6.情報学コース
Informatics
Course Code40INF001**

40INF002**

40INF003**

40INF004**

CourseIntroduction to Mathematical Logic

Introduction to Algorithms

High-Performance Computing

Information Sharing SystemArchitecture

CreditContent of Subject

2Basic knowledge of mathematical logic, in particular, firstorder logic will be explained.The aim is to be able to write
proofs in first-order logic and explaining soundness theorem
and completeness theorem, and explain Hoare logic, sequentsystem, and Peano arithmetic.

2Give an introduction to the algroithm theory, including
complexity, order, sorting algorithm, data structres such asheap and binarytrees. We also show some optimization
algroithms and string, enumeration algorithms.

2This course gives lectures on theory, implementation,application and future directions of the high performancecomputing technology utilizing supercomputers, PC clusters,
on-chip multiprocessors and grid computing.

2

This course will discuss information and communication
network architectures, including (1)advanced networking
technologies and network systems technologies for a variety
of telecommunication network services,(2)circuit switchingand packet switching,network layering and each layer's
function and (3)security technology.

40INF005**

Applied Linear Algebra

2Linear algebra is significantly essential in natural science andengineering. Moreover, it becomes to play an important role indata science recent years. In this lecture, we will learn thebasic properties and numerical methods of linear algebra. We
will also learn about practical applications.

40INF006**

Introduction to Software Science 1

2

This course presents two main themes in Software
Science,representation of software (programming andmodeling) and software systems.

40INF007**

Introduction to Software Science 22This course presents basic knowledge of Software Science
focusing on data management, data processing, and dataanalysis, including topics such as data engineering, datamodeling, data mining, and real-world data analysis.

2

Faculty members in Multimedia Information Science will givelectures on various topics covered by multimedia information
sciences. Through this course, students will acquire
knowledge in the fundamental fields that make up multimedia
information sciences and will be able to apply it for their own
purposes.

2Lectures are given on the fundamentals of intelligent systems
science, including artificial intelligence, human-agent
interaction, machine learning, natural language processing andintelligent robotics, vision and language, recommendersystems.

2This course gives knowledge on fundamental fields, such asmachine learning, information geometry, natural language
processing, deep learning, semantic web, data analyticalmethods, and computational social science for intelligent
systems science.

40INF008**

Introduction to Multimedia Information
Science

40INF009**

Introduction to Intelligent Systems
Science 1

40INF010**

Introduction to Intelligent Systems
Science 26.情報学コース
Informatics
Course Code40INF011**

40INF012**

40INF013**

CourseIntroduction to Information Environment
Science

Scientific Presentation

Scientific Writing

CreditContent of Subject

2

As the progress of information technology, interaction ofsociety, technology and information is facing great changes.
This course introduces researches on creation, distribution,
usage and storage of information. Participants are expected
to understand the issues and trend of researches on therelationships between information and society.

1

These lectures provide practical instruction for students toimprove their presentation materials and presenting skills. We
explore in detail the function, structure, form, and content ofscientific presentations. Students also work together toprovide feedback and suggestions for improving theirscientific presentations.

1

Strategies for scientific writing will be examined. The
students will be asked to read the titles, abstracts andintroductions of several real research papers of varying
quality, and to critique them in light of organizational
principles. Students will be encouraged to supply samples of
their own technical writing for analysis by the class.

40INF014**

Introduction to Information Security
Infrastructure

2

Information security technology, service, system, rule, andlaw give a fundamental framework for providing ICT(information and communication technology) systems andservices. This course will introduce information security andgive its explain in an ICT governance way.

40INF015**

Introduction to Big Data Science2This course will introduce basic concepts and methodologies
of large scale data processing, analysis, security, andvisualization by discussing relevant applications.

40INF016**

Practical Data Science2

To practice data science, several researchers take turns topresent and discuss subjects such as data acquisition, dataconstruction, data visualization and data analysis.

2This course introduces the basic knowledge of informatics
that is required to develop intelligent robot systems. It also
focuses on real-time sensor information processing andsystem integration method for the development of robot
systems.

2

This course aims to introduce the fundamental techniques ofnatural language processing (NLP), i.e. the study of humanlanguages from a computational and engineering perspective.
Basic topics include part-of-speech tagging, lexical analysis,
syntactic and discourse parsing, language modeling, and word
sense disambiguation. Dialogue system and question
answering are included as practical applications. We also
learn about cutting-edge research and deepen understandingof current issues and future developments.

2Understanding the basic technology for ICT-enabled services
and its application.This course focuses on how E-businessincluding Electronic Commerce or Electronic Money affects
the economic activity or social structure.

2

In this course, students learn basic statistical methods andmultivariate analysis techniques, with the expectation ofgaining insights into academic communities and educational
activities through the statistical analysis of bibliographic data,and educational data.

40INF017**

40INF018**

40INF019**

40INF020**

Robot Informatics

Natural Language Processing

ICT-enabled Business

Introduction to Statistical Methods inBibliometrics

6.情報学コース
Informatics
Course Code40INF021**

CourseLogic in Computer ScienceCredit

Content of Subject

2

Type theory gives a fundamental framework for programming
languages and software specification. This course will
introduce type theory and explain it in a mathematicallyrigorous way. The aim is complete mathematicalunderstanding of the introductory part of type theory,and theability of applying type theory to practical problems.

40INF022**

Discrete Mathematics

2Discrete mathematics has become popular in recent decades
because of its applications to computer science. Concepts
and notations from discrete mathematics are useful to study
or describe objects or problems in computer algorithms andprogramming languages.

40INF023**

Computational Complexity Theory

2

In this lecture, we explain the basics of computational
complexity theory. The topics include the P versus NP
problem, the theory of NP-completeness, and therelativization barriers.

2Game theory is the mathematical theory that models thestrategic interactions among self-interested agents. This
course covers selected theoretical topics in algorithmic gametheory that aims to understand the design of the algorithms
in strategic environments. The course's topics include:
solution concepts in game theory, such as Nash equilibrium
and correlated equilibrium, and their computation;
computational social choice: procedures for fair division, suchas cake cutting algorithms.

2This course will focus on (1) computer architecture including
high-performance microprocessors and LSI technologies, and(2) system software stack, including communication
mechanisms and parallel file systems, all of which areindispensable for designing highly-reliable high-performancecomputer systems.

2This course provides an introduction of the principle，algorithms，system architecture，wireless communications
basics，and performance evaluation methods of informationand communication systems. (lecture)2

Distributed systems are widely used from IoT to cloudcomputing nowadays. This lecture explains basic concepts on
distributed systems, e.g., distributed algorithms and protocols
and then advanced knowledges, e.g., distributed systemarchitecture and distributed data processing, to understand
distributed systems.

2In this lecture class, students learn software engineering
techniques for efficient development and operation of largescale, high-quality software. We have overview of activities
and techniques for each phase in the development process isgiven. We also have discussion over various development
paradigms as well as state-of-the-art topics.

40INF024**

Computational Game Theory

40INF025**

Computer System Design

40INF026**

Information and Communication
Systems

40INF027**

40INF028**

Distributed Systems

Software Engineering6.情報学コース
Informatics
Course CodeCourseCreditContent of Subject

This class introduce database theory based on databaseprogramming languages. Especially, Datalog, which is a logicalfoundation of query languages in relational databases, is used.

40INF029**

Database Theory

240INF030**

Programming Languages and Theory

2Learn about the basics of programming languages andimplement a small language, using the book "Types andprogramming languages" as a textbook.

40INF031**

Mathematical Structures in Formal
Methods

2Model checking is a fundamental technique in software
science. The course introduces its mathematical theory andpractical algorithms. Our emphasis is especially on themathematical theory of fixed points, formulated in latticetheory and category theory.

2

This course gives a lecture on technologies for software
verification. In particular, it introduces techniques based ontype systems, which make it possible to verify software
exhaustively and rigorously.

2This course explains the overview of the basic technologies
related to whole aspect of media processing especiallypattern recognition theory and signal processing theory.
These technologies are indispensable for media analysis,
feature extraction, media conversion, and so on. Projectworks such as video information processing will be assigned
upon necessity to deepen the understanding.

2

Students will learn techniques for processing, analyzing,processing/editing, and presenting media such as audio andimages as examples of media processing applications.
Specifically, image processing, image analysis, imagegeneration, and audio information processing will be studied,including mathematics and implementable algorithms.
Advanced multimedia technologies combining thesetechniques will also be studied as needed. Students will
acquire basic concepts and algorithms related to media
processing and be able to apply them to their own work.

2In this course, we will study the basic techniques underlying
Deep Learning and its main architectures, including Neural
Networks, Convolutional Neural Networks, Recurrent Neural
Networks, Transformers, and so on. We will also discuss
practical examples of Deep Learning applied to intelligent
drones and time series analysis.

2We exchange a variety of information with others and build
relationships not only in face-to-face situations, but also via
mobile phones and the Internet. To discuss such"communication environments" in our daily lives, this lecture
comprehensively discusses the usefulness of related previousstudies and their methodologies.

40INF032**

40INF033**

40INF034**

40INF035**

40INF036**

Software Verification

Fundamentals of Media Processing

Applications of Multimedia Processing

Deep Learning

Communication Environments

6.情報学コース
Informatics
Course CodeCourse

CreditContent of Subject

40INF037**

Data Mining

2

This course introduces data mining from theory to practice.

40INF038**

Methodology of Scientometrics

2To be able to quantitatively grasp the trends in science andanalyze and judge the current situation and problems, afterunderstanding the quantitative methods for science.

2“Efficient” algorithms have meant polynomial-timealgorithms. As the data size is increasingly large, however,even polynomial-time algorithms could be too slow. To handle
such large data, sublinear-time algorithms, especially, theframework of "property testing", have been developed in thelast decades, where sublinear means less than linear. This
course will cover theoretical foundations of sublinear-timealgorithms.

2

Market design is a field of research that considers how todesign rules of markets, such as matching and auction
markets. Through game-theoretic analysis, this field aims todesign market rules that yield socially desirable outcomes,
while each participant acts selfishly. In this course, we learn
the theory and applications of market design, while laying
emphasis on its algorithmic and discrete mathematicalaspects.

2

Machine learning tasks often involve combinatorial structures.
To design an efficient algorithm for these problems,
techniques of combinatorial optimization are indispensable.
This course will cover the theory of combinatorial
optimization, such as submodular optimization andapproximation algorithms, and its applications to machinelearning.

2This course focuses on probabilistic models in informatics,
which play important roles in the modeling of real-world data.
The course includes the basics of probability theory,
characteristics of probabilistic models, and challenges andevaluation issues in terms of applying probability-based
machine learning for real-world applications.

2

In this lecture, we discuss human-machine interaction andhuman-human interaction as examples of media processing
applications. Specifically, there are explanations of basic
methods such as modeling, design methods, evaluation
methods, and machine learning, as well as information
retrieval, reading comprehension, large-scale processing, andsecurity. *Students are required to have taken the course"Fundamentals of Media Processing" before taking thiscourse.

40INF039**

40INF040**

40INF041**

40INF042**

40INF043**

Sublinear Algorithms

Algorithmic Market Design

Combinatorial Optimization for Machine
Learning

Probabilistic Models in Informatics

Interactive Media

6.情報学コース
Informatics
Course Code40INF044**

40INF045**

40INF046**

40INF047**

80INF001**

CourseKnowledge Sharing System

Computational Social Science

Embedded Real-Time Systems

Quantum Algorithms

Experiment and Seminar on Basic
Knowledge in Informatics ⅠA

CreditContent of Subject

2This lecture will discuss the realization of knowledge sharing
through knowledge representation techniques, a branch ofartificial intelligence. First, the history of information sharing
in society will be introduced by reviewing the development of
the Internet to date. Then, the importance of the Semantic
Web concept in the transition from information sharing toknowledge sharing will be explicated. The lecture will focus on
how knowledge sharing on the Internet can be done with theSemantic Web. First, an overview of the Semantic Web will bepresented,

2Computational social science is the study of quantitative andtheoretical understanding of human behavior and economic,social, and political phenomena by capturing, analyzing, andmodeling large-scale economic, social, and political data
through information technology. In this course, students willlearn basic concepts of social science, applications ofinformation technology, and social scientific interpretation,
which are necessary for researchers in information scienceto tackle questions in social science. *Not open to students
who have earned credits in "Econophysics" by FY2020.

2Real-time and embedded systems pervade many aspects ofmodern life ranging from mobile communications, robotics,
medical systems and devices, motion control systems,
transportation systems, energy generation and management,
to aerospace and aircraft systems. This course covers boththe core concepts underlying such systems and applicationlevel concepts. First, the course focuses on the core
concepts and principles, including resource management, taskscheduling, dependability and system safety. Also, the course
offers the application-level discussions for Cyber-Physical
Systems (CPS) and Internet-of-Things (IoT), and real-time
networks.

2This lecture covers the basics of quantum algorithms andtheir implementation, extending to the physical aspects of theimplementation. The lectures are structured into input andoutput sections. During the input sections, students will learn
relevant contents through video materials registered at theQantum Academy of Science and Technology Online Learning
System (QOLS). During the output sections, they will prepare
presentations based on these contents. The students willpresent in front of their peers, followed by a discussion
involving both the students and the lecturer.

2Under the close guidance of the faculty advisor, students willplan and conduct experiments, analyze the results ofexperiments, and conduct exercises to acquire the basic
knowledge required for conducting research in informatics
and the advanced knowledge needed to solve fundamental
problems in informatics.

6.情報学コース
Informatics
Course Code80INF002**

80INF003**

CourseExperiment and Seminar on Basic
Knowledge in Informatics ⅠB

Experiment and Seminar on BasicKnowledge in Informatics ⅡA

CreditContent of Subject

2

Under the close guidance of the faculty advisor, students willplan and conduct experiments, analyze the results ofexperiments, and conduct exercises to acquire the basic
knowledge required for conducting research in informatics
and the advanced knowledge needed to solve fundamental
problems in informatics.

2

Under the close guidance of the faculty advisor, students willplan and conduct experiments, analyze the results ofexperiments, and conduct exercises to acquire the basic
knowledge required for conducting research in informatics
and the advanced knowledge needed to solve fundamental
problems in informatics.

80INF004**

Experiment and Seminar on Basic
Knowledge in Informatics ⅡB

2Under the close guidance of the advisor, students will acquire
the basic and advanced knowledge necessary for conducting
research in informatics, and will plan and conduct
experiments, analyze the results of experiments, and practice
exercises in order to achieve a level at which they cansummarize their progress and report on their research.

90DIFg18**

Research in Informatics for Master
Thesis ⅡB

2Registration possible only by the students enrolled in
SOKENDAI in/before AY2022