dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: Advanced Angular Development
Modules:
Instructor Welcome & Course Overview, Angular Modules, NgModule in Depth, Angular Services, Dependency Injection in Angular, Instructor Demo: Angular Services
Writing Observables in Angular, Angular Lifecycle Hooks, Making HTTP Requests in Angular, Instructor Demo: Lifecycle Hooks Part 1
Dynamic Components in Angular, Server-Side Rendering in Angular, Building & Publishing an Angular App, Instructor Demo: Angular Lifecycle Hooks: Making HTTP Requests, Congratulations
Course: Address Business Issues with Data Science
Modules:
CDSP Specialization Introduction, Course Intro: Address Business Issues with Data Science, Data Science, Design Thinking, Project Scope, Project Specification and Objectives, Project Timeline and Deliverables, Project Stakeholders, Stakeholder Requirements, POC, and MVP, Data Privacy and Security, Data Access and Governance
The Data Science Process, The Data Science Skillset, Problem Formulation, Common Data Science Issues, Modeling Data, Data Science Outcomes, Learning Modes, Randomness and Uncertainty
Data Science Project Outline
Course: Equivalent Circuit Cell Model Simulation
Modules:
2.1.1: Welcome to the course!, 2.1.2: How do we model open-circuit voltage (OCV) and state-of-charge (SOC)?, 2.1.3: How do we model voltage polarization?, 2.1.4: What is a "Warburg impedance" and how is it implemented?, 2.1.5: How do I convert a continuous-time model to a discrete-time model?, 2.1.6: What is a quick way to get approximate model parameter values?, 2.1.7: What is hysteresis in a lithium-ion cell and how can I model it?, 2.1.8: Summarizing an equivalent-circuit model of a lithium-ion cell, 2.1.9: Summary of "Defining an ECM of a Li-ion cell" and next steps
2.2.1: Lab equipment for cell characterization, 2.2.2: What cell tests are needed to determine open-circuit voltage?, 2.2.3: How to determine a cell's coulombic efficiency and total capacity, 2.2.4: How do I determine a cell's temperature-dependent OCV?, 2.2.5: Introducing Octave code to determine static part of ECM, 2.2.6: Summary of "Identifying parameters of static model" and next steps
2.3.1: What cell tests are needed to determine dynamic-model parameters?, 2.3.2: How are cell data used to find dynamic-model parameter values?, 2.3.3: Introducing Octave code to determine dynamic part of an ECM, 2.3.4: Introducing Octave toolbox to use ECM, 2.3.5: Understanding Octave code to simulate an ECM, 2.3.6: Understanding Octave code to look up model parameter value, 2.3.7: Understanding Octave code to compute OCV, 2.3.8: Some example results from using the Octave ESC toolbox, 2.3.9: Summary of "Identifying parameters of dynamic model" and next steps
2.4.1: How do I use the ECM to simulate constant voltage?, 2.4.2: How do I use the ECM to simulate constant power?, 2.4.3: How do I simulate battery packs?, 2.4.4: Introducing Octave code to simulate PCMs, 2.4.5: Introducing Octave code to simulate SCMs, 2.4.6: Summary of "Simulating battery packs in different configurations" and next steps
2.5.1: Introduction to the problem, 2.5.2: Modeling ideal vehicle dynamics, 2.5.3: Adding practical limits to model of vehicle dynamics, 2.5.4: Calculating electric-vehicle range, 2.5.5: Introducing Octave code to set up EV simulation, 2.5.6: Introducing Octave code to conduct EV simulation, 2.5.7 Summary of "Co-simulating battery and electric vehicle load" and next steps
Manually tuning an ESC cell model
Course: Black Lives Matter
Modules:
An Introduction to the Course, "The American Dream", A Culture of Racism?, Acts and Riots in the 1960s, The Conservative Turn, A Divided Community
Race and Policing, The Obama Presidency, The Troy Davis Moment, The Trayvon Martin Moment
A Generational Divide, A Women's Movement, Organizing the Movement, "Funding the Movement", The Demands of a Movement, The Solidarity of a Movement
The George Floyd Moment, The Impact of a Movement, "A Global Movement", An Anticapitalist Movement
Course: IBM COBOL Core
Modules:
Course Introduction, Introduction to Skytap and System Familiarization, Numeric Usage Types, Editing and Branching 1, Editing and Branching 2, Editing and Branching 3
Structured COBOL, Testing and Beginning Debugging, COBOL Reports Part 1, COBOL Reports Part 2, How to Call Programs
Table Handling Part 1, Table Handling Part 2, Sort and Merging, Intrinsic Functions, Course Wrap Up
Course: Communication Skills for University Success
Modules:
Welcome to the Academic Skills for University Success Specialization!, 1.1a Introduction to the Course, 1.2a Introduction to Academic Culture, 1.2b Introduction to Communication, 1.3a Survival Skills for University, 1.3b Resilience & Motivation for University, 1.4a Academic Integrity
2.1a Introduction to rhetorical situations, 2.1b Rhetorical situations at university, 2.1c University course outlines & contexts of communication, 2.2a Making the Most of Participation in University Contexts, 2.2b Participation & Communication at University, 2.3a Participating in Lectures & Tutorials, 2.3b Participating in Online Forums, 2.4a Participating in Group Work
3.1a Introduction to Understanding, Researching, and Planning Written Assignments, 3.2a Part 1: Understanding Essay Assignments, 3.2a Part 2: Interpreting Essay Questions, 3.2b Understanding and Interpreting Reports & Proposals, 3.3a Conducting Research for Essays, 3.3b Conducting Research for Reports & Proposals, 3.4a Planning Essays, 3.4b Planning Reports & Proposals
4.1a Introduction to Drafting, Refining, and Incorporating Visual Aids in Written Assignments, 4.2a Drafting Essays, 4.2b Drafting Reports & Proposals, 4.2c Coherence & Cohesion for Essays & Reports, 4.3a Polishing & Refining Essays, 4.3b Polishing & Refining Reports & Proposals, 4.3c Incorporating Visual Aids in Written Assignments, 4.3d Editing for Language, 4.4a Formatting and Proofreading Written Assignments for Submission
5.1a Introduction to Academic Presentations, 5.2a Understanding and Researching Presentations, 5.2b Planning Presentations, 5.3a Preparing Visual Aids, 5.3b Writing your Script, 5.3c Practising your Script, 5.4a Finding your Presentation Style, 5.4b Facilitating Audience Interaction and Fielding Questions
Summative Assessment Overview, How to mark your peers' assignments, Practice peer making activity answers
Course: Modernizing Data Lakes and Data Warehouses with GCP em Português Brasileiro
Modules:
Introdução à série de cursos, Introdução ao curso
Introdução ao módulo, O papel de um engenheiro de dados, Desafios da engenharia de dados, Introdução ao BigQuery, Data lakes e data warehouses, Diferenças entre bancos de dados transacionais e data warehouses, Trabalhar em parceria com outras equipes de dados, Gerenciar o acesso e a governança dos dados, Demonstração: Como encontrar as PII no conjunto de dados usando a API DLP, Criar pipelines prontos para produção, Estudo de caso de um cliente do Google Cloud, Resumo, Introdução ao laboratório: Como usar o BigQuery para fazer análises, Coursera: Guia inicial do Google Cloud Platform e do Qwiklabs
Introdução ao módulo, Introdução aos data lakes, Opções de armazenamento de dados e ETL no Google Cloud, Criar um data lake usando o Cloud Storage, Cloud Storage seguro, Armazenar todos os tipos de dados, Cloud SQL como um data lake relacional, Introdução ao laboratório: Como carregar dados de táxi no Google Cloud SQL
Introdução ao módulo, O data warehouse moderno, Introdução ao BigQuery, Demonstração: Como consultar TB de dados em segundos, Noções básicas sobre o BigQuery, Carregar dados no BigQuery, Introdução ao laboratório: Como carregar dados no BigQuery, Analisar esquemas, Demonstração: Como analisar esquemas, Projeto do esquema, Campos aninhados e repetidos, Demonstração: Campos aninhados e repetidos, Projetar o esquema ideal para o BigQuery, Introdução ao laboratório: Como trabalhar com dados JSON e de matriz no BigQuery, Otimizar usando particionamento e clustering, Introdução ao laboratório: Tabelas particionadas no BigQuery, Revisão
Resumo do curso
Modernizing Data Lakes and Data Warehouses with Google Cloud
Course: DevOps Prerequisite Course
Modules:
Introduction, Understanding DevOps Tools and How it works
Working your way through the CLI, Mastering the VI Editor, More Linux Commands, Understanding Package Management in Linux, Managing System Services in Linux
Essential Networking Principles, Exploring the Domain Name System
Introduction, Java - Introduction, Java - Build & Packaging, NodeJS - Introduction, Node JS - NPM, Python - Introduction, Python - PIP
Course: Navigating Compliance in the Food and Beverage Industry
Modules:
Introduction to the Course & Meet Your Instructor, Creating HACCP & Food Safety Management System, Biological Contamination, Cross Contamination, Viruses, and Parasites, Contamination, Pre-Requisites Prevent Contamination, Cleaning, Hygiene, and Traceability in Food Safety, Pre-Requisites Temperature/Time Control, Controlling CCP, Intro What is Risk Assessment, Priority Hazards in Restaurants, Managing Manual Handling and High-Risk Hazards in the Kitchen, Personal Protective Equipment, Cleaning for Food Safety, Chemical Safety in Cleaning and Food Safety, Induction Training - Food Safety and Health and Safety, Maintaining Training Records for Food Safety Compliance, Due Diligence, Reporting Accidents and Complaints, Congratulations and Continuous Learning Journey
Course: E-commerce Academy
Modules:
Bienvenida al curso, Fundamentos de e-commerce, ¿Qué hay que tener en cuenta para vender online?, El contexto actual del e-commerce: ¿cuáles son los productos más vendidos?
Branding: ¿cuál será la marca de nuestro negocio?, Consideraciones acerca del diseño de la tienda online, La experiencia del usuario (UX) en nuestra tienda online
¿Quién se encargará de desarrollar nuestra tienda online?, Sistemas de pago: ¿cómo cobraremos en nuestra tienda virtual?, La logística de distribución
Ventas online a través de marketplaces, Social commerce: cuando las redes sociales sirven también para vender online, Dropshipping: una manera sencilla de ingresar al comercio electrónico
Course: Gen AI for Fraud Detection Analytics
Modules:
Gen AI for Fraud Detection Analytics, Introduction to Generative AI, Understanding Gen AI's part in Fraud Detection, Technological Advancements of Generative AI in Fraud Detection, Overview of the Project, Project Development, Data Collection and Pre-Processing, Setting-up LSTM Model, Setting-Up GAN Model Architecture, Ethical Challenges in Fraud Detection, Regulatory compliance and Privacy protection, Course Summary
Course: Foundations of Machine Learning
Modules:
Gateway to the Course, Course and Instructor Introduction Video, Introduction to Problem Statement, How do we Make Predictions?, Methodology of Evaluating Predictions, Introduction to Data Division, Building Benchmark Models and Evaluating It, Introduction to Machine Learning, Applications of Machine Learning, Types of Machine Learning
ML Workflow, Tasks to be Performed, Combining Product Attribute Data with POS Data, Combining all the tables in the Dataframe, Understanding the Combined Data, Treating Missing Values - Part 1, Treating Missing Values Part 2, Outlier Detection and Treatment, Preparing the Dataset for Supervised and Unsupervised Models, Generative AI for Data Analysis, Introduction to KNN, Building a kNN model, Choosing the Optimal K, Different Ways to Calculate Distance, Problems with Distance Based Algorithm, Sklearn to build Optimal Process to Build an ML Model, Building a Knn classification model and evaluating it, Choosing the right K value, Bias and Variance
Understanding Confusion Matrix and Accuracy, A deep dive into Precision, Recall and F1 Score, Understanding the AU-ROC curve, Why do we calculate RMSE, Understanding R2 Score and Adjusted R2 Score, Train-Test Split, Train-Test split ratio and limit, Cross validation, Implementing Cross validation, Benchmark Models
Introduction to Linear Regression, Significance of Slope and Intercept in the linear regression, How Model Decides The Best-Fit Line, Let’s Build a Simple Linear Regression Model, Model Understanding Using Descriptive Approach, Model Understanding Using Descriptive Approach - II, Model Building Using Predictive Approach, Introduction, Lines to Curves with Logistic Regression, Reading Between the Curves with Log Loss, Stats Model Summary, Feature Selection and Scaling, Predictive model in Logistic Regression
Introduction to Decision Trees, Let’s Visualize The Decision Tree, How Do Decision Trees Decide?, How Decision Trees Make Predictions?, Hands on: Building the Decision Tree Classification Model, Hyperparameters of Decision Trees, Hands on: Building the Decision Tree Classification Model - Part 2, Building a Decision Tree Regression Model, Handling Imbalanced Datasets, Handling Imbalanced Datasets - Hands on
Setting the Context, Choosing Clustering Algorithms, Solving our Problem using k-means - Part 1, Solving our Problem using k-means - Part 2, Finding optimal K value, Analysis and Insights Based on the Plot, Introduction to Hierarchical Clustering Analysis (HCA), Solving our Problem using Hierarchical Clustering, Introduction to DBSCAN, Solving our Problem using DBSCAN Clustering, Course Summary
Course: Conduzir pesquisas de UX e testar os primeiros conceitos
Modules:
Introdução ao Curso 4: Conduzir pesquisas de UX e testar os primeiros conceitos, Sam - Como trabalhar como pesquisador de UX autodidata, Jason - Minha jornada até a UX, Compreenda o processo de pesquisa de UX, Conhecer os sete elementos de um plano de pesquisa, Comece a desenvolver um plano de pesquisa: histórico do projeto, objetivos e perguntas da pesquisa, Continue desenvolvendo o plano de pesquisa: KPIs, Continue desenvolvendo o plano de pesquisa: Metodologia, Continue desenvolvendo o plano de pesquisa: Participantes, Termine seu plano de pesquisa: Script, Transforme a privacidade em uma prática de UX, Compreenda questões de privacidade, Vanessa - Ética, privacidade e dados no mundo real, Finalização: Planejamento de estudos de pesquisa de UX
Boas-vindas à semana 2, Introdução a estudos de usabilidade, Realizar estudos de usabilidade moderados e não moderados, Introdução a uma simulação de estudo de usabilidade não moderado, Participante A - Simulação de estudo de usabilidade, Participante B - Simulação de estudo de usabilidade, Participante C - Simulação de estudo de usabilidade, Participante D - Simulação de estudo de usabilidade, Participante E - Simulação de estudo de usabilidade, Explore as práticas recomendadas para estudos de usabilidade: Antes de começar o estudo, Explore as práticas recomendadas para estudos de usabilidade: Durante o estudo, Deana - Meu trabalho como pesquisadora de UX, Identifique vieses ao entrevistar participantes de estudos de usabilidade, Reduza o viés nas entrevistas, Introdução a métodos de anotação durante estudos de usabilidade, Como usar uma planilha para fazer anotações, Chikezie - Minha jornada até a UX, Finalização: Como fazer uma pesquisa com estudos de usabilidade
Das observações aos insights, Estudo de caso: Como melhorar o design no Google, Desenvolvimento de insights, Reunir e organizar dados, Padrões e temas nos dados de pesquisa, Características de insights fortes, Utkarsh: Desenvolver insights a partir de estudos de usabilidade, Finalização: Analisar e sintetizar os resultados da pesquisa
Organizar insights para compartilhar, Escolher um formato para compartilhar insights, Criar uma apresentação consistente, Dicas de apresentação, Heather – Apresentar insights de pesquisa, Modificar designs com base nos insights de pesquisa, Demonstração de como modificar designs com base nos insights de pesquisa, Finalização: Compartilhar insights de pesquisa para aprimorar designs, Parabéns por concluir o Curso 4: Conduzir pesquisas de UX e testar os primeiros conceitos
Course: Herramientas de la Economía Circular
Modules:
Introducción al curso
Introducción Módulo 1: La esencia de la Economía Circular, Conceptos de la Economía Circular, Actores y roles
Introducción Módulo 2: Herramientas de la Economía Circular I, El Eco-Mapa, El Eco-Balance
Introducción Módulo 3: Herramientas de la Economía Circular II, Los Costos de Ineficiencia
Introducción al módulo 4: Alternativas preventivas innovadoras, Alternativas preventivas, Indicadores
Introducción al módulo 5 - Proyecto aplicado de Economía Circular, Estructuración de proyectos, Cierre de curso
Course: Leading Diverse Teams
Modules:
Cultural Intelligence (CQ) Framework, Additional Resources
Global Mindset Framework, Additional Resources
Implicit Bias, Additional Resources
CQ Development Plan, Additional Resources
Course: Trabajar para ser feliz
Modules:
IAE Business School, Introducción al curso, "Viejas creencias y nuevas realidades del mundo globalizado", "La gestión del talento hoy", "El aporte de la mujer al mundo laboral", "El valor de la complementariedad", "El trabajo del futuro", Amelia. Ross. Y el trabajo del futuro.
El cuidado de la ecología humana., La gestión del talento hoy., Proyecto de vida = Proyecto de felicidad., Rumbo hacia la felicidad, m2v3 (ver placa) "Los vínculos familiares: imprescindibles e irremplazables", La familia: configuradora de la vida social., La educación: camino del aprendizaje, La economía: arte de administrar la casa.
Fluir en el trabajo: De la motivación al disfrute (parte 1), Fluir en el trabajo: De la motivación al disfrute (parte 2), Cómo construir relaciones positivas en el trabajo., La esencia del liderazgo., Los líderes: agentes claves de la integración
Responsabilidad Social Empresaria (RSE) o Sustentabilidad, La familia de los colaboradores: un nuevo stakeholder de la empresa., Guías de Buenas Prácticas., Estrategias para la integración., Pasos a tener en cuenta para gestionar la integración: familia y trabajo., La felicidad como modelo de negocio (parte I), La felicidad como modelo de negocio (parte II), La felicidad como modelo de negocio (parte III)
Course: Programar desde cero en pseudocódigo
Modules:
Bienvenida, Variables y constantes: tipos de datos para usar en PSeInt, Instalación de PSeInt, Descubre estructuras condicionales, Juega con los operadores aritméticos, expresiones y asignaciones
Course: Introduction to Translational Science
Modules:
The Big Picture - Introduction (2:54), The Big Picture - Part I (7:41), The Big Picture - Part II (9:22), The Big Picture - Part III (5:20), The Big Picture - Part IV (7:00), T1 - Translation to Humans - Introduction (10:48), T1 - Translation to Humans Part I (6:59), T1 - Translation to Humans Part II (8:37)
T2 - Translation to Patients - Introduction (9:18), T2 - Translation to Patients - Part I (7:34), T2 - Translation to Patients - Part II (6:50), T2 - Translation to Patients - Part III (6:50), T2 - Translation to Patients - Part IV (9:55), T3 - Translation to Practice - Introduction (8:36), T3 - Translation to Practice - Part 1 (6:18), T3 - Translation to Practice - Part II (8:22), T3 - Translation to Practice - Part III (9:26)
T4 - Translation to Communities - Introduction (9:30), T4 - Translation to Communities - Part I (9:15), T4 - Translation to Communities - Part II (10:09), T4 - Translation to Communities - Part III (7:43), T4 - Translation to Communities - Part IV (6:58), T4 - Translation to Communities - Part V (9:04), Participating in Clinical and Translational Science - Introduction (4:12), Participating in Clinical and Translational Science - Part I (5:26), Participating in Clinical and Translational Science - Part II (3:51), Participating in Clinical and Translational Science - Part III (8:13)
Course: Introduction to Mobile Development
Modules:
Introduction to the program, Introduction to the course, Web and mobile developer roles, A day in the life of a mobile developer, How the internet works, What are websites and webpages?, What is a web server and how does it work?, What is a web browser and how does it work?, Mobile application evolution, iOS: Platform and language, Android: Platform and language, JavaScript, the language of the web, Web browsers vs mobile browsers, Responsive websites, Module summary: Mobile development
What is Hyper Text Markup Language?, HTML documents, Linking documents, Introduction to the DOM, Web accessibility, Selecting and styling, Box model introduction, Document flow - block vs. inline, Developer tools, What is a an IDE?, Module summary: Introduction to HTML and CSS
What is cross-platform mobile development?, Pros and cons of cross-platform app development, What is an emulator?, Static and dynamic content, Single page applications, What is React?, Case Study: Why did Facebook engineers create React?, How React works, Component hierarchy, What is React Native?, Why did Meta create React Native?, Module summary: React and React Native
Course 1 recap: Introduction to Mobile development, Congratulations, you have completed Introduction to Mobile development
Course: Planned Giving
Modules:
Planned Giving Course Introduction, General Tax Considerations, Charitable Gifts, and Deductions Introduction, General Tax Considerations (Part 1), General Tax Considerations (Part 2), Charitable Organizations, What is a Charitable Gift?, When is a Contribution Deductible? (Part 1), When is a Contribution Deductible? (Part 2)
Planned Giving Options and Donor Centered Giving Introduction, Planned Giving Terminology, Charitable Bequests, Charitable Gift Annuities, Pooled Income Funds, Charitable Remainder Trusts, Charitable Remainder Unitrust, Charitable Lead Trust, Identifying Planned Giving Donors, Building Relationships with Donors, Donor Interest and Strategies (Part 1), Donor Interest and Strategies (Part 2)
Planned Giving Administration Introduction, Structure Planned Giving with Legacy Management in Mind, Document Gift Acceptance Policies (Part 1), Document Gift Acceptance Policies (Part 2), Document Gift Acceptance Policies (Part 3), Build Relationships Between Investment, Gift, and Accounting Teams, Train Staff and Volunteers, Provide Donors Clear Disclosures, Marketing Fundamentals That Drive Successful Planned Giving
Planned Giving Resources Introduction, Specimen Agreements: Introduction, Specimen Agreements: Charitable Gift Annuity, Specimen Agreements: Charitable Trust and Unitrust, Specimen Agreements: Retain Life Estate, Planned Giving Software, Planned Giving Associations, Planned Giving Course Summary
Course: Financing and Profiting from Innovation for Corporate Entrepreneurs
Modules:
Preview of the Course, Welcome to Module 1, Finance for the corporate entrepreneur, The entrepreneurial spectrum, Corporate entrepreneur vs. startup entrepreneur, The "too typical" return on investment (ROI) process, A better approach to return on investment (ROI), Intangible assets and return on investment (ROI), The roles of products and leadership in return on investment (ROI), Financial statement basics, Financial statement details, Financial metrics
Welcome to Module 2, Valuation techniques, Net present value, Opportunity cost of capital, Why NPV is best, Project payback period, Internal rate of return, Weighted average cost of capital
Welcome to Module 3, Sources of funding, Internal funding, Customer and vendor financing, Franchising, Joint ventures, Co-branding, Licensing agreements
Welcome to Module 4, Business proposals and the pitch, How to write an effective business proposal, What do your funding sources want to see, How to create a pitch deck, Do's and don'ts of the pitch, Final thoughts
Course: Principles of Public Relations
Modules:
Specialization Introduction, Introduction to Defining the Public Relations Industry, Introduction to Week 1, Brief History and Development of the Field of Public Relations, Public Relations Society of America, Scholars’ Point-of-View
Introduction to Week 2, The Four-Step Process in Public Relations, An Example of the Four-Step Process in PR, Shifting from Tactical to Strategic Planning
Introduction to Week 3, Defining CSR, CSR in Practice, Corporate Social Advocacy
Introduction to Week 4, Agency vs. Corporate Communications, Range of Jobs in Public Relations, Polishing your LinkedIn Profile, Tips for Interviewing in PR
Introduction to Week 5, Defining Ethics in Public Relations, Making the Right Decision
Course: Building Regression Models with Linear Algebra
Modules:
Introduction to Specialization, Course Introduction, Instructor Introduction, What is Regression Analysis?, Different Types of Regression Models, Regression Models in the Real World, Introduction to the Method of Linear Regression Models, Introduction to the Method of Least Squares
Applying the Method of Least Squares, Minimizing the Error
What is Linear Regression?, Multiple Linear Regressions in Python
Solving a Real-World Problem Using Linear Regression Modeling: Part 1, Solving a Real-World Problem Using Linear Regression Modeling: Part 2
Course: Artificial Intelligence Ethics in Action
Modules:
Ethics in Action: Introduction
Project Summary
Project Summary
Project Summary
Course: Clinical Epidemiology
Modules:
Welcome to the Course!, Course Syllabus, Book: 'Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research', Short Survey
An Introduction, Core Concepts, Defining Your Research, A Multi-Level Research Problem
An Introduction to Diagnostic Research, Core Concepts in Diagnostic Research, Designing a Diagnostic Study, Case Study: A Diagnostic Rule for Deep Vein Thrombosis in Primary Care
An Introduction to Prognostic Research, Designing a Prognostic Study, Developing and Validating a Prediction Rule, Case Study: Developing a Prediction Rule for 10-year Cardiovascular Disease Risk
An Introduction to Intervention Research, Intended Effects, Unintended Effects, Case Study: Pneumococcal Vaccination in Adults
Join our challenge: help us reach Sustainable Development Goal (SDG) 3 on child health
Final Survey, Credits
Course: Spanish Vocabulary: Meeting People
Modules:
Course Introduction, Module Introduction, Introduction to Vocabulario, Introduction to Gramática, Pronunciation Tips, Subject Pronouns, Gender and Number Agreement, Linking Nouns with Other Expressions, The Verb Tener, Verbs that End with -AR, Numbers 1-10, Perspectivas Introduction: La Familia, Perspectivas: La Familia, Perspectivas Summary: La Familia, Module Summary
Module Introduction, Introduction to Vocabulario, Introduction to Gramática, The Verb Estar, Expressions for Physical Sensations, -AR, -ER, -IR Regular Verbs, Numbers: 1-100, Perspectivas Introduction: El Cuerpo Enfermo, Perspectivas: El Cuerpo Enfermo, Perspectivas Summary: El Cuerpo Enfermo, Module Summary
Module Introduction, Introduction to Vocabulario, Introduction to Gramática, Ser vs. Estar, The Verb Hay, –AR, -ER, -IR Stem-changing Verbs, Talking About the Weather, Expressing Obligations, Possessive Adjectives, Making Comparisons of Inequality, Perspectivas Introduction: La Plaza Central, Perspectivas: La Plaza Central, Perspectivas Summary: La Plaza Central, Module Summary
Course Summary
Course: Les bases de la vente et du marketing avec Goldman Sachs 10,000 Women
Modules:
Bienvenue, Identification des outils marketing adaptés à votre entreprise, Présentation du processus de vente, Comprendre le rôle des packs d’analyses de données
Course: Financial Analysis - Build a ChatGPT Pairs Trading Bot
Modules:
Introduction, Project Scope, Course Tools
How to Succeed in This Course, Where to Get the Code
Pairs Trading Intuition, The Initial Prompt, Correcting the Trading Signal, Correcting the Z-Score Computation, Correcting the Return Computation, Correcting How We Measure Strategy Performance, Returns, Log Returns, Cumulative Returns, More about Log Returns (Optional), Strategy Performance Computation (Optional), Asking ChatGPT for Pairs, Testing the Strategy, Benchmark Against Buy-and-Hold, Fixing the Spread, Extending the Position, Extending the Position (Code), Asking ChatGPT to Fix an Error, More Pairs, Long-Only Strategy, Long-Only Strategy (Code), Return Computation Revisited and Other Extensions (Optional), Return Computation Revisited (Code), Suggestion Box
Mean Reversion Test, Pairs Trading Test
Conclusion and Lessons, ChatGPT Knows Who I Am
Anaconda Environment Setup, How to Install NumPy, SciPy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
How to Code Yourself (Part 1), How to Code Yourself (Part 2), Proof that Using Jupyter Notebook Is the Same as Not Using It, How to Use GitHub and Extra Coding Tips (Optional)
How to Succeed in This Course (Long Version), Is This for Beginners or Experts? Academic or Practical? Fast or Slow-Paced?, What Order Should I Take Your Courses In? (Part 1), What Order Should I Take Your Courses In? (Part 2)
What Is the Appendix?
Course: Acing the Product Management Interview
Modules:
Where the Interviews Are, How to Network, Rules for Networking, Nancy's General Interview Tips
Behavioral Interview Questions 1, Behavioral Interview Questions 2, Behavioral Interview Questions 3, Product Design Interview Questions 1, Product Design Interview Questions 2, Strategy Interview Questions, Execution (Data Analysis) Interview Questions, Technical Interview Questions, Estimation Interview Questions
Mock Google Interview 1 of 5 feat. Bob O'Brien, Mock Google Interview 2 of 5  feat. Bob O'Brien, Mock Google Interview 3 of 5  feat. Bob O'Brien, Mock Google Interview 4 of 5 feat. Bob O'Brien, Mock Google Interview 5 of 5 feat. Bob O'Brien, Mock Amazon Interview 1 of 3 feat. Jenny Tai, Mock Amazon Interview 2 of 3 feat. Jenny Tai, Mock Amazon Interview 3 of 3 feat. Jenny Tai
You're the Top 3%!, Nancy Gessler 1 AWS Certificates, Nancy Gessler 2 Opportunities for PMs to Train, Nancy Gessler 3 Advice to PMs, Nancy Presents Exclusive AWIP Content, Tatyana Mamut 1 @ AWIP Summit, Tatyana Mamut 2, Tatyana Mamut 3, Tatyana Mamut 4, Tatyana Mamut 5, Sandy Carter 1 Origins, Sandy Carter 2 Building Your Authentic Brand, Sandy Carter 3 Wisdom from Sandy's Books, Au Revior!
Course: Security Operations Center (SOC)
Modules:
Introduction to Security Operations Center, SOC Defined, SOC Environment Today, Goal of a SOC, Challenges of a SOC, Wrap-Up
Introduction to Security Operations Center Processes and Services, SOC Interaction with Other Departments, Common SOC Services, Wrap-Up
Introduction to SOC Deployment Models and Types, SOC Types and Staffing Considerations, SOC Models and Their Consumers, Wrap-Up
Introduction to Staffing an Effective SOC Team, SOC Roles, Interaction of Various Roles Within the SOC, Wrap-Up
Introduction to Security Events Data and SOC Analyst Tools, SOC Relevant Data and Security Event Data Introduction, SOC Tools and Their Features, SOC Tools and Their Features (Cont.), Wrap-Up
Introduction to Developing Key Relationships with Internal and External Stakeholders, Internal Stakeholders, External Stakeholders, Wrap-Up
Introduction to Understanding SOC Metrics, Security Data Aggregation, Time to Detection, Security Controls Detection Effectiveness, SOC Metrics, Wrap-Up
Introduction to Understanding SOC Workflow and Automation, SOC WMS Concepts, Incident Response Workflow, SOC WMS Integration, SOC Workflow Automation Example, SOC Workflow Automation Example, Wrap-Up
Course: Practice Exam for Certified Scrum Master (CSM) Certification
Modules:
Course Introduction, CSM Overview and Domains, Exam Testing Strategies
Exam Instructions, Congratulations and Next Steps, Thanks from the Course Team
Course: Introdução à Ciência da Computação com Python Parte 1
Modules:
A quem se destina este curso, Como aproveitar este curso ao máximo, O que é Ciência da Computação?, Instalação do python3 e IDLE no Windows, Dica - Como reparar a instalação do Python no Windows, Instalação do python3 e IDLE no Linux, Linha de comando no Windows, Introdução ao Python, Variáveis e Primeiro Programa, Quatro maneiras de rodar o python, Software Livre – com Nelson Posse Lago, gerente técnico do CCSL
Tipos de Dados, Entrada de Dados, Enviando exercícios para o corretor automático
Expressões Booleanas, Execução Condicional, Exercício Resolvido
Repetição com while, Variáveis Booleanas, Depurador
Funções, Resolução de Exercício e Testes, Testes Automatizados - Introdução ao pytest, Música "Melô do Teste Automatizado" e Entrevista com Daniel Cukier
Exercício Resolvido, Depurador, Dicas sobre o Jogo do NIM
Repetições Encaixadas, Exercício Resolvido, Exercício Resolvido, Exercício Resolvido
Listas, Repetição com "for", Manipulação de Listas
Objetos na Memória, Exercício Resolvido, Dicas para o exercício final!
Course: Natural Language Processing in TensorFlow
Modules:
Introduction: A conversation with Andrew Ng, Introduction, Word based encodings, Using APIs, Notebook for lesson 1, Text to sequence, Padding, Out-of-Vocabulary Words, Notebook for lesson 2, Sarcasm, really?, Preprocessing the Sarcasm dataset, Notebook for lesson 3, Week 1 Wrap up
A conversation with Andrew Ng, Introduction, The IMDB dataset, Looking into the details, How can we use vectors?, More into the details, Notebook for lesson 1, Remember the sarcasm dataset?, Building a classifier for the sarcasm dataset, Let’s talk about the loss, Subword tokenization, Diving into the code
A conversation with Andrew Ng, Introduction, LSTMs, Implementing LSTMs in code, Accuracy and loss, A word from Laurence, Looking into the code, Using a convolutional network, Going back to the IMDB dataset, Tips from Laurence
A conversation with Andrew Ng, Introduction, Looking into the code, Preparing the training data, More on the training data, Finding what the next word should be, Example, Predicting a word, Notebook for lesson 1, Poetry!, Looking into the code, Laurence the poet!, Your next task, A conversation with Andrew Ng
Course: Fundamentals of Data Governance
Modules:
Course Introduction, Emergence of Data Governance, Introduction to Data Governance, Challenges and Benefits of Data Governance, Importance of Data Governance, Key Elements of Data Governance, Data Governance Framework, Data Admin, Data Steward, Data Custodian and Users, Data Security, Steps to Implement Data Governance, Data Governance Tools, Overview of Data Governance in the Cloud, Overview of Data Governance with Google Cloud, Overview of Data Governance with AWS, Overview of Data Governance with Azure, Getting started with Amazon DataZone Demonstration Part-1, Getting started with Amazon DataZone Demonstration Part-2, Getting started with Amazon DataZone Demonstration Part-3, Getting started with Amazon DataZone Demonstration Part-4, Getting started with Amazon DataZone Demonstration Part-5, Getting started with Amazon DataZone Demonstration Part-6, Getting started with Amazon DataZone Demonstration Part-7
Course: Security and Privacy for Big Data - Part 2
Modules:
Social costs of Big Data, Anonymizing and pseudonymizing data, Differential Privacy, Differential Privacy methods, Homomorphic encryption, Secure Multiparty Computation, Data Protection Law for Big Data, General Data Protection Regulation (GDPR), Important changes resulting from the GDPR, Personal Data, Personal data and Big Data applications
Course: GenAI for Product R&D Teams
Modules:
Introduction to GenAI for Product R&D Teams, The GenAI Future-Ready Framework for Product R&D Teams, Ethical Concerns and Remediating Risks, Demo for Creating an App Using Various GenAI Tools, Closing Thoughts: What’s Next
Course: Scandinavian Film and Television
Modules:
1.1: Scandinavian cinema and the welfare state, by Professor Ib Bondebjerg, 1.2: Scandinavian cinema: trends and international impact, by Professor Ib Bondebjerg, 1.3: Scandinavian television culture, by Professor Ib Bondebjerg, 2.1: The establishing of early cinema in Scandinavia, by Associate Professor Casper Tybjerg, 2.2: The golden age of Swedish cinema and Dreyer, by Associate Professor Casper Tybjerg, 2.3: Sound film and Dreyer's career as filmmaker, by Associate Professor Casper Tybjerg
3.1: Bergman and the modern art cinema, by Associate Professor Johannes Riis, 3.2: Bergman's film: Themes and style, by Associate Professor Johannes Riis, 3.3: Chamber films, Persona and the influence of Strindberg, by Associate Professor Johannes Riis, 4.1: Lars von Trier: The Early Years, by Associate Professor Peter Schepelern, 4.2: Dogma 95, by Associate Professor Peter Schepelern, 4.3: Lars von Trier: The Later Years, by Associate Professor Peter Schepelern
5.1: Birth of new wave cinema, by Associate Professor Birger Langkjær, 5.2: Scandinavian new wave: Main tendencies, by Associate Professor Birger Langkjær, 5.3: Scandinavian new wave auteurs, by Associate Professor Birger Langkjær, 6.1: And the Winner is ... Scandinavian heritage films, by Professor Ib Bondebjerg, 6.2: Contemporary Scandinavian film success, by Professor Ib Bondebjerg, 6.3: Modern Scandinavian art films, by Professor Ib Bondebjerg
7.1: Discovering reality on film: The early documentary, by Professor Ib Bondebjerg, 7.2: A new look at reality: The modern Scandinavian documentary, by Professor Ib Bondebjerg, 7.3: Documentary in a global and digital world, by Professor Ib Bondebjerg, 8.1: A medium for education: Early television drama, by Professor Ib Bondebjerg, 8.2: The birth of modern television drama, by Professor Ib Bondebjerg, 8.3: Stories by instalment: Television and serial narratives, by Professor Ib Bondebjerg
9.1: Scandinavian television drama after the millennium, by Associate Professor Eva Novrup Redvall, 9.2: Danish public service television drama in the 2000s, by Associate Professor Eva Novrup Redvall, 9.3: Scandi-Crime and Nordic Noir, by Associate Professor Eva Novrup Redvall, 10.1: The birth of a global online culture, by Professor Ib Bondebjerg, 10.2: Is Nordic globally cool?, by Professor Ib Bondebjerg, 10.3: Towards new horizons: Transnational futures, by Professor Ib Bondebjerg
Course: Customer Analytics
Modules:
Course Introduction and Overview, Overview of the Business Analytics Specialization
What is Descriptive Analytics?, Descriptive Data Collection: Survey Overview, Descriptive Data Collection: Net Promoter Score and Self-Reports, Descriptive Data Collection: Survey Design, Passive Data Collection, Media Planning, Causal Data Collection and Summary
Introduction to Predictive Analytics, Asking Predictive Questions, Regression Analysis, Part 1, Regression Analysis, Part 2, Beyond Period 2, Making Predictions Using a Data Set, Data Set Predictions: Mary, Sharmila, or Chris?, Probability Models, Implementation of the Model, Results and Predictions, Zodiac Story, Model Extensions, Surprising Applications, Machine Learning, Customer-Based Corporate Valuation (CBCV), CBCV Case Study: Farfetch
Introduction, What is Prescriptive Analytics?, Using the Data to Maximize Revenue, Parameters of the Model, Market Structure, Competition and Online Advertising Models, Conclusion(s)
Introduction to Application to Analytics, The Future of Marketing is Business Analytics, The Golden Age of Marketing, Applications: ROI, Radically New Data Sets in Marketing, The Perils of Efficiency, Analytics Applied: Kohl's, NetFlix, AmEx and more, Conclusion
Course: Introduction to Python Functions
Modules:
Course Overview, Why Do We Need Functions?, What Are Functions?, Let's Define Functions
What Are Parameters?, Exercise: Define Functions with a Single Parameter, What Are Multiple Parameters?, Exercise: Define Functions with Multiple Parameters, Calling Functions with Keyword Arguments
What Are Return Values?, Exercise: Define Functions with Return Values
Introduction to Nested Functions, Exercise: Define Functions calling Functions, The Design of Hierarchy of Functions, Recursive Functions
Course: Data Visualization and Transformation with R
Modules:
Welcome, Code along :: My first data visualization - UN Votes, Meet the toolkit: R + RStudio, Meet the toolkit: Quarto
Visualizing data, Building a plot step-by-step with ggplot2, Code along :: First look at Palmer Penguins, Grammar of graphics
Grammar of data transformation, Code along :: Flights and pipes, Visualizing and summarizing categorical data, Code along :: StarWars characters, Visualizing and summarizing numerical data, Visualizing and summarizing relationships between variables, Code along :: Diving deeper with Palmer Penguins, Meet the toolkit: Git + GitHub
Course: Human Rights for Open Societies
Modules:
Open societies and the ECHR, The foundations of the ECHR, The admissibility requirements
How does the ECtHR consider a fundamental rights case?, The principles and methods of interpretation, Categories of rights in the ECHR and possibilities for limitation, Conditions for restriction of ECHR rights, The intensity of review of restrictions and the margin of appreciation doctrine
The protection of human rights in a democratic society, Political parties, Human rights in transitions to democracy
The ECHR and the universal protection of human rights, Non-discrimination, Vulnerable groups, The rights of migrants and asylum seekers under the ECHR
Freedom of expression in a democratic society, The ECHR and the role of the media, The freedom of public protest
Final Survey
Course: Global Marketing: Building Iconic Brands
Modules:
Welcome to Global Marketing: Building Iconic Brands!, Meet Professor Carlos Torelli, Meet Professor Sharon Shavitt, Learn on Your Terms
Module 1 Overview, Module 1 Introduction, Key Global Marketing Actions: What is Global Marketing?, Understanding the New Market: Environmental Analysis, Sizing the New Market, Culture and Consumer Behavior
Module 2 Overview, Module 2 Introduction, Brands as Associative Networks in Memory, Brand Equity, Cultural Equity, The Brand Audit
Module 3 Overview, Module 3 Introduction, Consumers’ Reactions to Cultural Meanings in Brands, Crafting a Cultural Positioning, Choosing Products for a Culturally Focused Marketing Plan, Communicating a Cultural Positioning Part 1, Communicating a Cultural Positioning Part 2, Channel and Pricing Decisions to Reinforce a Cultural Positioning
Module 4 Overview, Module 4 Introduction, Integrating the Global Marketing Plan: Standardization vs. Adaptation, Standardization: Why and When to Use it?, Adaptation: Why and When to Use it?, Strategies to Deal with a Negative Country Image
Course: Effective Onboarding
Modules:
Introduction to Effective Onboarding, Defining Onboarding, Onboarding vs. Orientation, Benefits of an Effective Onboarding Program, Impact of a Poor Onboarding Program
Intro to an Effective Onboarding Program, Qualities of an Effective Onboarding Program, Missing the Mark, 8 Steps to Build an Effective Onboarding Program, Thanks!
Course: Organisational design: Know your organisation
Modules:
Course welcome and introduction, Week 1 outline, Organisational alignment, The importance of key capabilities, How to identify key capabilities, Value chain analysis, Habit corner 1
Week 2 outline, What is organisational culture?, Why organisational culture is important, Types of organisational culture, Levers of cultural change
Week 3 outline, Key trade-offs in organisational structure, Types of organisational structure, Advantages and disadvantages of different structure types
Week 4 outline, The four types of control systems, The balanced score card
Week 5 outline, A strategic approach to HRM, Strategic workforce segmentation, Apply a strategic workforce segmentation diagnostic tool
Week 6 outline, From critical issues to possible solutions, Risk assessment of proposed solutions
Course: Managing Google Workspace - Português Brasileiro
Modules:
Apresentação e guia para iniciantes, Visão geral dos serviços do Google Workspace, Introdução ao Gmail, Introdução ao app Agenda, Introdução ao Drive e ao app Documentos, Gerenciar dispositivos móveis, Gerenciar outros dispositivos, Segurança aprimorada para computadores com Windows, Introdução ao Google Vault, Introdução aos relatórios, Introdução a domínios, Importar e exportar dados, Solução de problemas do Google Workspace, Recapitulação
Course: Interactive Computer Graphics
Modules:
Course Preview, Introduction, 1-1 Scrolling Interface, 1-2 Desktop Icons, 1-3 Pointing, 1-4 Digital Ink, 1-5 Voice Interaction
2-1 Diagram Beautification, 2-2 Pen-and-ink Textures, 2-3 Shape Manipulation, 2-4 Dynamic Illustrations
3-1 Suggestive Interface, 3-2 Sketch-based Modeling, 3-3 Shape Control by Curves, 3-4 Flower Modeling, 3-5 Volumetric Textures
4-1 Clothing Manipulations, 4-2 Layer Operations, 4-3 Spatial Key Framing, 4-4 Procedural Deformation, 4-5 Motion Database
5-1 Plush Toys, 5-2 Beadworks, 5-3 Chairs, 5-4 Soft Folding, 5-5 Interactive Packing
6-1 Cantilever, 6-2 Musical Instruments, 6-3 Garments, 6-4 Furniture, 6-5 Gliders
7-1 Command Card Interface, 7-2 Style-by-Demonstration, 7-3 Actuated Puppet, 7-4 Robotic Light, 7-5 Fur Display, Concluding Remarks
Course: IELTS Listening and Speaking Sections Skills Mastery
Modules:
Meet Your Teacher, Listening: Sections 1 & 2 (Part 1), Listening: Sections 1 & 2 (Part 2), Listening: Sections 1 & 2 (Part 3), Listening: Sections 3 & 4 (Part 1), Listening: Sections 3 & 4 (Part 2)
Speaking (Part 1), Speaking (Part 2), Speaking (Part 3)
Listening & Speaking Tips (Part 1), Listening & Speaking Tips (Part 2), Listening & Speaking Tips (Part 3)
Course: Aspectos básicos de la planificación y la gestión de proyectos
Modules:
Bienvenida del curso, ¿Qué es un proyecto?, ¿Cómo definimos un proyecto?, Cómo tener en cuenta la organización y las partes interesadas, El éxito y el fracaso de un proyecto, El resumen de cómo se hizo Boyhood y la T5 de British Airways, El resumen de cómo se hizo Boyhood y la T5 de British Airways, La vida útil de un proyecto
¿Por qué planificar?, Cómo examinar al detalle, Cómo identificar las dependencias, Cómo determinar la fecha de finalización y la ruta crítica, ¿Cómo programamos?, ¿Qué pasa si no me gusta planificar? Hacer cambios, Reflexión sobre los errores más comunes, Virginia Festival of the Book (ejemplo práctico adicional), Tutorial adicional: Introducción a Microsoft Project
¿Cuáles son los riesgos de un proyecto?, Cómo identificar y evaluar los riesgos de un proyecto, Una cronología más realista: parte I, Una cronología más realista: parte II, Análisis de los riesgos de costes, Planificación de la ambigüedad, Zumo Lumi (ejemplo práctico adicional), Tutorial adicional: Cómo modelar las incertidumbres del programa, parte I - Gráficos de tornado en Microsoft Excel, Tutorial adicional: Cómo modelar las incertidumbres del programa, parte II - Simulaciones Monte Carlo en Microsoft Excel
Del plan a la acción, Valor acumulado, Aquellos que ejecutan, Ágil, Scrum y Kanban, Tutorial adicional: Cómo hacer un seguimiento del progreso y actualizar el plan de proyecto en Microsoft Project, Gestión de proyectos en el mundo real, Gestión de proyectos: caso n.º 143, Gestión de proyectos: caso n.º 168, Conclusión del curso
Course: The Control Phase for the 6 σ Black Belt
Modules:
Understanding Statistical Process Control (5:29), Rational Subgrouping (5:46), Sources of Variation (3:37)
Variables Charts (9:44), Moving Average and Individual Charts (4:00), Attribute Charts with Constant Subgroup Size (3:19), Attribute Charts with Variable Subgroup Size (2:50), Short Run Charting Methods (5:03), Identifying Special Causes of Variation (6:08)
Maintenance Programs (4:35), Assessing Total Productive Maintenance (6:50)
Understanding the Control Phase (4:15), The Control Plan (6:15), Pre-Control (3:24)
Postmortem (3:16), Document Management (4:59), Training (3:04), Ongoing Evaluation (2:08)
Course 7 Summative Quiz
Course: GenAI for Business Intelligence Analysts
Modules:
Introduction to GenAI for Business Intelligence Analysts, History & Background For GenAI and Business Intelligence Analysts, Demo for Analysis of Competitor Data Using Claude 2, Remediating Risks and Ethical Concerns, Demo for Market Trend Identification with Claude 2, Closing Thoughts: What’s Next