dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: Introduction to Time Series
Modules:
Course Overview, Instructor Introduction, Module 1 Introduction, What are Time Series, and How are They Used?, Getting Started with R, A Gentle Introduction to Stationarity - Part 1, A Gentle Introduction to Stationarity - Part 2, A Gentle Introduction to Stationarity - Part 3
Module 2 Introduction, Weak and Strong Stationarity - Part 1, Weak and Strong Stationarity - Part 2, Weak and Strong Stationarity - Part 3, Weak and Strong Stationarity - Part 4, Introduction to Linear Processes - Part 1, Introduction to Linear Processes - Part 2, Introduction to Linear Processes - Part 3, Introduction to Linear Processes - Part 4
Module 3 Introduction, Understanding ARMA (p, q) Processes - Part 1, Understanding ARMA (p, q) Processes - Part 2, Understanding ARMA (p, q) Processes - Part 3, Understanding ARMA (p, q) Processes - Part 4, Computing ACF's of AR (2) Processes Using Difference Equations - Part 1, Computing ACF's of AR (2) Processes Using Difference Equations - Part 2, Computing ACF's of AR (2) Processes Using Difference Equations - Part 3, Computing ACF's of AR (2) Processes Using Difference Equations - Part 4, Computing ACF's of AR (2) Processes Using Difference Equations - Part 5
Module 4 Introduction, ACF's and Difference Equations - Part 1, ACF's and Difference Equations - Part 2, ACF's and Difference Equations - Part 3, ACF's and Difference Equations - Part 3 (Cont.), Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 1, Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 2, Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 2 (Cont.), Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 3
Module 5 Introduction, The Sample ACF and Sample PACF - Part 1, The Sample ACF and Sample PACF - Part 2, Preliminary Estimation and the Yule-Walker Equations - Part 1, Preliminary Estimation and the Yule-Walker Equations - Part 1 (Cont.), Maximum Likelihood Estimators for ARMA Processes - Part 1, Maximum Likelihood Estimators for ARMA Processes - Part 2, Maximum Likelihood Estimators for ARMA Processes - Part 3, Maximum Likelihood Estimators for ARMA Processes - Part 4
Module 6 Introduction, Model Diagnostics - Part 1, Model Diagnostics - Part 2, Model Diagnostics - Part 3, Order Selection and the AICC - Part 1, Order Selection and the AICC - Part 2, Order Selection and the AICC - Part 3
Module 7 Introduction, ARIMA Models - Part 1, ARIMA Models - Part 1 (Cont.), ARIMA Models - Part 2, ARIMA Models - Part 2 (Cont.), ARIMA Models - Part 3, ARIMA Models - Part 4, SARIMA Models - Part 1, SARIMA Models - Part 2
Module 8 Introduction, Beyond One-Step-Ahead Prediction - Part 1, Beyond One-Step-Ahead Prediction - Part 1 (Cont.), Beyond One-Step-Ahead Prediction - Part 2, Beyond One-Step-Ahead Prediction - Part 3, Beyond One-Step-Ahead Prediction - Part 3 (Cont.), Beyond One-Step-Ahead Prediction - Part 4, Exponential Smoothing - Part 1, Exponential Smoothing - Part 2
Course Summative Assessment
Course: Severe to Profound Intellectual Disability: Circles of Care and Education
Modules:
Introduction to the course, Introduction to week 1, Understanding intellectual disability, Understanding the impact of intellectual disability, Context of intellectual disability, Understanding learning in intellectual disability, Asserting the right to education (Part 1), Facilitating learning as a caregiver, Week 1 conclusion
Introduction to week 2, Lifelong learning, How learning takes place, Attitudes to learning, Facilitating learning, Communication - why is it so important, Strategies to facilitate communication, Learning context, TEDI Research: Lifelong learning, Week 2 conclusion
Introduction to week 3, Support needs: An overview, Support needs: A caregiver's perspective, Developing a learning programme, Planning daily programmes with structure and routine, Engaging the child in learning, Working with children in groups, Learning opportunities: A caregiver's  perspective, Building relationships of care and education, Being part of a team: A mother's perspective, Week 3 conclusion
Introduction to week 4, Listening to children and developing their voice, Ethics of care: Receiving and giving, Developing an ethics of care: A parent's perspective, Caring for the caregiver, TEDI research: Experience of caregivers, Voice of inclusion, Week 4 conclusion
Course: Getting Started with CyberGIS
Modules:
Welcome to Getting Started with CyberGIS!
Geographic Information Science and Systems, Cyberinfrastructure, CyberGIS, Geospatial Big Data, Geospatial Data Science, Scientific Applications and Drivers
Plotting with Matplotlib, Mapping with Cartopy, Mapping with Basemap, Web Mapping with Mplleaflet and Folium, Geopandas Plotting Geometries and Spatial Operations
Vector Operations with Shapely, Raster Manipulation with Raster.io, Introduction to Hadoop, Hadoop Distributed File System and Map Reduce Paradigm, Hadoop Streaming API
Theoretical Foundations, Applications and Case Studies, Future Trends, Where Do We Go From Here?
Course: Art & Ideas: Teaching with Themes
Modules:
Introduction to Art & Ideas, How to Teach with Themes
Places & Spaces, Teaching with Themes: Places & Spaces, Piet Mondrian. Broadway Boogie Woogie. 1942–43, Martin Wong. Stanton near Forsyth Street. 1983, Zarina. Home is a Foreign Place. 1999, Claude Monet. Water Lilies. 1914-26, Andrew Wyeth. Christina's World. 1948, Emeka Ogboh. Lagos State of Mind. 2017/2020, Gordon Matta-Clark. Bingo. 1974, Teddy Cruz, Fonna Forman. Manufactured Sites: A Housing Urbanism Made of Waste/Maquiladora, project (Model: 2005). 2005-08
Art & Identity, Teaching with Themes: Art & Identity, Henri Matisse. The Red Studio. 1911, Frida Kahlo. Self-Portrait with Cropped Hair. 1940, Gilbert Baker. Rainbow Flag. 1978, Catherine Opie. Being and Having. 1991, Rineke Dijkstra. Almerisa series. 1994–2008, Lorna Simpson. Wigs (Portfolio). 1994, Kay WalkingStick. You’re an Indian? 1995, Amira Virgil. The Melanin Pack for The Sims 4. 2016
Transforming Everyday Objects, Teaching With Themes: Transforming Everyday Objects, Ruth Asawa. Untitled (BMC. 145, BMC Laundry Stamp). C. 1948-49, Robert Rauschenberg. Bed. 1955, Alfonso Ossorio. Empty Chair or The Last Colonial. 1969, Doris Salcedo. Atrabilious. 1992–93, Diamond Stingily. Entryways. 2021, Clara Porset. Butaque Chair. C. 1957, Tomás Gabzdil Libertiny. The Honeycomb Vase “Made by Bees” (Prototype). 2006, Jessica Rosenkrantz, Jesse Louis-Rosenberg. Kinematics Dress. 2013
Art & Society, Teaching with Themes: Art & Society, Dorothea Lange. Migrant Mother. 1936, Jacob Lawrence. Migration Series. 1940–41, Carolina Caycedo. Spirals for Shared Dreams. 2022, Ernest Cole. Untitled. C. 1960, Martha Rosler. House Beautiful (Bringing the War Home). 1967-72, Hanes, Inc. White T-Shirt. 1910s, Faith Ringgold. American People Series #20: Die. 1967, Shahzia Sikander. Candied. 2003
Optional Prompts for Discussion & Reflection, End-of-course survey, CTLE for New York State educators, MoMA Resources, Virtual Event Recordings, Tips for Teaching Remotely
Course: Corruption
Modules:
1.1 Introduction, 1.2 What is Corruption?, 1.3 How Much Corruption?, 1.4 How Did Corruption Spread?
2.1 Societal Level Effects, 2.2 Decision Makers, 2.3 Corruption and Trust, 2.4 Corruption Hurts
3.1 Time and Money, 3.2 Relationships, 3.3 Indirect Costs, 3.4 Sanctions
4.1 Theories of Control, 4.2 Control by Firms, 4.3 Control by Industries, 4.4 Control by Polities
Course: Muestreo de personas, redes y registros
Modules:
1.0 Introducción al curso, 1.1 Diseño de la investigación y muestreo. Parte 1, 1.1 Diseño de la investigación y muestreo. Parte 2, 1.2 Encuestas y muestreo, 1.3 ¿Por qué tomar muestras? Parte 1, 1.3 ¿Por qué tomar muestras? Parte 2, 1.4 ¿Por qué deberíamos aleatorizar y cómo podríamos hacerlo?, 1.5 ¿Qué ocurre cuando aleatorizamos?, 1.6 ¿Cómo se evalúa la calidad de una muestra?, 1.7 ¿Qué tipo de cosas podemos muestrear?
2.1 Muestreo aleatorio simple (SRS), 2.2 Mera aleatorización: Una breve historia, 2.3 La distribución de muestreo SRS. Parte 1, 2.3 La distribución de muestreo SRS. Parte 2, 2.4 Tamaño de la muestra, 2.5 Margen de error, 2.6 Tamaño de la muestra y de la población
3.1 Muestreo complejo simple. Elección conglomerados enteros. Parte 1, 3.1 Muestreo complejo simple. Elección de conglomerados enteros. Parte 2, 3.2 Efectos de diseño y correlación intraclase. Parte 1, 3.2 Efectos de diseño y correlación intraclase. Parte 2, 3.3 Muestreo en dos etapas, 3.4 Diseño del muestreo en dos etapas. Parte 1, 3.4 Diseño del muestreo en dos etapas. Parte 2, 3.5 Enfrentarse al mundo real. Conglomerados de distinto tamaño. Parte 1, 3.5 Enfrentarse al mundo real. Conglomerados de distinto tamaño. Parte 2, 3.6 Fracción de muestreo
4.1 Formación de grupos, 4.2 Varianza de muestreo, 4.3 Más sobre la agrupación, 4.4 Asignar la muestra, 4.5 Otras asignaciones, 4.6 Ponderaciones para combinar a través de los estratos
5.1 Selección sistemática, 5.2 Intervalos con fracciones. Parte 1, 5.2 Intervalos con fracciones. Parte 2, 5.3 Orden de la lista, 5.4 Estimación de la incertidumbre
6.1 Software estadístico para la selección de muestras, 6.2 Muestreo estratificado multietapa, 6.3 Ponderaciones para el sobremuestreo y submuestreo, 6.4 Ponderación de la falta de respuesta y de la falta de cobertura, 6.5  Muestrear redes: ponderación de la multiplicidad, 6.6 Muestreo no probabilístico
Course: Étudier en France: French Intermediate course B1-B2
Modules:
Introduction
Présentation de la semaine 1, Arriver dans une ville étrangère : extrait de "L'Auberge Espagnole", L’arrivée en France…. Premières impressions…., Le passé composé, Le participe passé et ses accords, Les étudiants et le voyage, Les étudiants et l'expatriation, Les mots de la semaine : locomotive /cliché /intégration, Le son /e/ de "fée" et le son /ɛ/ de "fait", Les clichés sur les Français ... et les autres
Présentation de la semaine 2, "L'attrait de la France"extrait de journal télévisé, "Le logement étudiant", extrait de journal télévisé, Paris vu par.... des étudiants étrangers, L'imparfait, Le plus-que-parfait, Les étudiants et le logement, Entraînez-vous! Questions-vidéos: "Etudiants à la recherche d'un logement", Les mots de la semaine : louer/ location/ locataire, Le son /ʁ/ de "grand"
Présentation de la semaine 3, Extrait du film "L'auberge Espagnole": Vive la bureaucratie!, Semaine de pré-rentrée à la faculté des sciences de Montpellier, Les prépositions 1, Les prépositions 2, L'éducation et l'enseignement supérieur, Les mots de semaine : bureaucrate/bureaucratie, Les nasales /ɛ̃/ /ɑ̃/ /ɔ̃/ de "frein/franc/front", Augmentation des droits d'inscription
Présentation de la semaine 4, Extrait d'un cours de philosophie: prendre des notes, L'emploi des modes indicatif, subjonctif, infinitif (1ère partie), L'emploi des modes indicatif, subjonctif, infinitif (2ème partie), Les cours et l'évaluation, L'exposé oral, Les mots de la semaine : amphithéâtre/ sécher un cours, Cours d'introduction à l'histoire de la pensée économique, juridique et politique, Prononciation: "pont"/"bon" et "rue"/"roue"
Présentation de la semaine 5, Vie quotidienne: ouvrir un compte bancaire et s'assurer, Extrait du film "Bienvenue chez les Ch'tis", Les pronoms 1, Connaissez-vous la France?, Les mots de la semaine : muter/ alexandrin, Prononciation: le /s/ de "poisson" et le /z/ de "poison"
Présentation de la semaine 6, Le monde est un campus : portrait d'une étudiante, Extrait: Les médecins vus par Norman, Les pronoms 2, Vie quotidienne : la santé, Vie quotidienne : la gastronomie française, Les mots de la semaine : patient/ ordonnance, La prononciation des finales et les liaisons
Course: Methods for Quantitative Research in Psychology
Modules:
Get Started With PsycLearn Essentials!, Metacognitive Checkpoints: Pause and Reflect on Your Learning
Welcome
Eight Steps, The Scientific Literature, Asking Research Questions
Recognizing Variables, Measuring Variables, Measurement Error
Exploring Research Designs, Using Descriptive Research Methods, Using Correlational Research Methods, Using Experimental Research Methods, Using Quasi-Experimental Research Methods
Construct Validity, Internal Validity, External Validity
Key Takeaways, Key Vocabulary, Course References
Closing Remarks
Introduction to APA Resources, Student Resources, APA Style®, Research, and Writing, Students from Diverse Ethnic, Cultural, and Economic Backgrounds, Psychology Help Center, Psychology Careers, Careers and Internships at APA, Other APA Resources
Course: The Science of Well-Being
Modules:
Start a New Journey!, Become Happier by Learning & Applying Psychological Science, Why This Course Exists, What is the G.I. Joe Fallacy?, Watch out for scams
Savoring, Gratitude, Part 1 - Good Job, Part 2 - Money, Part 3 - Awesome Stuff, True Love, Perfect Body & Good Grades, Annoying Features of the Mind, Question & Answer
Kindness, Social Connection, Annoying Feature #1, Annoying Feature #2, Annoying Feature #3, Annoying Feature #4, Annoying Features Summary, Question & Answer
Exercise, Sleep, Part 1 - Rethink "Awesome Stuff", Part 2 - Thwart Hedonic Adaptation, Part 3 - Reset Your Reference Points, Overcome Biases Summary, Question & Answer
Meditation, Good Job, Good Grades, Kindness, Interview with Elizabeth Dunn, Social Connection, Interview with Nicholas Epley, Time Affluence, Mind Control, Healthy Practices, Question & Answer
Part 1 - Situation Support, Part 2 - Goal Setting, Interview with Gabriele Oettingen, Question & Answer, Recap
Welcome to Your Final Rewirement Challenge
Welcome to Week 2
Welcome to Week 3
Welcome to Week 4, Congratulations on Completing Your Challenge!, Students Discuss Their Rewirement Challenges, Conclusion
Course: Effective Programming in Scala
Modules:
Introduction, Elements of Programs, Types, Methods and Parameters, Conditions, Evaluating Definitions, Domain Modeling, Case Classes, Sealed Traits, Enumerations, Business Logic
First Steps With Lists, Functions, More Operations on Lists, Introducing Collections, Constructing Collections, Querying Collections, Transforming Collections, Sequences and Maps, Option, Collections Extra, Introducing Loops, More Loop Examples, Tail Recursion, “for” Syntax
Organize Code, Build Tools, Introduction to the sbt Build Tool, sbt, Keys, and Scopes, Program Entry Point, Encapsulation, Extending and Refining Classes, Case Classes vs Simple Classes, Opaque Types, Extension Methods
Reasoning About Code, Refactoring-Proof Programs, A Case for Side-Effects, Mutable Objects, Unit Testing, Property-Based Testing, Mocking, Integration Testing, Testing the Tests, Debugging Programs
Motivation, Context Parameters, Given Definitions, Priorities Between Given Definitions, Type Classes, Conditional Given Definitions, Type Classes and Extension Methods, Implicit Conversions
Error Handling, Error Handling with Try, Manipulating Try Values, Validating Data, Manipulating Validated Values, Combining Try and Either, Concurrent Programming, Operations on Type Future, Examples with Future, Execution Context
Course: 혁신을 위한 디자인 씽킹
Modules:
디자인 씽킹 소개, 디자인 씽킹이란 무엇인가? 전문가에게 들어봅시다, The Good Kitchen 사례, 비즈니스 모델 혁신, 디자인 씽킹에 가장 적합한 도전 과제, 시각화 도구
혁신의 물리학, George와 Geoff의 이야기, 여러분의 마인드는 준비되었습니까?, 스토리텔링 도구
아이디어 도출 과정, MeYouHealth 이야기 1부: 무엇인가?, MeYouHealth 이야기 2부: 만약에?, 마인드 매핑 도구
"무엇이 놀라움을 주는가?"와 "무엇이 실현되는가?", IBM 이야기, 학습 시작 툴, 강의 복습, 전략적 기회
최종 과제 개요
Course: Computational Social Science Methods
Modules:
What is this Specialization About?, Course Introduction, Optional: Study Suggestions (not required), Module 1 Introduction, The Digital Revolution, First Ever UC-wide Online Course, A Very Short History of Science, A Very Simplistic Hierarchy of Science, Social Emergence (Part 1), Social Emergence (Part 2), The Scientific Method Revisited, Limitations of Induction and Deduction, Glass of Red Wine Theorizing, Social Science Challenges
Introduction to Examples of CSS (Part 1), Overview of Big Data, Fighting Poverty with Data, Extracting Features, Predicting Poverty, Who Cares?, Webscraping Lab How-To
Introduction to Examples of CSS (Part 2), Overview of Artificial Intelligence (Part 1), Overview of Artificial Intelligence (Part 2), Machine Learning, Overfitting, Training, Validation, Testing, A Common Difficulty in ML
Introduction to Social Networks and Computer Simulations, Overview of Social Networks, Connected, From Obesity to Generosity, Get Your Friends Involved!, Overview of Computer Simulations, Models, Why Model?, Cultural Boundaries, Course Summary
Course: Introduction to User Experience Principles and Processes
Modules:
Welcome, What is User Experience?, The UX Process, Components of UX
UX Design Overview, Prototypes, Sketching, A Brief Incomplete History of UX
Visual Perception, Part 1, Visual Perception, Part 2, Memory, Part 1, Memory, Part 2
Seven Stages of Action, Gulfs of Execution and Evaluation, Design Principles
Heuristics for Design, #1 - Visibility of System Status, #2 - Match Between System and Real World, #3 - User Control and Freedom, #4 - Consistency and Standards, #5 - Error Prevention, #6 - Recognition Over Recall, #7 - Flexibility and Efficiency of Use, #8 - Aesthetic and Minimalist Design, #9 - Error Recovery, #10 - Help and Documentation
Heuristic Evaluation, Course Wrap-up, Next Steps, Basic Methods of UX Research, Interview - UX Designer Matt Martin, Interview With UX Researcher Lija Hogan
Course: Sustainable Development in the 21st Century with Ban Ki-moon
Modules:
Course Introduction, Copy of Course Introduction, Introduction, What is the 2030 Development Agenda?, From MDGs to SDGs, Who decided on the SDGs?, Behind-the-Scenes Negotiations, What are the 17 SDGs?, Key Characteristics of the SDGs, How to remember the SDGs: The 5 Ps, Summary
Introduction, What is Poverty? Part I, What is Poverty? Part II, Is Poverty Increasing or Decreasing?, Extreme Poverty, Interconnected Nature of Poverty, Call to Action: Eradicating Extreme Poverty, Poverty & Education Part I, Poverty & Education Part II, Poverty & Gender Equality, Case Study: Reforming Health Care in Bahrain Part I, Case Study: Reforming Health Care in Bahrain Part II, Summary
Introduction, Recycling is not an option, but a must!, Biodiversity, Ecosystem Services and Commoner's Laws of Ecology, Climate Change and its Global Effects, Climate Change and the Paris Agreement Part I, Climate Change and the Paris Agreement Part II, Climate Change: Mitigation, Climate Change: Adaptation, Summary
Introduction, Green Jobs, Green Buildings, Green Energy, Social Innovation and the SDG 2030 Agenda, Social Innovation and Sustainable Development, Social Innovation and Collective Impact, Summary
Introduction, Peace through Social Inclusion, Global Governance & Citizenship, Foundation & Values of SDGs, Partnerships for the Goals, Case Study: Civil Society Impact Part I, Case Study: Civil Society Impact Part II, Corporate Governance, Corporate Social Responsibility, Measuring Progress on Sustainable Development, Summary
Introduction, Role of the University for Civic Engagement, Education Case Study, Humanitarian and Environmental Agendas Part I: The Tensions, Humanitarian and Environmental Agendas Part II: Reconciliation, Citizen-Led Accountability Part I, Citizen-Led Accountability Part II, Lifelong Learning, Case Study: Lifelong Learning, World Bank: Empowering Young People, World Bank: Case Study Part I, World Bank: Case Study Part II, Summary
Final Project
Course: Build Better Generative Adversarial Networks (GANs)
Modules:
Welcome to Course 2, Welcome to Week 1, Evaluation, Comparing Images, Feature Extraction, Inception-v3 and Embeddings, Fréchet Inception Distance (FID), Inception Score, Sampling and Truncation, Precision and Recall
Welcome to Week 2, Disadvantages of GANs, Alternatives to GANs, Intro to Machine Bias, Defining Fairness, Ways Bias is Introduced
Welcome to Week 3, GAN Improvements, StyleGAN Overview, Progressive Growing, Noise Mapping Network, Adaptive Instance Normalization (AdaIN), Style and Stochastic Variation, Putting It All Together, Conclusion of Course 2
Course: Proyecto Final: Diseño y Gestión de Proyectos de Desarrollo
Modules:
1.1.1  Información importante del curso, 1.1.2 Conoce al equipo del curso, 1.2.1 Introducción al módulo, 1.2.4 Solución: Acta de Constitución del Proyecto
2.1.1 Introducción al módulo, Solución: Herramienta de gestión de tiempo, Solución: Herramienta de Gestión de Costos, Solución: herramienta de gestión de compras: matriz de adquisiciones, Solución: herramienta matriz RACI
3.1.1  Introducción al módulo, 3.1.3 Solución: Matriz de riesgos
4.1.1 Introducción al módulo, ¡Solicita tu insignia digital!, 4.2.2 Final del curso
Course: Stages of Incident Response
Modules:
Incident definitions and severity criteria, Identifying threats and vulnerabilities, Incident Response assets inventory and identification
Incident identification, Incident Response classification levels, Communication/notification of an incident, Identification tools and techniques
Scoping containment efforts, Determining status of infected/affected computing resources, Containment actions, Containment tools and techniques
Who, What, When, Where?, Investigation data sources, The role of Digital Forensics
What is eradication?, Cleanup and verification, Notification, Eradication tools and techniques
Returning to normal business processes, Service and System restoration, Certification and validation of Business Continuity, Recovery and restoration tools and techniques
Assessing the team and processes' effectiveness, Implementing improvements, Feedback from other teams in the organization
Course: Pensamiento de diseño para la innovación
Modules:
Introducción al pensamiento de diseño, ¿Qué es el pensamiento de diseño? Escuche a los expertos, La historia de The Good Kitchen, Innovación del modelo de negocio, Desafíos más adecuados para el pensamiento de diseño, Herramienta Visualización
La física de la innovación, The Story of George & Geoff, ¿Cuán preparada está su mente?, Herramienta Narración
El proceso de generación de ideas, La historia de MeYouHealth Parte I: ¿Qué es?, La historia de MeYouHealth Parte II: ¿Y si?, Herramienta Mapas mentales
¿Qué sorprende y qué funciona?, La historia de IBM, Herramienta Lanzamiento de aprendizaje, Revisión de nuestras lecciones, Oportunidades estratégicas
Visión general de la tarea final
Course: Answering Interesting Questions with Data
Modules:
Meet Dr. Barb Ericson, Welcome to the Course, How is This Course Different?, What is Python?, Why Work in Groups?, POGIL Roles, How to Write Code in the eBook, Reloading Your Code History, Welcome to the Week 1, Introduction to HTML, Fix HTML, The Document Object Model (DOM), Attributes, CSS Classes, Introduction to Beautiful Soup, How to read sections on Beautiful Soup, find vs find_all, View page source and inspect HTML page elements, Why use class_ with find or find_all?, Create a Soup object from a URL
Welcome to Week 2, What is XML?, XML terms, Parsing XML, Fixing XML, What is JSON?, XML vs JSON, Processing JSON, What is an API?, Free APIs, API Authorization, Get JSON data from an API, Using Params to Specify API Parameters
Welcome to Week 3, Why use a Database?, Intro to SQLite, How to Download DB Browser, Exploring a database with DB Browser, Introduction to SQL in DB Browser, Basic SQL Statements, Using Python to Execute SQL, More SELECT Keywords, Using Python to Select Data, Using Python for SQL Statements, Using fetchone and fetchall
Welcome to Week 4, Intro to Spidering Twitter, Code for spidering twitter, Code for multiple tables, Code with JOIN, Goals for Database Design, Intro to OMDB, Tables for OMDB, Types of keys and best practices, What is Matplotlib?, Why plot data?, Key Terms, Example Plots, Enhancements, Example Pie Chart, Plotting Michigan and Georgia data, Paired bars
Course: Health Informatics for Healthcare Professionals
Modules:
Module Introduction, The Patient Record, The Beginning of Cloud Computing, Cloud Computing from 1990s to Present Day, Data Science, Evolution of Leadership Roles, An Exciting Future for Health Informatics
Module Introduction, Data Standards: Content, Data Standards: Vocabulary & Transmission, The Creation of Data Standards
Era of Meaningful Use, Storing & Analyzing Data, The Importance of Natural Language Processing
Module Introduction, The Future of CDS, The Challenge of Creating CDS, Challenges with AI CDS Development, Making CDS Additive for Clinicians, Approaches to Data Control, The Creation of a Global Registry
Course: Fundamentals of Unity Android Game Development
Modules:
Installing and Setting Up Unity 2022
Create 3D Runner Game
Setting Up Game Level, Player, and Platform, Controlling the Ball, Moving the Ball after First Touch, Checking When the Ball Falls Off the Platform, Camera Following the Ball Smoothly, Make the Platforms Fall Down after Ball Goes Away, Spawning the Platforms, Random Platform Spawning Algorithm, Fixing Platform Falling, Creating Diamonds and Randomly Spawning Them, Destroying Diamonds in Collision, Creating Awesome particle Effects, Create UiManager and Text Animations, More Main Menu UI Animations, Game Over Menu and Animations, Scripting the UiManager, ScoreManager Score and HighScore, Creating GameManager and Controlling the Whole Game, Final Fixes and Finishing the Game, Building and Publishing to Android
Build a Simple 2D Android Game
Inkscape Crash Course, Creating Basic 3D Game Art Assets: Designing a Gradient Ball, Create Game Art: Designing Facial Features for a 3D Ball Character, Designing Second Tappy Ball Sprite, Designing the Pipe - Creating Game Art Assets, Designing Sky Clouds and Ground - Game Art Assets, Exporting Your Game Art Assets to Use Them in Game
Creating Tappy Ball Menu and UI, Programming the Ball Movement, Adding the Pipes, Spawning the Pipes, Checking Score, Designing UI and UiManager, Game Over Menu and Animations, Adding Attractive User Interface Elements, Creating Game Manager and Controlling Everything, Adding Final Tweaks and Finishing the Game
Build an Android Game Start to Finish in 40 Minutes
Course: Logging and Monitoring in Google Cloud - 日本語版
Modules:
コースの概要
モジュールの概要, Google Cloud のオブザーバビリティが必要な理由, Cloud Monitoring, Cloud Logging, エラー報告, アプリケーション パフォーマンス管理ツール, モジュールのまとめ
モジュールの概要, モニタリングの概要, Cloud Monitoring のアーキテクチャのパターン, 複数のプロジェクトをモニタリングする, データモデルとダッシュボード, 指標をクエリする, 稼働時間チェック, Coursera:  Google Cloud Platform と Qwiklabs を使用する, モジュールのまとめ
モジュールの概要, SLI、SLO、SLA, アラート戦略の策定, アラートの作成, Service Monitoring
モジュールの概要, Cloud Logging の概要とアーキテクチャ, ログのタイプと収集, ログの保存、ルーティング、エクスポート, ログのクエリと表示, ログベースの指標の使用, ログ分析, モジュールのまとめ
モジュールの概要, Cloud Audit Logs, データアクセス監査ログ, 監査ログエントリの形式, ベスト プラクティス, モジュールのまとめ
コースのまとめ
モジュール 1:  Google Cloud オペレーション スイートの紹介, モジュール 2:  重要なシステムのモニタリング, モジュール 3:  アラート ポリシー, モジュール 4:  高度なロギングと分析, モジュール 5:  監査ログの操作
Course: Successful Negotiation: Essential Strategies and Skills
Modules:
Course Goal and Game Plan, Introduction to the University of Michigan
Should I Negotiate?, A Position Based or Interest Based Negotiation, A Dispute Resolution or Deal Making Negotiation?, Analyzing the Negotiation, Your BATNA in a Dispute Resolution Negotiation, Using Decision Trees to Complete Your BATNA Analysis, Cross-Cultural Negotiations, How to Handle Ethical Issues, General Ethical Standards, Using Agents in Negotiations
Getting to Know the Other Side, Using Power in Negotiations, Introduction to Psychological Tools; Mythical Fixed Pie Assumption, Psychological Tools: Anchoring, Psychological Tools: Overconfidence, Psychological Tools: Framing, Psychological Tools: Availability, Psychological Tools: Escalation, Psychological Tools: Reciprocation, Contrast Principle, and Big Picture Perspective
Perspectives on Contracts, Sources of Contract Law, Creating Contracts: The Agreement, Creating Contracts: Consideration and Legality, Creating Contracts: Writing Requirements, Business vs. Legal Objectives in Contracting
Dispute Prevention, ADR Concepts, ADR Tools, Arbitration, Arbitration (Conclusion), Mediation, Mediation (Conclusion), Contract Performance Review and Evaluation
Introduction to Negotiation Exercise, Negotiation Debrief: Planning for Negotiation, Negotiation Debrief: Planning for Negotiation (Conclusion), Negotiation Debrief: Negotiation Tactics, Negotiation Debrief: Psychological Tools, Negotiation Debrief: Psychological Tools (Conclusion), Negotiation Debrief: Creating and Performing the Contract, Negotiation: Building a Larger Pie
Final Examination: Instructions and Honor Code, Some important reminders, Post-course Survey, Keep Learning with Michigan Online!
Course: A quick tour on Big Data and Business Intelligence
Modules:
Welcome!, Big Data: an introduction, The Five 'V' of Big Data, Distributed architecture
Hadoop Ecosystem, Hadoop and HDFS, Hadoop and Map-Reduce
Pig Latin, Apache Hive, Beyond Map Reduce
NO SQL, CAP Theorem, Artificial Intelligence
Course: Branching and Merging in Git
Modules:
Branch, Branching Operations, Create and Check Branch, Switch and Rename Branch, Track and Delete Branch, Check Difference between Branch, Push and Commit Changes, Types of Branches, Master Branch, Feature Branch, Release Branch, Hotfix Branch, Develop or Integration Branch, DEMO: Working with Git Branches, Git Merge, Merge Types, DEMO: Git Merging, Merge Conflict, DEMO: Git Merge Conflicts, Merging Strategies, Rebasing, DEMO: Git Rebasing
Visual Studio Code, Git with VSCode, VSCode with GitHub, DEMO: Visual Studio Code IDE, DEMO: Visual Studio Code Git Repositories, IntelliJ IDE, Git with IntelliJ IDE, DEMO: IntelliJ Installation, DEMO: IntelliJ Code Modification, Git with Eclipse IDE, DEMO: Eclipse Installation, DEMO: Eclipse Code Modification
Course: Getting There and Going Beyond
Modules:
Lesson 1 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 2 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, Transporter, The Future, Wrap Up
Lesson 3 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, Transporter, The Future, Wrap Up
Lesson 4 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, Transporter, The Future, Wrap Up
Lesson 5 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, Transporter, The Future, Wrap Up
Lesson 6 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 7 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 8 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 9 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, Transporter, The Future, Wrap Up
Lesson 10 Overview, Video Capsule Introduction, Video Capsule, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 11 Overview, Video Capsule Introduction, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Lesson 12 Overview, Video Capsule Introduction, Discussion Prompt, Your Path, Connections, Crew Questions, The Future, Wrap Up
Course: Six Sigma Principles
Modules:
What is Quality - Origins of Six Sigma - David Cook, Six Sigma Foundations and Principles, Purpose of Six Sigma, Six Sigma Methodology, Evolution of Six Sigma, Value of Six Sigma, Individual Contributors, Yellow and Green Belt, Roles and Responsibilities of Black Belts, Role of Master Black Belts, Role of Champions
Introduction to Quality Tools, Pareto Charts, Cause and Effect Diagrams, Flow Charts and Process Mapping, Checksheets, Scatter Diagrams, Histograms, Six Sigma Measure - pt1, Six Sigma Measure - pt2, Cost of Poor Quality
Importance of Teams, Types of Teams, Stages of Team Development, Brainstorming, Team Decision-Making, Agendas, Minutes, and Status Reports
Purpose of Lean, Value Stream Mapping, Interview: Real World Value Stream Mapping, JIT & KanBan, Poka Yoke, Value to the Organization
Course: Sales and CRM Overview
Modules:
Welcome to the Professional Certificate!, The Sales Operations Specialist Role, Welcome to the Course, Welcome to Week 1, Challenges Business Face, Who Uses Salesforce
Welcome to Week 2, B2C vs. B2B Sales: Differences and Similarities, Review of the Sales Process, Sales Process Examples
Welcome to Week 3, Databases and Data Hygiene
Welcome to Week 4, Salesforce Updates and Customization, Structure of a Resume, Resume Best Practices, Course Recap, Congratulations!
Course: Automation for Business
Modules:
Introduction to the Instructor, Overview of Automation Concepts, Benefits and Challenges of Business Automation, Identifying Automation Opportunities, Introduction to Automation Tools and Technologies, Planning Your Automation Strategy, Configuring Automation Workflows, Integration and Data Management, Overcoming Automation Challenges, Measuring Automation ROI, Continuous Improvement and Optimization, Selecting the Right Automation Tools, Innovation through Automation, Evaluating Automation Tool Options, Implementing Automation Solutions, Managing Change and Employee Training, Ensuring Compliance and Security, Emerging Trends in Business Automation: Generative AI, Emerging Trends in Business Automation: Robotic Process Automation, Emerging Trends in Business Automation: Out of the Box Solutions, Ethics and Responsibility in Automation: Strategies to overcome Ethical Issues, Ethics and Responsibility in Automation: Principles to Ethical AI, Preparing for the Future of Work
Course: Introducción a las humanidades digitales
Modules:
Introducción al curso, Introducción a la semana 1, Patricia Murrieta - humanidades espaciales, Stefania Gallini - historia ambiental, Miguel Escobar - teatro, Nuria Rodríguez - historia del arte, Gimena del Rio - filología, Antonio Rojas - edición académica digital
Introducción a la semana 2, Guía de buenas prácticas (Isabel Galina), Explicación del manual de buenas prácticas, Repaso de elementos básicos de los proyectos
Introducción a la semana 3, Voyant Tools para generar visualizaciones, Mapas en las humanidades digitales, ¿De qué están hechos los mapas?, Hagamos un mapa
Licencias Creative Commons, Explicación de las licencias CC, Licencias de derechos de autor, Licencias de dominio público, Despedida
Course: From Excel to Power BI
Modules:
Course Introduction and Objectives, Overview of Power BI, Lesson: Understand Power BI Licenses, Lesson: Understand Data Importation and the Table View, Overview of the Table View in Power BI, Import a File from Excel, Use Get Data to Connect to Data Sources, Try a Sample Dataset from Power BI Desktop, Lesson: Clean and Transform Data, Access the Power Query Editor, Overview of the Applied Steps List in Power Query Editor, Execute Basic Math Operations to a Column, Replace Errors in a Column, Lesson: Introduction to Data Modeling, Report View, and Visualizations, View Relationships in the Model View, Edit or Remove Relationships, Add a New Relationship Between Tables and Columns, Lesson: Understand the Report View, Overview of the Report View in Power BI, Add a Visualization, Overview of Format Features for Visualizations, Change the Visualization Type, Lesson: Understand Text Visualization Types, Create a Visualization Card, Create a Table Visualization, Create a KPI Chart, Create a Key Influencers Chart, Lesson: Intro to Chart Visualizations, Create a Scatter Chart, Create a Waterfall Chart, Create a Funnel Chart, Create a Ribbon Chart, Lesson: Filters, Slicers, and Data Drilling, Create a Slicer, Analyze Your Visualization, Drill Down and Drill Up in a Visualization, Lesson: Introduction to Power BI Service, Publish a Dataset or Report, View My Workspace in the Power BI Service, View Workspaces in the Power BI Service, Overview of Dashboards, Create a New Dashboard, Add a Tile to a Dashboard, Pin a Tile from a Report, Subscribe to a Power BI Dashboard, Share a Report Via Email, Share a Report To a Teams Channel, Export a Report to PowerPoint
Course: Training and Learning Programs for Volunteer Community Health Workers
Modules:
Welcome Video, Lecture 1A: Principles of Learning, Part 1, Lecture 1B: Principles of Learning, Part 2, Lecture 1C: Adult Education Approaches, Lecture 2A: Overview, Lecture 2B: Approaching the Health Service, Lecture 2C: Approaching the Community, Lecture 2D: Approaching the Community: Gaining Support for Volunteer Efforts
Lecture 3A: What Information Is Needed?, Lecture 3B: Documents and Interviews, Lecture 3C: Observation of Performance, Lecture 3D: Training Needs to Deliver a Basic Package of Services, Lecture 4A: Content and Objectives, Lecture 4B: SMART Objectives
Lecture 5A: A Variety of Methods, Lecture 5B: Sample Methods for Learning about Educating Villagers, Lecture 5C: Sample Methods for Learning about a Census, Lecture 6A: Training Logistics, Lecture 6B: Matching Materials with Methods, Lecture 6C: Developing and Using Educational Materials/Aids, Lecture 6D: A Simple Training Guide
Lecture 7A: What is Monitoring?, Lecture 7B: Monitoring Content and Process, Lecture 8A: Sample Community Volunteer Session on Malaria Case Management, Lecture 8B: Sample Community Volunteer Session on Malaria Case Management, Lecture 8C: Sample Community Volunteer Session on Malaria Case Management
Lecture 9A: Overview and Definitions of Evaluation, Lecture 9B: Pre- and Post-Tests, Lecture 9C: Observation, Feedback, and Analysis, Lecture 10A: Monitoring and Measuring Performance, Lecture 10B: Realities Back on the Job, Lecture 10C: Supervision Functions and Eﬀectiveness, Lecture 10D: Overcoming Supervisory Challenges, Lecture 10E: Continuing Education Revisited
Wrap-up Video
Course: Game Design and Development 2: 2D Platformer
Modules:
Course Overview, Project Overview, Creating a New Unity Project, Getting the New Input System, Importing the Asset Package, Tilemaps - Tile Palette and Tiles, Tilemaps - Rules Tiles, Tilemaps - Animated Tiles, Tilemaps - Combining Rules and Animation, Player Setup - Physics, Player Setup - Input System, Player Setup - Animations and the Animator, Player Setup - Camera and Visual Effects, Canvases and User Interface, Level Setup - Using the Provided Prefabs, Level Setup - More Tilemaps, Level Setup - Adding More Levels, Scripting and Using Visual Studio, Finish the Project, 2D Platformer Modification Examples
Game World - Part 1: Introduction, Game World - Part 2: Components, Game World - Part 3: Designing the Game World, Game World - Part 4: Designing the Game World (cont.), Game World - Part 5: Designing the Game World (cont.), Storytelling - Part 1: Introduction, Storytelling - Part 2: Characters, Making of Uncharted Characters Documentary, Storytelling - Part 3: Character Design, Storytelling - Part 4: Setting and Plot, Storytelling - Part 5: Interactive Stories
Gameplay - Part 1: Introduction, Gameplay - Part 2: Decomposing Gameplay, Gameplay - Part 3: Decomposing Gameplay (cont.), Gameplay - Part 4: Game Genres, User Experience - Part 1: Introduction, User Experience - Part 2: Inputs, User Experience - Part 3: Outputs, User Experience - Part 4: Designing with UX
Game Technology - Part 1: Introduction, Game Technology - Part 2: A Brief History, Game Technology - Part 3: A Brief History (cont.), Game Technology - Part 4: Hardware, Game Technology - Part 5: Hardware (cont.), Game Technology - Part 6: Software, Game Technology - Part 7: Environments, Course Wrap Up
Course: Test-Driven Development Project: Random Person Generator
Modules:
Course Introduction
Course: Agile Scrum Master Certification Exam Prep (CSM)
Modules:
Course introduction, Introduction to Scrum Master Certified
Agile History, Project Management, Agile Manifesto Principles, Agile Manifesto Principles Continue
Scrum Principles, Empirical Process Control, Self-Organization, Collaboration, Value-Based Prioritization, Timeboxing, Iterative Development
Scrum Versus Project Management, Scrum Versus Project Management Continue, Benefits of Using Scrum, Benefits of Using Scrum Continue, Scrum Phases, Initiate Phase, Plan and Estimate Phase, Implement Phase, Review and Retrospect Phase, Release Phase, Agile Methods, Scrum History
Scrum Aspects Introduction, Roles in Scrum, Identify the Scrum Master, Scrum Master Responsibilities, Scrum Master Responsibilities Continue, Scrum Master Authority, Identify the Product Owner, Product Owner Responsibilities, Product Owner Authorities, Scrum-Development Team, Business Justification, Quality, Change, How Risk Effects the Scrum Process, How Risk Effects the Scrum Process Continue
How Sprint Starts the Scrum Process, Important Tasks for Sprint, What Is Sprint Timebox, Sprint Planning Can Begin Early, Follow Proper Sprint Process, What Is Sprint Backlog
Introduction to Scrum Artifacts, Designing the Product Backlog, How Are Product Backlog Items formed?, Fill Information Accordingly, How Daily Scrum Needs, Daily Scrum Meeting, Summary of Daily Scrum, Reviewing the Sprint, Scrum Master Helps Sprint Review, Scrum Standpoint, Sprint Retrospective, Purpose of the Sprint Retrospective, Summary of Sprint Retrospective, Monitoring Progress Toward Goals, Sprint Backlog, Monitoring Sprint Progress, Increment, Definition of Done
Introduction to Scrum Values, Follow Commitment, Scrum Process, Scrum Process Continue, Scrum Values-Focus, Openness, Respect, Scrum Overall Process, Scrum Overall Process Continue, Scrum Master Summary, Scrum Master Summary Continued
Course: Recommender Systems: An Applied Approach using Deep Learning
Modules:
About the Instructor, Course Outline
Module Introduction, Overview, Deep Learning in Recommender Systems, Inference after Training, Inference Mechanism, Embeddings and User Context, Neural Collaborative Filtering, VAE Collaborative Filtering, Strengths and Weaknesses of DL Models, Deep Learning Quiz, Deep Learning Quiz Solution
Module Overview, TensorFlow Recommenders, Two-Tower Model, Project Overview, Download Libraries, Data Visualization with WordCloud, Make Tensors from DataFrame, Rating Our Data, Random Train-Test Split, Making the Model and Query Tower, Candidate Tower and Retrieval System, Compute Loss, Train and Validation, Accuracy Versus Recommendations, Making Recommendations
Course: How to Get Into Cloud Computing
Modules:
Welcome to the course, What is cloud computing?, Breakthroughs and benefits of cloud computing
Career advice from Mark from Amazon Web Services (AWS), Career advice from David from T5 Digital, Essential technical skills for a career in cloud computing, Course summary
Course: Social and Economic Networks:  Models and Analysis
Modules:
An Introduction to the Course, 1.1: Introduction, 1.2: Examples and Challenges, 1.2.5 Background Definitions and Notation (Basic - Skip if familiar  8:23), 1.3: Definitions and Notation, 1.4: Diameter, 1.5: Diameter and Trees, 1.6: Diameters of Random Graphs (Optional/Advanced 11:12), 1.7: Diameters in the World, 1.8: Degree Distributions, 1.9: Clustering, 1.10: Week 1 Wrap
2.1: Homophily, 2.2: Dynamics and Tie Strength, 2.3: Centrality Measures, 2.4: Centrality – Eigenvector Measures, 2.5a: Application - Centrality Measures, 2.5b: Application – Diffusion Centrality, 2.6: Random Networks, 2.7: Random Networks - Thresholds and Phase Transitions, 2.8: A Threshold Theorem (optional/advanced 13:00), 2.9: A Small World Model, 2.10 Week 2 Wrap
3.1: Growing Random Networks, 3.2: Mean Field Approximations, 3.3: Preferential Attachment, 3.4: Hybrid Models, 3.5: Fitting Hybrid Models, 3.6: Block Models, 3.7: ERGMs, 3.8: Estimating ERGMs, 3.9: SERGMs, 3.10: SUGMs, 3.11: Estimating SUGMs (Optional/Advanced 21:03), 3.12: Week 3 Wrap
4.1: Strategic Network Formation, 4.2: Pairwise Stability and Efficiency, 4.3: Connections Model, 4.4: Efficiency in the Connections Model (Optional/Advanced 12:41), 4.5: Pairwise Stability in the Connections Model, 4.6:  Externalities and the Coauthor Model, 4.7: Network Formation and Transfers, 4.8: Heterogeneity in Strategic Models, 4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47), 4.10: Pairwise Nash Stability (Optional/Advanced 11:34), 4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57), 4.12: Evolution and Stochastics (Optinoal/Advanced 16:05), 4.13: Directed Network Formation (Optional/Advanced 16:38), 4.14: Application Structural Model (Optional/Advanced 35:06), 4.15: Week 4 Wrap
5.1: Diffusion, 5.2: Bass Model, 5.3: Diffusion on Random Networks, 5.4: Giant Component Poisson Case, 5.5: SIS Model, 5.6: Solving the SIS Model, 5.7: Solving the SIS Model - Ordering (Optional/Advanced 24:16), 5.8a: Fitting a Diffusion Model to Data (Optional/Advanced 22:47), 5.8b: Application:  Financial Contagions (Optional/Advanced 12:47), 5.8c: Application: Financial Contagions - Simulations (Optional/Advanced 13:41), 5.9: Diffusion Summary, 5.10: Week 5 Wrap
6.1: Learning, 6.2: DeGroot Model, 6.3: Convergence in DeGroot Model, 6.4: Proof of Convergence Theorem (Optional/Advanced 10:25), 6.5: Influence, 6.6: Examples of Influence, 6.7: Information Aggregation, 6.8: Learning Summary, 6.9: Week 6 Wrap
7.1: Games on Networks, 7.2: Complements and Substitutes, 7.3: Properties of Equilibria, 7.4: Multiple Equilibria, 7.5: An Application, 7.6: Beyond 0-1 Choices, 7.7: A Linear Quadratic Model, 7.8: RepeatedGames and Networks, 7.9: Week 7 Wrap, 7.9b: Course Wrap
Final
Course: 离散数学概论 Discrete Mathematics Generality
Modules:
01-课程介绍, 02-正式内容之前：形式化及其极限, 03-正式内容之前：悖论、版画、卡农, 04-数理逻辑介绍, 05-什么是命题, 06-排中律, 07-命题符号化, 08-逻辑联结词（上）, 09-逻辑联结词（下）, 10-命题公式, 11-真值函数, 12-命题形式化
13-重言式, 14-逻辑等价式和逻辑蕴涵式, 15-代入原理和替换原理, 16-证明逻辑等价式和逻辑蕴涵式, 17-范式及基本术语, 18-求范式的一般步骤, 19-主范式, 20-联结词集完备性, 21-形式系统和证明、演绎, 22-命题演算形式系统PC, 23-PC中的定理证明, 24-三个元定理, 25-定理判定问题
26-数理逻辑-个体、谓词和量词, 27-数理逻辑-谓词公式, 28-数理逻辑-谓词公式永真式, 29-数理逻辑-谓词演算形式系统FC, 30-数理逻辑-全称引入规则及存在消除规则, 31-数理逻辑-自然推理系统, 32-数理逻辑-ND中的定理证明
33-集合论与无限, 34-集合基本概念, 35-子集合, 36-集合基本运算, 37-集合族及运算, 38-归纳定义, 39-自然数的定义, 40-归纳原理, 41-数学归纳法
42-有序组, 43-笛卡尔积, 44-关系定义, 45-关系运算, 46-关系合成运算, 47-关系基本特性, 48-关系特性定理
49-等价关系, 50-等价关系与划分, 51-划分之间的关系, 52-划分运算, 53-序关系, 54-序关系中的特殊元素, 55-函数, 56-函数合成, 57-特殊函数类
58-图的定义, 59-图的基本概念, 60-度和正则图, 61-子图与同构图, 62-路径与连通性, 63-连通性, 64-欧拉图与哈密顿图
65-图的矩阵表示, 66-二分图, 67-二分图的匹配, 68-平面图, 69-树, 70-树的应用
71-引言, 72-代数结构, 73-幺元, 74-零元, 75-逆元, 76-可约元素, 77-同构与同态, 78-同余关系, 79-群环域
80-语言及研究方向, 81-形式语言, 82-短语结构语法, 83-语言及语法表示, 84-形式语法分类, 85-语法分析, 86-BNF范式, 87-语法图, 88-正则语法
89-有限状态机, 90-状态图, 91-泵引理, 92-机器同余, 93-商机器, 94-商机器的性质, 95-机器化简, 96-带输出的机器, 97-程序实现状态机
98-图灵机, 99-图灵机例子, 100-图灵机变种, 101-识别与判定, 102-哥德尔编码, 103-通用图灵机, 104-停机问题, 105-哥德尔不完备定理, 106-不可判定问题
期末考试
Course: Know Thyself - The Value and Limits of Self-Knowledge: The Unconscious
Modules:
About this course, Course assessments and exercises, Optional companion book
Meet Sigmund, Freud's Method, Meditative Moment, Inside the Unconscious, Freudian Slips, Dreams, Meditative Moment, Is a Cigar Ever Just a Cigar?, Left Behind?
Your mind on the defence, Defense mechanisms, Meditative Moment, A window into the child's mind, Introjecting, projecting, and gaslighting, Meditative Moment, The best defence, Summary
Strangers to Ourselves, Proprioception and other automatic marvels, A snowball on top of the iceberg?, Meditative Moment, Tests for the adaptive unconscious, The psychological immune system, Implicit bias, Durability bias, Meditative Moment, Conscious will, Decision making
Practical and theoretical rationality, The Ghastly Ordeal of Phineas Gage, Meditative Moment, Knows, but does not feel, Primary and secondary emotions, Somatic markers, How would that make you feel?, Somatic markers and the SEUT, Meditative Moment, Somatic markers gone awry, Descartes' errors?
Share what you've learned by editing the Wikipedia entry on self-knowledge!, A brief How-To, The Examined Life, Losing Oneself, Post-Course Survey
Course: AppSheet Administration
Modules:
Introducing AppSheet Administration
No-code apps and AppSheet use cases, Governance and rollout strategy
Setup tasks
Overview of policies and templates, Demo: Creating a policy in AppSheet
Share team data sources, Share sample apps and databases, Managing integrations
Demo: Export team audit logs to BigQuery
Topics review