + table.change(change_html_link, table, html_link) + question = gr.Textbox( + label="Question", value="How many ECTS credits does the project seminar have?" + ) + with gr.Accordion("Advanced Options", open=False): + with gr.Group(): + model_selction = gr.Dropdown( + [ + "google/tapas-finetuned-wtq", + "google/tapas-large-finetuned-wtq", + ], + label="Select Model", + value="google/tapas-finetuned-wtq", + ) + view_as_table_or_text = gr.Checkbox( + label="View detailed information as table", value=False + ) + + ask_btn = gr.Button("Ask The Assistant") + gr.HTML("
") + inputs = [table, question, view_as_table_or_text, model_selction] + output_question = gr.HTML(label="Answer") + outout_full_module = gr.HTML(label="Detailed Description") + outputs = [output_question, outout_full_module] + ask_btn.click(fn=get_answer, inputs=inputs, outputs=outputs, api_name="greet") + +demo.launch(debug=True, share=True) +