dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: Introduction to Cataract Surgery
Modules:
01.01 - Preoperative Evaluation, 01.02 - Refractive goals, 01.03 - How to Choose an Intraocular Lens: Part 1, 01.04 - How to Choose an Intraocular Lens: Part 2, 01.05 - Perioperative Medications
02.01 - Surg-onomics, 02.02 - Anesthesia, 02.03 - Wound Construction, 02.04 - Viscoelastics, 02.05 - Capsulorhexis, 02.06 - Hydrodissection and Hydrodelineation
03.01 - Phacodynamics, 03.02 - Phacoemulsification Techniques: Divide & Conquer and Phaco Chop, 03.03 - Irrigation and Aspiration, 03.04 - IOL Materials and Design, 03.05 - Single Piece IOL loading and insertion, 03.06 - 3-Piece IOL Loading and Insertion, 03.07 - How to Insert an Anterior Chamber Lens Implant
04.01 - Capsule Complications, 04.02 - Conversion to Extracapsular Cataract Extraction, 04.03 - Capsular Tension Rings (13:07), 04.04 - Small Pupil (14:00), 04.05 - Astigmatism management in Cataract Surgery, 04.06 - Manual Small Incision Cataract Surgery
Course: The Discovery of the Higgs Boson
Modules:
Why is the Higgs Boson discovery important?, Collisions, Higgs decays and the discovery plot, Introduction, Newton's Law, Harmonic oscillator, Gravitational forces and potential, Spatial translation symmetry, Rotational symmetry and time translation symmetry, Particles and fields in classical mechanics
Maxwell's equations, Special relativity: from experiment to theory, Particles of light, Particle-wave duality, The hydrogen atom, The photoelectric effect, quantum mechanics & special relativity
Relativistic wave equations, Dirac's equation, Interactions of matter and light, Elementary processes in QED, Higher-order processes and applications, QED & symmetries, Renormalisation
The theory of strong interactions, The theory of weak interactions, Massless particles, Massive particles and bowl potentials, Superconductors and spontaneous symmetry breaking, Goldstone's theorem, The Higgs mechanism and the Higgs boson, Professor Boyle, in the Maxwell Building, with a copper pipe, QCD & strong interactions
The Higgs boson and the Standard Model, Higgs decay modes, The 1964 paper
Physics of Particle Colliders and early searches for the Higgs Boson, Searches at the LHC and the discovery of the Higgs boson, Higgs measurements and future colliders, Peter's commentary on the searches for the Higgs Boson, Bonus video: the experimental challenges, The Edinburgh group at the ATLAS experiment, The Edinburgh group at the LHCb experiment, Why is the sun burning so slowly?
L'imagination au pouvoir?, The hot Big Bang, Quantum vacuum & cosmology, The Higgs boson, scalar fields and inflation, Theories beyond the Standard Model, In conversation with John Ellis, Life at building 40, Behind the scenes footage
Course: How to Jumpstart Your Hidden Creative Genius
Modules:
About The Instructor, Course Overview, Just What Is Creativity?, Tying It All Together: Creativity, Imagination, Innovation And Other Terms, Learn About You, Unlearn It, Then Relearn Better, Your Creativity, How We All Had And Then Lost Our Creativity, TW: What Happens In Our Lives That Kills Our Creativity?, TW: Peers, TW: Caregivers, TW: Schools, TW: Self-Confidence and Creativity, No One Is as Wonderfully Unique as You, IDEO Founder David Kelly's TED talk: "How to Build Your Creative Confidence"
How to Reclaim Your Dormant Creativity, Get Your Curiosity On!, Push Your Comfort Zone, TW: Don’t Be Your Worst Critic, TW: Challenge Negative Assumptions, Smart Car Pong
How Your Corporate Culture Could Be Holding Back Innovation, Energize Your Organization with a Creative Culture
How Problem-Solving Methods Work, Wheelchairs And Snow: An Example Of A Problem Solved Badly, Then Properly, Creativity Venn Diagram & Why Constraints Are Good, Sneaking Past Your Brain’s Guard Post, What is Design Thinking?, Step 1: Empathy (a): Why Understanding The End-User Is Important:, Empathy (b): How To Empathize Properly, STEP 2: Define the Problem (a), Define the Problem (b): Identifying and Defining the Right Problem to Solve, Define the Problem (c): How to Write a Problem Statement Step by Step, Define the Problem (d): Ask a Good Question You'll Solve, Step 3: Ideate: Brainstorming GREAT Ideas, Steps 4 and 5: PROTOTYPE and TEST
Brainstorming Techniques, Overview of Brainstorming Techniques, Sorting Ideas With An Affinity Mapping Tool, The SCAMPER technique, Forced Association and Word Association, The Brainwriting Technique, The Freewriting technique, Final Wrap-Up, (Word Association technique example) Reeses Commercial, Invent A Field Game!, Overview Of Your Challenge, Word Association Brainstorming Technique
Course: Practical Python for AI Coding 1
Modules:
Objectives of this course, Concept of programming language, Introducing Python language, Installing Python with Anaconda distribution, Building AI coding environment : Explanation, Building AI coding environment : Demonstration
Installing JupyterLab, Using JupyterLab, Basic rules and concepts of Python, Data types, Clear, concise and compact coding
Getting familiar with Jupyter lab and notebook, Indentation, string and Boolean concepts, and triple quotes, Integers and floats, Type change and dynamic value assignment, Basic concept and use of if-clause
If...elif...else statement, More complex if-clause use cases, While-loop, for-loop, Augmented assignment and lazy evaluation, Use of break and continue in loops(maybe retake)
Basic rules of creating functions, Functions taking multiple inputs, Functions with default values and taking inputs of an arbitrary number, Reusing functions created and Using __name__=='__main__' syntax, Standard library and importing modules and libraries, Random number generation
Concept and slicing of lists, Concept of tuples and unpacking, Enumerate function and modifying lists, Sorting and searching elements, List comprehensions and two dimensional lists, Filter, lambda, map and zip functions
Introduction to dictionary, Dictionary iteration, Dictionary: Sorting and comprehension expressions, Word counting with dictionary, Concept and operations off sets
Course: Healthcare Analytics Essentials
Modules:
Meet your faculty: Martin Kohn
Why Do We Measure?, Positive and Negative Measures, Outcomes Measurement, Outcome Requirement Challenges, Outcomes Data Challenges, Outcomes Research, Outcomes that Matter, PROMS
Physician Evaluation, Process Review, Outcomes Performance Measures, Patient Surveys, Managing Physician Change, Incentives for Change Management, Nudging
Physician Burnout, Addressing Burnout, Addressing Physician Burnout and Standards of Reliability at Mayo Clinic, Peer Review Panels, Approaches for Change, HROs, HRO Errors
Course: Cloud Machine Learning Engineering and MLOps
Modules:
Instructor Introduction, Course Introduction, Lab Onboarding, Course 4 Project Overview, Introduction to Machine Learning Engineering, Machine Learning Engineering Overview, Machine Learning Engineering Architecture, Introduction to Machine Learning Microservices, Machine Learning Microservices Overview, Monolithic versus Microservice, Introduction to Continuous Delivery for Machine Learning, Continuous Delivery for Machine Learning Overview, What is Data Drift?, Continuously Deploy Flask ML Application, AWS App Runner:  High-Level PaaS Continuous Delivery
Introduction to AutoML, What is AutoML?, AutoML Computer Vision, Introduction to No Code/Low Code, No Code/Low Code AutoML: Part 1, No Code/Low Code AutoML: Part 2, Apple Create ML AutoML, Introduction to Ludwig AutoML, What is Ludwig AutoML?, Ludwig AutoML Deep Dive, Ludwig AutoML By Example, Introduction to Cloud AutoML, What is Cloud AutoML?, Cloud AutoML Deep Dive, Guest Speaker: Alfredo Deza, Introduction to Azure Machine Learning Studio, Create a Dataset in Azure Machine Learning Studio, Automated ML Run in Azure Machine Learning Studio, Experiments in Azure Machine Learning Studio, Deploy a Module in Azure Machine Learning Studio, Test Endpoints in Azure Machine Learning Studio
Introduction to MLOps, What is MLOps?, MLOps Deep Dive, Introduction to Edge Machine Learning, What is Edge Machine Learning?, Edge Machine Learning Vision in Action, Hardware Inference Model Solutions in Edge Machine Learning, Edge Machine Learning in Google, Edge Machine Learning in AWS, Introduction to AI APIs, How to Use AI APIs?, Core Components of a Cloud Application, AWS Comprehend for Natural Language Processing, AWS Rekognition for Computer Vision, GCP AutoML for Natural Language Processing, GCP AutoML for Computer Vision, Azure AutoML for AI Predictions, Azure AutoML for Computer Vision, Core Components of a Cloud Application Recap, Steps to Developing an API, Flask Machine Learning Backend, Checklist for Building Professional Web Services
Course: Gemini in Google Slides - Italiano
Modules:
Introduzione a Gemini in Presentazioni Google, Genera un'immagine con Gemini, Scegli uno stile per le tue immagini, Attività spiegata
Course: Ongoing U.S. Settler Colonialism & Native Peoples Teach-Out
Modules:
Meet Your Course Guide, Melissa
Hello, Settler Colonialism, Tribal Sovereignty and Settler Colonialism
The Enduring Presence of Native Peoples and Settler Colonialism’s Attempt to Eliminate, Aambe! (Let's go!) with Dr. Niiyokamigaabaw Deondre Smiles (Pt. 1), Settler Colonialism’s Eight Eliminatory Strategies (1-4), Settler Colonialism’s Eight Eliminatory Strategies (5-8), Aambe! (Let's go!) with Dr. Melissa Lewis (Pt. 1)
Land, Place, and Property, Aambe! (Let's Go!) with Dr. Autumn Asher BlackDeer (Pt. 1), Implications and Going Deeper, Aambe (Let's Go!) with Dr. Niiyokamigaabaw Deondre Smiles (Pt. 2)
Indigenous Relationships and Settler Colonial Anti-relationality, Aambe! (Let's go!) with Dr. Melissa Lewis (Pt. 2), Examples of Settler Colonial Anti-relationality, Aambe! (Let's Go!) with Dr. Joaquin Muñoz (Pt. 1)
Settler Colonialism’s Limited Options, Aambe! (Let's Go!) with Dr. Joaquin Muñoz (Pt. 2), Aambe! (Let's Go!) with Dr. Autumn Asher BlackDeer (Pt. 2), Extended Example of Limited Options
Mína Kaawaapamitiin! (See You Later!)
Course: Gestion de l’analyse des données
Modules:
Le sujet de ce cours, La répétition de l’analyse des données, Les phases de l’analyse des données, Les six types de questions, Les caractéristiques d’une bonne question, Objectifs et attentes de l’analyse exploratoire des données, Utiliser des modèles statistiques afin d’examiner vos données (partie 1), Utiliser des modèles statistiques afin d’examiner vos données (partie 2), Analyse exploratoire des données : Quand arrêter, Réaliser des inférences à partir des données : Introduction, Les populations se présentent sous de nombreuses formes différentes, Inférence : Ce qui peut ne pas bien se passer, Cadre général, Analyse associative, Analyses prédictives, Inférence ou Prédiction, Interpréter vos résultats, Communication régulière relative à l’analyse des données, Faire une présentation de l’analyse des données
Course: Introduction to Hearing Loss
Modules:
Welcome
Video for Module I
Video for Module II
Video for Module III
Video for Module IV
Course: رسوم متحركه ثنائية الأبعاد في Unity باستخدام Sprite Sheets
Modules:
Task 1, Task 2, Task 3, Task 4, Task 5, Task 6, Task 7
Course: Antibióticos ¿cuándo, cómo y para qué?
Modules:
Te damos la bienvenida, Presentación, ¿Por qué el uso inadecuado de antibióticos es un problema?, ¿Cuáles son los efectos en la salud pública del uso inadecuado de antibióticos?, ¿Qué son los antibióticos?, ¿Para qué sirven los antibióticos?, ¿Cómo nuestras prácticas cotidianas inadecuadas contribuyen a la resistencia bacteriana?, Cierre
Inicio semana 2, ¿Qué son las  bacterias?, Problemas de salud causados por bacterias en el pasado, Problemas de salud causados por bacterias en la actualidad, Transmisión de infecciones, Los antibióticos como fármacos, Cierre
Inicio semana 3, ¿Cómo se produce el fenómeno de la resistencia bacteriana?, ¿Para qué sirven los antibióticos y por qué es importante utilizarlos?, Mecanismo de acción de los antibióticos, Cierre
Inicio semana 4, ¿Cuáles son las acciones que podría hacer en mi vida cotidiana para reducir el riesgo de infecciones que requieran el uso de antibióticos?, ¿Cuáles podrían ser buenas prácticas del uso responsable  de antibióticos?, ¿Cómo las acciones individuales pueden contribuir con la solución del problema del uso excesivo de antibióticos?, Recomendaciones del uso responsable de antibióticos, Despedida
Course: Навыки Excel для бизнеса: Основы
Modules:
Неделя 1. Введение, Неделя 1. Обсуждение, Тренировочное видео: Овладение Excel, Тренировочное видео: Навигация и выбор, Тренировочное видео: Режимы просмотра, Тренировочное видео: Ввод данных, типы данных, редактирование и удаление, Тренировочное видео: Маркер заполнения, Неделя 1. Подведение итогов, Копирование и вставка, Шаблоны
Неделя 2. Введение, Неделя 2. Обсуждение, Тренировочное видео: Формулы, Тренировочное видео: Формулы в контексте, Тренировочное видео: Функции I: СУММ и АВТОСУММА, Тренировочное видео: Функции II: СРЗНАЧ, МИН и МАКС, Обсуждение: Абсолютные ссылки на ячейки, Тренировочное видео: Абсолютные ссылки на ячейки, Тренировочное видео: Перекрестные вычисления между листам, Неделя 2. Подведение итогов, Параметры Excel
Неделя 3. Введение, Неделя 3. Обсуждение, Тренировочное видео: Форматирование, Тренировочное видео: Границы, Тренировочное видео: Инструменты выравнивания, Тренировочное видео: Формат по образцу, Тренировочное видео: Форматы чисел, Тренировочное видео: Стили и темы, Неделя 3. Подведение итогов, Графика
Неделя 4. Введение, Неделя 4. Обсуждение, Тренировочное видео: Управление строками и столбцами, Тренировочное видео: Найти и заменить, Тренировочное видео: Фильтрация, Тренировочное видео: Сортировка, Тренировочное видео: Условное форматирование, Неделя 4. Подведение итогов, Доступность
Неделя 5. Введение, Неделя 5. Обсуждение, Тренировочное видео: Предпросмотр печати, Тренировочное видео: Ориентация, поля и масштаб, Тренировочное видео: Разрывы страниц, Тренировочное видео: Печатать заголовки, Тренировочное видео: Верхние и нижние колонтитулы, Неделя 5. Подведение итогов, Параметры сохранения
Неделя 6. Введение, Неделя 6. Обсуждение, Тренировочное видео: Основные типы диаграмм: Круговые, столбчатые диаграммы и графики, Тренировочное видео: Перемещение и изменение размера диаграмм, Тренировочное видео: Изменение стиля и типа диаграммы, Тренировочное видео: Изменить элементы диаграммы, Неделя 6. Подведение итогов, Обмен диаграммами
Курс 1: Итоговая оценка
Course: ما هي الإدارة ولماذا نحتاج إليها |What and Why of Management
Modules:
مفهوم الإدارة (Management), أبعاد الإدارة (The Dimensions of Management) -الجزء الأول, أبعاد الإدارة (The Dimensions of Management) -الجزء الثاني, عامل الوقت (Time Factor), الفرق بين المدير (Manager) والقائد (Leader), أمثلة عن دور المدراء في  شركات ناجحة, أنواع المديرين ومزايا وعيوب كل نوع -الجزءالأول, أنواع المديرين ومزايا وعيوب كل نوع -الجزء الثاني, التحكم الذاتي من خلال القياس (Self-Control Through Measurement)
Course: The Social Context of Mental Health and Illness
Modules:
Welcome to the course!, 1.0 Introduction, 1.1 Visiting the asylum, 1.2 Why the asylum?, 1.3 20th century mental health care, 1.4 Antipsychiatry, 1.5 Deinstitutionalization, 1.6 Community-based mental health care, 1.7 Recovery and mental health, 1.8 Conclusion, Bonus material: An introduction to author Caroline Fei-Yeng Kwok
2.0 introduction to lecture 2, 2.1 defining mental health, 2.2 what is mental illness?, 2.3 social determinants of mental health, 2.4 SDoH in action, 2.5 the biopsychosocial perspective on mental health, 2.6 applying the biopsychosocial perspective, 2.7 Conclusion
3.0 Introduction to lecture 3, 3.1 Demystifying the DSM, 3.2 Diagnosis as a series of social events, 3.3 Diagnosis: An example of the role of social context, 3.4a The social context of treatment options, 3.4b The social context of treatment options part 2, 3.5 The social context of treatment access, 3.6 Conclusion, From summer 2014: what's with the DSM?
4.0 introduction to lecture 4, 4.1 culture mental health mental illness, 4.2 culture & mental health in historical context, 4.3 culture and mental health, 4.4 culture and mental illness, 4.5 an example of intersections between culture and mental health, 4.6 cultural competence and multicultural mental health care, 4.7 Conclusions
5.0 introduction to lecture 5, 5.1 families and mental health, 5.2 do families cause mental illness - no, 5.3 families and caregiving, 5.4 families and recovery, 5.5 conclusions
6.0 introduction to lecture 6, 6.1 stigma and mental illness, 6.2a a life course approach to preventing mental disorders part 1, 6.2b a life course approach to preventing mental disorders part 2, 6.3 interventions to promote community mental health, 6.4 towards community that support mental health, 6.5 conclusions
Course: نماذج إدارة العمليات | Operations Management Models
Modules:
مقدمة عن شجرة القرار (Decision Tree), أهم نماذج إدارة العمليات في سوق العمل, طريقة حساب (Event Nodes) و(Decision Nodes), الإنتاج في الوقت المناسب (الجزء 1), الإنتاج في الوقت المناسب (الجزء 2), أهمية 6 سيجما (Six Sigma), أمثلة عن 6 سيجما (Six Sigma), عيوب 6 سيجما (Six Sigma), إدارة الجودة الشاملة (Total Quality Management), الخاتمة
Course: خدمة العملاء | Customer Service
Modules:
مسؤوليات وواجبات خدمة العملاء, أهم صفات موظف خدمة العملاء, الأمور الواجب تجنبها ومتابعة العملاء, كيفية التعامل مع شكاوى العملاء, أنواع العملاء وكيفية التعامل معهم, التأكد من رضا العميل, الجانب السيء لخدمة العملاء, خطة خدمة العملاء
Course: Applying Data Analytics in Finance
Modules:
Coursera Course Introduction  ***, Instructor Bio: Jose Rodriguez  ***, Interview with Jose Rodriguez, Learn on Your Terms
Module 1 Overview  ***, Jose Rodriguez: Forecasting in Practice, Lesson 1-1.1 Subjective Forecasting, Lesson 1-1.2 Business Forecasting and Time Series Data, Lesson 1-2.1 Introduction to Financial Analytics, Lesson 1-3.1 Forecasting Performance Measurements: Distance, Lesson 1-3.2 Forecasting Performance Measurements: Metrics
Module 2 Overview  ***, Jose Rodriguez: Forecasting Models in Practice, Lesson 2-1.1 Introduction to Forecasting: Average Method, Lesson 2-1.2 Introduction to Forecasting: Naive Method, Lesson 2-1.3 Introduction to Forecasting: Linear Regression  ***, Lesson 2-1.4 Introduction to Forecasting: R Example, Lesson 2-2.1 Moving Averages, Lesson 2-3.1 Introduction to Exponential Smoothing, Lesson 2-3.2 Simple Exponential Smoothing, Lesson 2-3.3 Simple Exponential Smoothing: R Example, Lesson 2-4.1 Holt's Exponential Smoothing, Lesson 2-4.2 Holt-Winter's Forecasting Model, Lesson 2-4.3 Holt-Winter's Model: R Example, Lesson 2-5.1 Autoregression, Lesson 2-5.2 Autoregression: R Example
Module 3 Overview  ***, Jose Rodriguez: ARIMA in Practice, Lesson 3-1.1 Stationarity: Introduction, Lesson 3-1.2 Stationarity: Differencing, Lesson 3-2.1 ARIMA: Introduction, Lesson 3-2.2 ARIMA: Components, Lesson 3-2.3 ARIMA: Model and R Example Part 1, Lesson 3-2.4 ARIMA: Model and R Example Part 2, Lesson 3-2.5 ARIMA: Model and R Example Part 3, Lesson 3-2.6 ARIMA: Model and R Example Part 4, Lesson 3-2.7 ARIMA: Model and R Example Part 5
Module 4 Overview  ***, Jose Rodriguez: Portfolios in Practice, Lesson 4-1.1 Portfolio Theory: Introduction, Lesson 4-1.2 Portfolio Theory: Expected Returns, Lesson 4-1.3 Portfolio Theory: Risk of a Security, Lesson 4-1.4 Portfolio Theory: Efficient Frontier, Lesson 4-1.5 Portfolio Theory: Portfolio Weights, Lesson 4-1.6 Portfolio Theory: Capital Allocation Line, Lesson 4-1.7 Portfolio Theory: Diversification, Lesson 4-2.1 Introduction to Algorithmic Trading, Lesson 4-2.2 Introduction to Algorithmic Trading: Trend Following Strategy, Lesson 4-2.3 Introduction to Algorithmic Trading: Backtesting, Lesson 4-2.4 Introduction to Algorithmic Trading: R Example, Lesson 4-2.5 Introduction to Algorithmic Trading: Conclusion, Course Summary: Applying Data Analytics in Finance
Course: From Climate Science to Action
Modules:
Be Part of the Global Conversation on Climate Change, Climate Science and Emissions Scenarios, Climate Impacts in the 21st Century, Types of Climate Observation
Sectoral Impacts Around the World (Part I), Sectoral Impacts Around the World (Part II), Climate Change, Fragility, and Conflict, Sectoral Impacts in South Asia, Sectoral Impacts in East Asia and Pacific, Sectoral Impacts in Sub-Saharan Africa, Sectoral Impacts in Europe and Central Asia, Sectoral Impacts in The Middle East and North Africa, Sectoral Impacts in Latin America and the Caribbean, Resilience and Adaptation – Monitoring Coastal Zones
Climate Resilience, Policy Instruments for Low Emission Development, Mitigation in East Asia and Pacific, Adaptation and Resilience in East Asia and Pacific, Mitigation in Sub-Saharan Africa, Adaptation and Resilience in Sub-Saharan Africa, Mitigation in Europe and Central Asia, Adaptation and Resilience in Europe and Central Asia, Adaptation and Resilience in the Middle East and North Africa, Mitigation in the Middle East and North Africa, Mitigation in Latin America and Caribbean, Adaptation and Resilience in Latin America and Caribbean, Mitigation in South Asia, Adaptation and Resilience in South Asia, The Importance of EO in Climate Policy and Planning
We Can, We Will, We Must Act on Climate Change, Act Now, Act Together, Act Differently in Response to Climate Change, Perspectives - Countries Acting to Address Climate Change Challenges, Big Data and Crowdsourcing – ESA MOOC
Course: Amazon DevOps Guru Getting Started
Modules:
Amazon Bedrock - Getting Started
Course: Responsible AI for Developers: Fairness & Bias - 繁體中文
Modules:
課程簡介
AI 與責任, Google 的 AI 開發原則, 負責任的 AI 技術做法, 個案研究：Google 航班/機票
公平性和偏誤總覽, 找出偏誤：TFDV 工具, 找出偏誤：What-if 工具, 找出偏誤：TFMA 工具, 減少偏誤：資料介入, 減少偏誤：閾值校準, 減少偏誤：Model Remediation, 研究室：在 TensorFlow 中使用 MinDiff 減少偏誤, Coursera：開始使用 Google Cloud Platform 和 Qwiklabs
課程摘要
單元 0：課程簡介, 單元 1：負責任的 AI 技術簡介, 單元 2：AI 公平性和偏誤, 單元 3：課程摘要
Course: Chino básico: La etiqueta social en los negocios
Modules:
¡Bienvenidos al Curso 2!
¡ Bienvenidos al Módulo 1!, Vocabulario y frases importantes, Módulo 1 Conclusión: ¡Felicidades!
¡Bienvenidos al Módulo!, Los puestos de trabajo 1, Los puestos de trabajo 2, Los departamentos dentro la empresa, Video: ¡A practicar!, Diálogo 1, Diálogo 2, Diálogo 3, Conclusión Módulo 2: ¡Felicidades!
Introducción al Módulo 3, ¿Qué haces en el trabajo?, Frases simples 1, Frases simples 2, Los títulos universitarios, Frases simples 3, Video: Diálogo 1, Video: Diálogo 2, Video: Diálogo 3, Conclusión del Módulo 3: ¡Felicidades!
Introducción al Módulo 4, Vocabulario: La hora 1, Vocabulario: La hora 2, Video: Frases simples, Video: Conversaciones básicas 1, Video: Conversaciones básicas 2, Video: Diálogo 1, Video: Diálogo 2, Video: Diálogo 3, Conclusión del Módulo 4:  ¡Felicidades!
Introducción al Módulo 5, Video: De visita 1, Video: De visita 2, Video: Preguntas y respuestas para conocerse mejor 1, Video: Preguntas y respuestas para conocerse mejor 2, Video: Diálogo 1, Video: Diálogo 2, Video: Diálogo 3, Conclusión del Módulo 5: ¡Felicidades!
Examen sumativo: Curso 2
Conclusión de Curso 2: ¡Felicidades y buen trabajo!
Course: Arabic for Beginners: Communicating in Arabic Culture
Modules:
Course Introduction, Course Overview, Introduction Dialogue, Family and Friends, Feelings and Emotions, Feelings and Emotions Review, Professions and Workplaces
Senses and Body Parts, Locations, Time, Directions and Places, School Vocabulary and Activities
Module Description, Cultural Celebrations, Dining, Restaurants, and Cooking
Personal Preferences, Daily Routines and Functions, Course Outro
Course: Art and the Digital Transformation
Modules:
Voices, Introduction, Interview with Caroline Sinders, Interview with Jazmin Morris
Art as pharmakon, Interview with T.I.E., Interview with Caroline Sinders, Interview with Klaus Æ. Mogensen, Interview with Nicolas Padfield
Interview with Sineglossa, Interview with the SIM project, Interview with FACT
Interview with Daniel G. Andujar, Interview with Daniel G. Andujar, Interview with Daniel G. Andujar, Interview with Daniel G. Andujar
Interview with LATRA, Interview with Waag, Interview with European Alternatives, Interview with Radiona
Interview with the TRACE WASTE Project, Interview with Paolo Cirio, Happy Hybrid
Case study
Course: Fundamentals of Robotics & Industrial Automation
Modules:
About the Specialization, About the Course, Importance of Mechatronics and its emergence -Part 1, Importance of Mechatronics and its emergence -Part 2, Role of sensors from Domestic appliances to Shop floors - Part 1, Role of sensors from Domestic appliances to Shop floors - Part 2, Proximity Sensors, Position Sensors & Displacement Sensors in Machine tools -Part 1, Proximity Sensors, Position Sensors & Displacement Sensors in Machine tools -Part 2, Temperature sensors in Machineries, Force Sensors in Machineries, Concept of Range sensors  for Robots, Touch & Binary Sensors in Robots, Sensors in AGV, Analog Sensors for Robots, Compliance and Slip Sensors in pick and place Robots, Static and Dynamic Characteristics of Sensors, Standards and specifications of sensors
Optical Encoders in speed measurement - Part 1, Optical Encoders in speed measurement- Part 2, Interfacing sensors in a CNC Machine for Tool life monitoring  -Part 1, Interfacing sensors in a CNC Machine for Tool life monitoring  -Part 2, Autonomous Mechatronics systems in Machine tools, Open loop systems and closed loop systems (Servo Systems) in Machineries, Digital Motor in Machine tools (Machineries) -Part 1, Digital Motor in Machine tools (Machineries) -Part 2, Servo motors AC and DC in a Manufacturing system - Part 1, Servo motors AC and DC in a Manufacturing system - Part 2, Electrical drives in powering machine tools -Part 1, Electrical drives in powering machine tools -Part 2, Trouble shooting in Electrical Drives Part-1, Trouble shooting in Electrical Drives Part-2
Organization of an Industrial Robot, Applications of Robot Manipulator, Robotic Configurations in applications perspective, Industrial Robot - Joints, Robot Wrist Configurations, Industrial Robot –  Mechanical Gripper, Other type of Robotic Grippers for various applications, Microprocessor in Automated Machine tools-Part 1, Microprocessor in Automated Machine tools-Part 2, Microcontroller in modern Machinery, Microcontroller in Modern Machinery-Part 2, Role of PLCs in Machining systems Part 1, Role of PLCs in Machining systems Part 2, Mechatronics system design-Part 1, Mechatronics system design-Part 2, Utilizing IoT in Mechatronics systems- Part 1, Utilizing IoT in Mechatronics systems- Part 2, Role of Fuzzy logic in Manufacturing arena- Part 1, Role of Fuzzy logic in Manufacturing arena- Part 2, Role of Fuzzy logic in Manufacturing arena- Part 3, Introduction to MATLAB-Part 1, MATLAB Problem 1-Part 2, MATLAB Problem 2-Part 3
Course: 软件测试 (Software Testing)
Modules:
0.1 L-课程介绍, 0.2 D-慕测平台 (mooctest), 1.1 L-Bug故事, 1.2 L-PIE模型, 1.3 L-测试术语, 1.4 L-Fault反思
2.1 L-测试中的图, 2.2 L-图覆盖准则, 2.3 L-结构化覆盖, 2.4 L-控制流测试, 2.5 L-数据流测试, 2.6 D-JUnit使用示例
3.1 L-随机测试, 3.2 L-等价类划分, 3.3 L-边界值分析, 3.4 L-组合测试, 3.5 D-Selenium使用演示, 3.6 D-PICT使用演示
4.1 L-功能测试简介, 4.2 L-探索式测试, 4.3 L-微软记事本功能测试1, 4.4 L-微软记事本功能测试2, 4.5 L-华三SDN测试简介, 4.6 L-华三SDN部署测试, 4.7 L-华三SDN功能测试
5.1 L-性能测试简介, 5.2 L-趋势IWSaaS+AWS云性能测试, 5.3 L-趋势IWSaaS无人值守性能测试, 5.4 L-趋势性能测试环境, 5.5 L-淘宝Web性能测试, 5.6 L-淘宝PTS性能测试服务, 5.7 L-华三SDN性能测试, 5.8 D-JMeter使用演示
6.1 L-移动应用测试简介, 6.2 L-百度MTC介绍, 6.3 L-百度MTC演示, 6.4 L-百度移动应用质量标准, 6.5 L-趋势安全移动办公的用户体验测试, 6.6 L-趋势科技移动虚拟化平台应用测试, 6.7 D-Kikbug众包测试
Course: Bayesian Statistics: Techniques and Models
Modules:
Course introduction, Objectives, Modeling process, Components of Bayesian models, Model specification, Posterior derivation, Non-conjugate models, Monte Carlo integration, Monte Carlo error and marginalization, Computing examples, Computing Monte Carlo error
Algorithm, Demonstration, Random walk example, Part 1, Random walk example, Part 2, Download, install, setup, Model writing, running, and post-processing, Multiple parameter sampling and full conditional distributions, Conditionally conjugate prior example with Normal likelihood, Computing example with Normal likelihood, Trace plots, autocorrelation, Multiple chains, burn-in, Gelman-Rubin diagnostic
Introduction to linear regression, Setup in R, JAGS model (linear regression), Model checking, Alternative models, Deviance information criterion (DIC), Introduction to ANOVA, One way model using JAGS, Introduction to logistic regression, JAGS model (logistic regression), Prediction
Introduction to Poisson regression, JAGS model (Poisson regression), Predictive distributions, Correlated data, Prior predictive simulation, JAGS model and model checking (hierarchical modeling), Posterior predictive simulation, Linear regression example, Linear regression example in JAGS, Mixture model in JAGS
Course conclusion
Course: Préparer les données pour l'exploration
Modules:
Introduction à l'exploration de données, Hallie : Des informations fascinantes sur les données, La collecte de données dans notre monde, Déterminer quelles données collecter, Découvrir les formats de données, Comprendre les données structurées, Savoir reconnaître le type de données avec lesquelles vous travaillez, Composants du tableau de données, Découvrir les données larges et longues
Assurer l'intégrité des données, Partialité : Des questions aux conclusions, Données partiales et impartiales, Comprendre la partialité dans les données, Identifier les bonnes sources de données, Qu'est-ce qu'une « mauvaise » donnée ?, Introduction à l'éthique des données, Rappel facultatif - Alex : L'importance de l'éthique des données, Introduction à la confidentialité des données, Andrew : L'utilisation éthique des données, Caractéristiques des données ouvertes, Andrew : Étapes pour une utilisation éthique des données
Tout sur les bases de données, Caractéristiques des bases de données, Explorer les métadonnées, Utiliser les métadonnées en tant qu'analyste, Gestion des métadonnées, Megan : S’amuser avec les métadonnées, Travailler avec plus de sources de données, Importation de données à partir de feuilles de calcul et de bases de données, Tri et filtrage, Configurer BigQuery, y compris les options Sandbox et de facturation, Comment utiliser BigQuery, BigQuery en action
Ayez confiance en vos données, Soyons organisés, Tout ce qu’il faut savoir sur le nommage de fichier, Fonctionnalités de sécurité des tableurs
Gérer votre présence en tant qu'analyste de données, Pourquoi une présence en ligne est importante, Conseils pour améliorer votre présence en ligne, Savoir-faire en réseautage, Avantages du mentorat, Rachel : Les mentors sont essentiels
Félicitations ! Résumé du cours
Course: Pensamiento sistémico
Modules:
Introducción, De la antigüedad hasta el siglo XX, Teoría general de sistemas y cibernética, Sistemas complejos, El modelo y lo modelado, Reduccionismo: sus ventajas y sus límites, Implicaciones de las interacciones, Relevancia de las simulaciones, Inundados por datos
Sistemas, Redes, Dinámica y retroalimentación, Fragilidad, robustez y antifragilidad, Información, Emergencia, Auto-organización, Complejidad
Microbioma, La mente extendida, Familias, Organizaciones, Sociedades, Ciudades, Economías, Epidemias, Ecología
Ingeniería, Ciencia, Arte, Filosofía, Ética, Felicidad, Proyecto final, Pensamiento sistémico en el contexto de la pandemia por COVID19
Course: Managing Human Capital in Retail
Modules:
Introduction, Course Overview, Human Capital as Cost Driver vs. Organizational Capacity, From Headcount to Organizational Capacity, The Ability-Motivation-Opportunities Framework, Human Capital Management as a System, The Value of the Partnership Approach, Human Capital Management Strategy
Effective Staffing: The Right Number of People, Effective Staffing: The Right People, Effective Staffing: The Problem with Intuition, Best Practices in Selecting Employees: Identify Your Criteria, Best Practices in Selecting Employees: Evaluating Candidates, Best Practices in Selecting Employees: Integrating Scores, New Technologies in Hiring, Developing the Talent Pipeline
Development and Retention Introduction, Why Train: Firm Specific Skills, Why Train: General Skills, Keys to Effective Learning, Costs of Attrition, Causes of Attrition, Strategies for Retention
Achieving Alignment and Motivation Introduction, Theories of Motivation, Goal Setting and Motivation, Managing Compensation, Setting the Right Pay Level, Motivation through Job Design, Course Conclusion
Course: Leer a Macondo: la obra de Gabriel García Márquez
Modules:
Video: Introducción al curso, Video: Presentación de La hojarasca, Video: Una mirada al autor, Video: Estructura de la novela, Video: Los monólogos en la narración de la novela, Video: El surgimiento de Macondo, Video: Macondo en La hojarasca, Video: El dilema ético, Video: Cierre de La hojarasca
Video: Presentación de El coronel no tiene quien le escriba, Video: Una mirada al autor, Video: Estructura de la novela, Video: Estructura y lenguaje, Video: Macondo como bisagra, Video: El aislamiento y la prensa, Video: El valor simbólico del paraguas, Video: El valor simbólico del reloj, Video: Cierre del módulo
Video: Presentación de Los funerales de la Mamá Grande, Video: La siesta del martes, Video: Los funerales, un carnaval, Video: Un día de estos, Video: Unidad e intensidad, Video: El barroco en Los funerales de la Mamá Grande, Video: El espacio público y privado, Video: Comparación con Espuma y Nada Más, Video: Cierre del módulo
Video: Presentación de La mala hora, Video: Una mirada al autor, Video: Lenguaje y estructura, Video: Ediciones de La mala hora e intertextualidad, Video: Lo privado y lo público, Video: La peste y la violencia, Video: La novela de La Violencia, Video: Cierre del módulo
Video: Presentación de Cien años de soledad, Video: Análisis del título, Video: Análisis del primer capítulo, Video: Los personajes femeninos, Video: La figura del héroe, Video: El personaje lector, Video: Cierre del módulo
Video: Presentación al análisis por ciclos, Video: Tiempo mítico 1, Video: Tiempo histórico 1, Video: Tiempo histórico 2, Video: Tiempo mítico 2, Video: Cierre del módulo, Video: Cierre del curso
Course: إتقان فن الإيجاز في الحديث | Mastering The Art of Briefing
Modules:
المقصود بفن الإيجاز وأهميته, متى يجب الإيجاز؟, المبادئ الرئيسية لتطبيق فن الإيجاز, مهارات ومتطلبات إتقان فن الإيجاز, خطوات إجراء الحوار الموجز والفعال, عناصر إتقان فن الإيجاز - الجزء الأول, عناصر إتقان فن الإيجاز - الجزء الثاني, الأخطاء والمشاكل التي تعيق إتقان الايجاز
Course: Build Basic Generative Adversarial Networks (GANs)
Modules:
Welcome to the Specialization, Welcome to Week 1, Generative Models, Real Life GANs, Intuition Behind GANs, Discriminator, Generator, BCE Cost Function, Putting It All Together, (Optional) Intro to PyTorch
Welcome to Week 2, Activations (Basic Properties), Common Activation Functions, Batch Normalization (Explained), Batch Normalization (Procedure), Review of Convolutions, Padding and Stride, Pooling and Upsampling, Transposed Convolutions
Welcome to Week 3, Mode Collapse, Problem with BCE Loss, Earth Mover’s Distance, Wasserstein Loss, Condition on Wasserstein Critic, 1-Lipschitz Continuity Enforcement
Welcome to Week 4, Conditional Generation: Intuition, Conditional Generation: Inputs, Controllable Generation, Vector Algebra in the Z-Space, Challenges with Controllable Generation, Classifier Gradients, Disentanglement, Conclusion of Course 1
Course: z/Architecture Assembler Language Part 1: The Basics
Modules:
Course overview
Introduction
Numbering systems, Decimal to hexadecimal conversion, Basic arithmetic
Memory, The CPU, Base-displacement, Long displacement, Relative addressing, Instructions, RS/RX instructions, SI/SS instructions, RXY/RI instructions
Assembler syntax, Reserving and initializing storage, DC, DS, and character strings, Assembler instructions, Assembler execution
Badge Quiz
Course: Gérer les crises de demain
Modules:
Présentation du cours, Introduction aux situations d'incertitude, Les apports de la littérature sur les situations d'incertitude, L'apport courant des HRO pour comprendre le fonctionnement en environnement incertain
Ce qu’il faut avoir préparé, Comment se lancer dans le pilotage de crise, Ne pas avoir de certitude mais inspirer confiance
Une crise est un effondrement de sens, Le processus de résilience organisationnelle par la création de sens, Mettre en pratique la résilience organisationnelle
Pilotage de la performance, Les spécificités du pilotage de la performance en période de forte incertitude, Sortie de crise : quel pilotage ?
Pourquoi communiquer en temps de crise ? L’opportunité, Que dire en cas de crise ? Le message, Les 10 règles d’or
Course: Translating Basic Research into Research for Humans
Modules:
Welcome to Translating Basic Research into Research for Humans, Pre-Course Survey, Syllabus, Acknowledgments, What Are The Different Types of Clinical Research?, Research Types - American Heart Association, Dana Farber Cancer Institute - Basic, Clinical, Translational Research: What's the Difference?, Basic, Translational, and Clinical Research - What is the difference?, Animals in Research, Ethics in Animal Research
Career Development for Translational Research
T1 Research with Communities: Rebecca Hasson, T1 Laboratory Research: Kathleen Stringer, T1 Clinical Research: MeiLan Han
Course: Responsible AI for Developers: Interpretability & Transparency - Español
Modules:
Introducción al curso
Descripción general de la interpretabilidad y transparencia, Descripción general de las técnicas de interpretabilidad, Explicaciones basadas en atributos: Agnóstico al modelo, Explicaciones basadas en atributos: Específico del modelo, Explicaciones basadas en ejemplos y conceptos, Herramientas de interpretabilidad, Transparencia de datos y modelos, Lab: Vertex Explainable AI, Coursera: Empezar a usar Google Cloud y Qwiklabs
Resumen del curso
Módulo 0: Introducción al curso, Módulo 1: Interpretabilidad y transparencia de la IA, Módulo 2: Resumen del curso
Course: Regression Models
Modules:
Introduction to Regression, Introduction: Basic Least Squares, Technical Details (Skip if you'd like), Introductory Data Example, Notation and Background, Linear Least Squares, Linear Least Squares Coding Example, Technical Details (Skip if you'd like), Regression to the Mean
Statistical Linear Regression Models, Interpreting Coefficients, Linear Regression for Prediction, Residuals, Residuals, Coding Example, Residual Variance, Inference in Regression, Coding Example, Prediction, Really, really quick intro to knitr
Multivariable Regression part I, Multivariable Regression part II, Multivariable Regression Continued, Multivariable Regression Examples part I, Multivariable Regression Examples part II, Multivariable Regression Examples part III, Multivariable Regression Examples part IV, Adjustment Examples, Residuals and Diagnostics part I, Residuals and Diagnostics part II, Residuals and Diagnostics part III, Model Selection part I, Model Selection part II, Model Selection part III
GLMs, Logistic Regression part I, Logistic Regression part II, Logistic Regression part III, Poisson Regression part I, Poisson Regression part II, Hodgepodge
Course: Power and Foreign Policy in International Relations
Modules:
Meet Your Instructor, Course Introduction
What Is Power and Why Does Size Matter in World Politics?, Hard Power, Soft Power, and Smart Power, Measuring a Nation-State's Overall Power or Comprehensive National Power, What Is the Present International Power Configuration?, What Exactly Is Foreign Policy?, National Interests and the Determinants of Foreign Policy, Do Only State Elites Conduct Foreign Policy?, Typical Attitudes and Outlooks of Great Powers, Typical Attitudes and Outlooks of Middle Powers, Typical Attitudes and Outlooks of Small Powers
Sustaining Primacy and the Global Balance of Power, Preserving the Capitalist World Order, Making the World Safe for Democracy, The Seismic Shift After the Collapse of the Soviet Union, The Liberal Takeover and the Trend of Humanitarian Interventions, The Global War on Terrorism: A Fatal Diversion from Great Power Competition, Are we Entering Bipolarity or Multipolarity?, Exiting the Forever Wars, Reorienting US Foreign Policy to Face China, Shifts in Domestic American Politics and an Inward Turn
From the Hindu Rate of Growth to the Express Train, From Estranged Democracies to Comprehensive Global Strategic Partnership, Strategic Diffidence to Strategic Assertion, A Net Provider of Security in the Indian Ocean Region, To Intervene or Not in Smaller Neighboring Countries, Rescue Diplomacy and Vaccine Diplomacy, Regional Integration and Connectivity Strategies, Narendra Modi’s Three Ds, Idealism vs. Realism in Indian Foreign Policy, A Multilateral Alliance of Democracies to Counterbalance China
The Watershed Moment of the Gulf War of 1990-91, Military and Economic Interdependence with the West, The Trump Disruption and the Qatar-Saudi Cold War, The Role of Values in the US-Qatar Alliance, Iran and Qatar’s Zero Enemy Policy, Picking up the Radical Palestinian Cause, Teaming up with Erdogan’s Turkey, Al Jazeera and the Forging of a Critical Arab Voice, Energy Diplomacy as a Vehicle for Influence, Mediating the War in Afghanistan
How Do Countries Adjust Their Foreign Policies in Response to the Changing International/Regional Power Configuration?
Course Wrap-Up
Course: General AI Mastery Toolbox: Master AI and Drive Success
Modules:
Introduction and Welcome, Overview of General AI, Importance of AI, Key Concepts, Essential AGI Resources, AGI Tools and Platforms, Community and Networking, Case Studies, Ethical Considerations, Emerging Trends, Course Summary
Course: Data Visualization with Tableau
Modules:
Installation & Introduction to UI of Tableau, Basics of Data Visualization, Why data visualization is important for any career, Exploratory Vs. Explanatory Analysis, Clients and Products in Tableau, Introduction to the tool, Tableau features, Connecting data with tableau, Joining data sources, Union on data sources, Live data connections vs data extracts, Usage of Menus and Toolbar, Analytics Pane, Sheet Tabs
Shelves and Cards, Marks Card, Legends, Difference between Green and Blue pill, Splitting data, Pivoting & Transforming data, Blue & green pills Filters, Blue & green pills affect on dates, Cleaning data by Bulk Re-aliasing, Create hierarchies to drill down into data, Creating groups for data, Creating and Using Sets, Create data filters, Create calculated fields, Combine data sources using data blending, Bringing in More data with Joins
Visualizing data using Bar Chart, Line Charts, Scatterplots, Heat maps, Histograms, Maps in Tableau, Dual Axis Charts, Pie Charts, Bump Charts, Control charts, Pareto charts, Waterfall charts, Usage and filtration of data with charts, Visualizing categorical data, Visualizing time series data, Visualizing multiple variables
Mapbox integrations, Aggregate calculations, Date calculations, Logic calculations, Number calculations, String calculations, Summary statistics in visualizations, Add reference lines, Add trend lines, Visualizing forecasting data, What is Dashboard?, Use of Dashboard?, Creating a dashboard
Course: AWS: Network Security, Compliance and Governance
Modules:
Welcome to the Course, Evaluate design requirements for alignment with security and compliance objectives Part 1, Evaluate design requirements for alignment with security and compliance objectives Part 2, Evaluate design requirements for alignment with security and compliance objectives Part 3, Security Groups, NACL, and Webserver - Part 1, Security Groups, NACL, and Webserver - Part 2, Security Groups, NACL, and Webserver - Part 3, Evaluate monitoring strategies in support of security and compliance objectives - Part 1, Evaluate monitoring strategies in support of security and compliance objectives - Part 2, VPC Flow Logs - Part 1, VPC Flow Logs - Part 2
CloudTrail - Part 1, CloudTrail - Part 2, CloudWatch Alarm - Part 1, CloudWatch Alarm - Part 2, CloudWatch Custom Metrics - Part 1, CloudWatch Custom Metrics - Part 2, Contrast and Compare Functional Capabilities of Security Groups, Network ACLs, and IAM policies - Part 1, Contrast and Compare Functional Capabilities of Security Groups, Network ACLs, and IAM policies - Part 2, Utilize encryption technologies to secure network communications, Outline the components of the solution (encryption, key management, audit controls etc.)-Part 1, Outline the components of the solution (encryption, key management, audit controls etc.) Part 2, Given a scenario, troubleshoot and resolve a network issue- Part 1, Given a scenario, troubleshoot and resolve a network issue -Part 2, Assess appropriate use of security groups and Network ACLs -Part 1, Assess appropriate use of security groups and Network ACLs  -Part 2, Course Conclusion
Course: Teaching Science at University
Modules:
Course Overview, Evidence-based science teaching, Rate teaching strategies, How the brain computes information, from behaviourism..., ...to constructivism, Encouraging higher order thinking
Identifying everyday conceptions, No teaching without everyday conceptions, Assessing your students conceptions, Learning as conceptual change, Learning as ontological change, Tips for engagement
Why science is hard to grasp, Using analogies, How to teach analogies, Successful instructional analogies, Multiple representations in science
Make science relevant, Active learning with socioscientific issues, Tasks for active learners, Active Learning with Digital Tools, Setting goals for students, Supervision of theses, Communication risk and uncertainity
Conducting a lab class, Interview with a digital simulation user, Preparing a lab class, Design principles for experiments, Identifying and fostering students' experimental competences, Teaching practical skills with digital simulations, Changing students conceptions about the nature of science, Models and modelling in science
Course: Trust and Security with Google Cloud - 日本語版
Modules:
コースの概要
概要, セキュリティに関する重要な用語と概念, クラウド セキュリティの構成要素, クラウド セキュリティと従来からのオンプレミス セキュリティとの比較, サイバーセキュリティの脅威
概要, データセンター, 安全なストレージ, ID, ネットワーク セキュリティ, セキュリティ運用
概要, Google Cloud の信頼に関する原則と透明性レポート, データ所在地とデータ主権, 業界と地域のコンプライアンス
コースのまとめ
Course: Beginner's Guide to Unit Testing
Modules:
Unit Testing Quiz
Course: Sustainable Vikings:  Sustainability & Corporate Social Responsibility in Scandinavia
Modules:
1.1) Course Overview, 1.2) What is the purpose of business?   From Adam Smith to Milton Friedman to Michael Porter., 1.3a) What is sustainability?  What is corporate social responsibility (CSR)?, 1.3b) Why do we need sustainability & CSR?, 1.3c) Interview with Professor Mette Morsing, Copenhagen Business School, 1.3d) Interview with Mads Øvlisen, former CEO Novo Nordisk & “Father of CSR in Denmark, 1.3e)  Interview with Professor Ed Freeman, University of Virginia Darden & oft-cited as “Father of Stakeholder Theory”, 1.4) Reflections with Robert Strand
2.1) What is Scandinavia?, 2.2) Exploring sustainability & CSR in Scandinavia: My personal journey, 2.3) Why explore sustainability & CSR in Scandinavia?, 2.4) Scandinavian Creating Shared Value, 2.5a) What is Scandinavian culture?, 2.5b) Interview with Mads Øvlisen, former CEO Novo Nordisk & “Father of CSR in Denmark
3.1) What does Scandinavian leadership & management look like?, Conversation with Mads Øvlisen Part A, Conversation with Mads Øvlisen Part B, Conversation with Mads Øvlisen Part C
4.1) Introduction to a global sustainability leader: Novo Nordisk, Conversation with Susanne Stormer Part A, Conversation with Susanne Stormer Part B
5.1) Introduction to Corporate Governance in Scandinavia, Conversation with Professor Steen Thomsen, Copenhagen Business School Part A, Conversation with Professor Steen Thomsen, Copenhagen Business School Part B, 5.4) Reflections on Discussion with Professor Steen Thomsen
6.1) Reflections from this course, 6.2) Becoming a Sustainable Viking
Course: What is the Metaverse?
Modules:
Welcome to the metaverse, This is the metaverse, Experiences in the metaverse, Avatars in the metaverse, Interoperability in the metaverse, Connection and communication, Working in the metaverse, The ecological implications of the metaverse
An interconnected ecosystem, Devices to access the metaverse, Game engines, XR in the metaverse, A supercomputer in a pair of glasses
Educational potential in the metaverse, Learning in the metaverse, Health in the metaverse, Marketing and retail in the metaverse, Arts, entertainment, and sports in the metaverse
Commerce in the metaverse, The creator perspective, Economic trends and opportunities
Keeping people safe, Building a safe metaverse, Diversity, equity, and inclusion in the metaverse, Ethics in the metaverse
Future technology, Research and development opportunities, The infrastructure of the metaverse