dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: New Learning: Principles and Patterns of Pedagogy
Modules:
Syllabus, Task Overview: How to Pass This Course, About the Discussion Forums, Take This Course As a Stepping Stone for a University of Illinois Certificate, Masters, or Doctorate - Fully Online!, Course Readings, Updating Your Profile, Social Media
What Is New Learning?, Teaching As an Art and Science, Learning and Education: Defining the Key Terms, Formal and Informal Learning, Learning Community, Curriculum, and Pedagogy, Modern Educational Institutions, Models of Pedagogy, What Kind of Science Is Education?, Education As the Science of Coming-to-Know, Changing Social Contexts of Learning, The Profession of Education, Contemporary Social Contexts of Education, Changing Roles for the Teacher, Changing Sites of Learning, Education As Designs for Social Futures
Models of Pedagogy: Didactic, Authentic, and Transformative, Dimensions of Pedagogy, Didactic Pedagogy, As Felt Subjectively, Analyzing Didactic Pedagogy Part 1, Analyzing Didactic Pedagogy Part 2, Didactic Pedagogy Today, The Origins of Authentic Pedagogy, Analyzing Authentic Pedagogy Part 1, Analyzing Authentic Pedagogy Part 2, Critiques of Authentic Pedagogy
The Social Context of Transformative Pedagogy, Education to Transform the Conditions of Individual and Social Life, Analyzing Transformative Pedagogy Part 1, Analyzing Transformative Pedagogy Part 2, Analyzing Transformative Pedagogy Part 3
Course: Writing and Editing: Word Choice and Word Order
Modules:
Good with Words, Making You More Persuasive, Errors and Insights, Mechanics and Strategy, Map to a Decision, Saints vs. Jerks, Better at Getting Better, S.M.A.R.T. Goals and Stretch Goals, Résumé Review, 6-60-6, Technical and Tactical, Punctuation and Professionalism, Punctuation and Professionalism: Comma Splices, Notes on Nuance: "Un-", Good Sentences, Reflection is a Team Sport, Student Takeaway: Words Under the Words, Student Takeaway: Better at Getting Better, Student Takeaway: T-Shaped, Student Takeaway: 6-60-6, Student Takeaway: Writing as Mapping
Previously On, Previously On: The Words Under the Words, Previously On: Deliberate Practice, Previously On: Mechanics and Strategy, Writing as Redecorating, The Infinite Power of Grammar, The Animal Farm Principle, Punctuation and Professionalism: "However", Notes on Nuance: "Almost" and "Even", Takeaways, Student Takeaway: Passive on Purpose, Student Takeaways: Positive No
Previously On, Previously On: Syntax, Previously On: The Animal Farm Principle, The Rule of Three, Punctuation and Professionalism: Adverbial Conjunctions, Notes on Nuance: "To", Takeaways, Student Takeaway: Rule of Three
Previously On: Interleaving and "To", Previously On: "Interleaving", Previously On: "To", The Power of the Particular, What Makes a Word "Real"?, Sentences Nobody Else Can Write, Sentences Nobody Else WOULD Write, S-H-A-P-E, Class Clip: The S-H-A-P-E Framework, Punctuation and Professionalism (Coordinating Conjunctions), Notes on Nuance: Chiasmus, Student Takeaway: Earn Your Generalizations, Student Takeaway: Sincerity Takes a Few Drafts, Next Course: Writing is a Superpower
Course: Interpretable Machine Learning
Modules:
Introduction to Interpretable ML, Linear Regression, Logistic Regression, Generalized Linear Models, Generalized Additive Models
Decision Trees, Sparse Decision Trees, Decision Rules, RuleFit, Neural Network Interpretability, Protoype-based Neural Networks (ProtoPNet), Monotonic Neural Networks (MonoNet), Kolmogorov-Arnold Networks
Introduction to Mechanistic Interpretability, Mechanistic Interpretability Concepts, Introduction to Circuits, The Superposition Hypothesis, Mechanistic Interpretability Representation Learning, Scaling Mechanistic Interpretability to LLMs
Course: Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
Modules:
Layers of Cellular Regulation and Omics Technologies, The Connectivity Map, Geometrical View of the Connectivity Map Concept, LINCS Data and Signature Generation Centers, BD2K-LINCS Data Coordination and Integration Center, Induced Pluripotent Stem Cells (iPSCs), Introduction to LINCS L1000 Data, L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo
Introduction to Metadata and Ontologies | Part 1, Introduction to Metadata and Ontologies | Part 2
Accessing and Serving Data through RESTful APIs | Part 1, Accessing and Serving Data through RESTful APIs | Part 2
Analyzing Big Data with Computational Pipelines
The Harmonizome Concept, Processing Datasets | Part 1, Processing Datasets | Part 2, Processing Datasets | Part 3
Data Normalization | Part 1, Data Normalization | Part 2
Data Clustering | Part 1 | Introduction, Data Clustering | Part 2 | Distance Functions, Data Clustering | Part 3 | Algorithms and Evaluation
Midterm Exam
Enrichment Analysis | Part 1, Enrichment Analysis | Part 2, Enrichr Demo
Introduction to Machine Learning | Part 1, Introduction to Machine Learning | Part 2, Introduction to Machine Learning | Part 3
Benchmarking | Part 1, Benchmarking | Part 2
Interactive Data Visualization with E-Charts, Visualizing Data using Interactive Clustergrams Built with D3.js | Part 1, Visualizing Data using Interactive Clustergrams Built with D3.js | Part 2, Visualizing Data using Interactive Clustergrams Built with D3.js | Part 3
Microtasks and GEO2Enrichr Demo, L1000-2-P100 Megatask Challenge
Final Exam
Course: Fundamentos de la escritura académica
Modules:
Bienvenida al curso / Tipología textual, 3 pasos para el aprendizaje del Siglo XXI, Etapas de un alumno en la modalidad virtual
Texto narrativo
Tesis general y macroestructura del texto argumentativo, Argumentos y evidencias, Tipos de argumentos
Estructura de un argumento, Cierre del curso
Course: Fundamentals of Finance
Modules:
Course Introduction (1:24), Present Value Concepts (7:39), NPV Rule (10:39), Separation Theorem (2:06), Simple vs. Compound Interest (7:56), Annuities and Perpetuities (12:40), Growing Delayed Annuities and Perpetuities (7:45), Compounding Within the Year and the Effective Annual Interest Rate (13:59)
Introduction to Fixed Income Valuation (4:53), Valuation of Pure Discount Bonds (6:06), Yield to Maturity vs. Holding Period Return (13:11), Prices and Returns on Coupon Bonds (17:17), Semi-Annual Bonds (6:27), The Yield Curve (16:50)
Introduction Equity Valuation (9:50), Applying Infinite Horizon Formulas (4:06), Determining Dividend Growth (17:32)
Definition of Internal Rate of Return (IRR) (11:18), Comparing NPV and IRR: Accept or Reject Decision (9:34), Comparing NPV and IRR: Exclusive Projects (13:15), Course Conclusion (0:36)
Capital Budgeting in Practice, Expected Returns and Risk, Portfolio Analysis, Capital Asset Pricing Model (CAPM), Market Efficiency, Capital Structure, Valuation and Capital Budgeting with Leverage, Option Definitions and Strategies, Option Valuation
Course: Introduction to AWS
Modules:
AWS Overview, Gartner Research, Cloud Architecture Design Principles, Well-Architected Framework, Operational Excellence, Security, Reliability, Performance Efficiency, Cost Management, DEMO: Setting up an AWS Account, Availability Zones and Regions, CloudFront Infrastructure, Edge Locations, Networking and Content Delivery Services, Virtual Private Cloud (VPC), VPC Peering, VPC End Points, Domain Name System (DNS), CDN, CloudFront Infrastructure, Elastic Load Balancer, ELB Types, Compute Services, What Is EC2?, EC2 Benefits and Features, EC2 Creation Steps, Amazon Machine Image (AMI), EC2 Instance Types, EC2 Creation Steps (Continue), AWS CLI, EC2 Auto Scaling, Elastic Beanstalk, DEMO: Launching EC2 Instance Using AWS Console, DEMO: Launch an EC2 Instance Using AWS CLI
Course: Game Theory II: Advanced Applications
Modules:
An Introduction to the Course, 1.1 Social Choice: Taste, 1.2 Social Choice: Voting Scheme, 1.3 Paradoxical Outcomes, 1.4 Impossibility of Non-Paradoxical Social Welfare Functions, 1.5 Arrow's Theorem, 1.6 Impossibility of Non-Pardoxical Social Choice Functions, 1.7 Single-Peaked Preferences
2.1 Mechanism Design: Taste, 2.2 Implementation, 2.3 Mechanism Design:  Examples, 2.4 Revelation Principle, 2.5 Revelation Principle: Examples, 2.6 Impossibility of General Dominant-Strategy Implementation, 2.7 Transferable Utility, 2.8 Transferable Utility Example, 2.9 Mechanism Design as an Optimization Problem
3.1 VCG: Taste, 3.2 VCG: Definitions, 3.3 VCG: Examples, 3.4 VCG: Limitations, 3.5 VCG: Individual Rationality and Budget Balance in VCG, 3.6 VCG: The Myerson-Satterthwaite Theorem
4.1 Auctions: Taste, 4.2 Auctions: Taxonomy, 4.3 Bidding in Second-Price Auctions, 4.4 Bidding in First-Price Auctions, 4.5 Revenue Equivalence, 4.6 Optimal Auctions, 4.7 More Advanced Auctions
FINAL EXAM
Course: Computational Thinking for K-12 Educators: Nested If Statements and Compound Conditionals
Modules:
Welcome!, Optional: The Computational Thinking & Block Programming in K-12 Education Specialization
In My Life: Nested Ifs, (Optional) Writing Programs: What's Special for Teachers?, Debugging: Nested If Else Statements
Classroom Discussions: Nested If Else Statements, Introducing: pencilcode.net -- a different (free) block based programming language, Optimize Your Fortune!
Compound Conditionals in Soccer, Debugging: Compound Conditionals
Classroom Discussions: Compound Conditionals, Scratch: Programming Because You Want To, Introducing: Soccer in Scratch!
What we know about debugging in block based languages, From CS Teacher to CS Education Leader
Course: Beyond Silicon Valley: Growing Entrepreneurship in Transitioning Economies
Modules:
Course Welcome and Overview
Role of Government
Role of Philanthropy/Donors
Role of Intermediary Organizations/NGOs
Leveraging Anchor Institutions
Seed Accelerators, Angel Investing, Venture Capital
Course Wrap-Up
Course: Python for the Absolute Beginner
Modules:
Course Introduction, Objectives
Python Introduction, Print Function, Literals, Operators, Variables, Comments, Input, String Methods
Comparison Operators, Conditional Statements
Loops - while, Loops - for
Logic Operators, Bitwise Operators
Lists, Lists - Methods, Iterating Lists, Understanding Lists, Slicing Lists, Finding in Lists, Nested Lists - 2D, Nested Lists - 3D
Functions, Arguments, Return Statement, List as Argument, Scopes, Arguments Explained
Tuples, Dictionaries
Exploring Python Error Handling, Understanding the Exception Hierarchy
Python Internals, Conclusion
Course: Machine Design Part I
Modules:
Module 1: Course Overview, Module 2: How to Succeed in this Course, Module 3: Strength, Module 4: Modulus of Elasticity - Introduction, Module 5: Modulus of Elastricity - Applications, Module 6: Ashby Plots, Module 7: Material Selection in Hip Implant, Module 8: Common Metals in Design, Module 9: Metal Designations and Processing, Module 10: Temperature Effects and Creep, Module 11: CTE mismatch
Module 12: Review of Stress, Strength, and Factor of Safety, Module 13: Factor of Safety Example, Module 14: Axial and Torsional Stress Review, Module 15:  Axial, and Torsional Stress Example, Module 16: Bending Stress Review, Module 17: Bending Stress Example, Module 18: Transverse Shear Review, Module 19: Transverse Shear Example
Module 20: Ductile to Brittle Transition Temperature, Module 21: Stress Concentration Factors, Module 22: Static Failure Theories, Module 23: Distortion Energy Theory (von Mises Theory), Module 24: Simple Example Distortion Energy Theory, Module 25: Complex Example Distortion Energy Theory, Module 26: Case Study - Static Load Analysis, Module 27: Brittle Coulomb Mohr Theory, Module 28: Brittle Coulomb Mohr Theory Example
Module 29: Introduction to Fatigue Failure, Module 30: Fatigue and the SN Curve, Module 31: Approximating the SN Curve, Module 32: Estimating the Endurance Limit, Module 33: Estimating the Endurance Limit - Example Problem, Module 34: Fatigue Stress Concentration Factors Part I, Module 35: Fatigue Stress Concentration Factors Part II, Module 36: Fatigue Fully Reversed Loading Example
Module 37: Fatigue Case Study - Aloha Airlines Flight 243 Failure, Module 38: Fatigue Fluctuating Stress, Module 39: Fatigue Goodman Diagram, Module 40: Fatigue Goodman Diagram Example, Module 41: Fatigue Goodman Diagram Example (Life), Module 42: Randomly Varying Stresses and Miner's Rule, Module 43: Randomly Varying Stresses and Miner's Rule Example 1, Module 44: Randomly Varying Stresses and Miner's Rule Example 2
Course: Linear Algebra: Linear Systems and Matrix Equations
Modules:
Systems of Linear Equations, Row Reduction and Echelon Form
Vector Equations, Matrix Equations, Solution Sets of Linear Systems
Linear Independence, Introduction to Linear Transformations, The Matrix of a Linear Transformation
Linear Systems and Matrix Equations
Course: Amazon Kinesis Video Streams - Getting Started
Modules:
Amazon Kinesis Video Streams - Getting Started
Course: Hands-on with AWS for IT Professionals
Modules:
Welcome to the Course, Creating an AWS Account, Creating an Administrative User, The AWS Free Tier, Week 1 Wrap-Up
Week 2 Introduction, Grouping Roles by Affinity, A Data Scenario, Hands-on Activity for Data, An Operations Scenario, Hands-On Activity for Operations, An Architecture Scenario, Hands-On Activity for Architecture, Where to go next?, Course and Series Wrap-Up
Course: Healthcare Data Quality and Governance
Modules:
Course Introduction, Module 1 Introduction, Why Data is Collected and Defining Quality, Why Data Quality Matters, Part 1, Why Data Quality Matters, Part 2, How Data Quality Assessment Varies in Different Data Uses
Module 2 Introduction, Describing Metadata in Healthcare, Data Provenance in Healthcare, Components of Data Quality, Data Validation Methods, A Framework for Validating and Verifying Data, The SBAR Methodology
Module 3 Introduction, Establishing the Culture of Quality throughout the Data Lifecycle, Improving Data Quality from the Baseline, Managing Data Quality: Expected and Unexpected Changes, Monitoring Strategies Along the Data Pipeline
Module 4 Introduction, Defining Data Governance in Healthcare, Why Data Governance Matters in Healthcare, Data Governance Committees in Healthcare, Data Governance Systems in Healthcare, Course Summary
Course: Anticoagulación
Modules:
Promocional, Introducción al curso, Introducción al módulo 1, Farmacología y su relación con los anticoagulantes, Seguridad y eficacia de los noacs en TVP y FA
Introducción al módulo 2, Fisiopatología, indicaciones y contraindicaciones de la anticoagulación en fibrilación auricular, Anticoagulación en poblaciones especiales
Intoducción al módulo 3, Lo que hay que saber de la enfermedad tromboembólica venosa, ¿A quien dar alta temprana en TVP?, Entrevista: TVP en paciente oncológico y síndrome antifosfolípido
Introducción al módulo 4, La anticoagulación en la embolia pulmonar
Introducción al módulo 5, Manejo periprocemimento de la anticoagulación, Cierre del curso
Course: Establishing Command-and-Control and Finding Credentials
Modules:
Introduction to Command-and-Control, Traffic Analysis with Python, Calculating Entropy with Python, Detecting Encodings with Python, Building C2 Packets with Python
Introduction to Credential Access, Dumping Chrome Credentials with Python, Searching the Registry with Python, Searching the System with Python, Cracking the Linux Passwords with Python, Analyzing Passwords with Python
Course: Transformer Models and BERT Model - Bahasa Indonesia
Modules:
Model Transformer dan BERT: Ringkasan, Model Transformer dan BERT: Panduan Lab
Course: Building High Quality User Experience Using Material UI
Modules:
Context Setting, Style a React Component using an External StyleSheet​, Watch and Repeat : Adding Styles to React Component using External CSS file, Make use of a CSS Module to Style a React Component ​, Watch and Repeat : Adding Styles to React Component using CSS file as module, Apply Inline Styles to React Components, Watch and Repeat : Adding Styles to React Component using Inline Style, Style a React Component using Styled-Component Module which follows CSS in JavaScript Pattern​, Watch and Repeat : Apply CSS-in-JS concept in React Component, Practice Brief, Practice Debrief, Learning Consolidation
Context Setting, Material Design Philosophy​, Watch and Repeat : How to Install Material and use it’s Prebuilt Component in React App, Layout Components​, Watch and Repeat : Implementing Layout Component of Material, Input Components​, Watch and Repeat : Implementing Input Components of Material, Navigation Components​, Watch and Repeat : Implementing Navigational Components of Material, Surface Components​, Watch and Repeat : Implementing Surface Components of Material, Theming Components, Watch and Repeat : Implementing Custom Theme in Material Design, Material UI Hooks, HOCs​, Watch and Repeat : Customizing Material prebuilt Components using Hooks and API, Practice Brief, Practice Debrief, Challenge Brief, Challenge Debrief, Learning Consolidation
Course: Shaping Your Professional Brand
Modules:
Welcome to Shaping Your Professional Brand!
1.0.1: 2MC: Brand Manager, 1.1.1 Being Valued at Work, 1.2.1: 2MC: Kidney Donation, 1.3.1 First: Listen, 1.3.2 2MC: Meredith's Mother-in-Law, 1.3.3 How Are You Listening?, 1.3.4 Listen to Learn, 1.3.5 What Happened Next? Meredith’s Mother-in-Law, 1.4.1 Second: Ask Questions, 1.4.2 2MC: Signing Strangers' Names is the Process, 1.4.3 Formulating Questions, 1.4.4 Reciprocity: Questions Shape Answers, 1.4.5 How and What You Ask Affects the Outcome, 1.5.1: Achieving and Sustaining Rapport, 1.5.2: 2MC: Personal Services, 1.5.3: Establishing Rapport, 1.5.4: Paraphrasing, 1.5.5: What Happened Next? Personal Services, 1.6.1: What Happened Next? Kidney Donation
2.1.1 Overview: Likeability Matters, 2.2.1: 2MC: Whose Money Is It?, 2.3.1: Approach Matters, 2.3.2: 2MC: That Parking Space, 2.3.3: Creating Energy, 2.3.4: De-energizers: The Costs, 2.3.5: Your Energy and Approach, 2.4.1: Aligning with Others, 2.4.2: 2MC: Recommend a Friend, 2.4.3: The And Stance: How and Why, 2.4.4: But … Objections to The And Stance, 2.4.5: Experts on The And Stance, 2.5.1: High-Road Go-To Solutions, 2.5.2: 2MC: Charging for Work Before Authorization, 2.5.3: Find Common Ground, 2.5.4: Get It In Writing, 2.5.5: What Happened Next? Charging for Work Before Authorization, 2.6.1: What Happened Next? Whose Money Is It?
3.1.1: We're Not as Rational as We Think We Are, 3.2.1: 2MC: Commission Sales, 3.3.1: It's Not All About You, 3.3.2: 2MC: Face Embarrassment, 3.3.3: Overconfidence and Egocentrism, 3.3.4: Confirmation Bias and Motivated Blindness, 3.3.5 What Happened Next? Face Embarrassment, 3.4.1: There are More Cognitive Biases?, 3.4.2: 2MC: Chen Becomes Uncomfortable at Work, 3.4.3: Stop Digging: Pursuit of Sunk Costs, 3.4.4: Sinister Attribution Bias, 3.4.5: Chen's Situation, First Pass, 3.5.1: Prevention and Recovery: Framing and Reframing, 3.5.2: 2MC: Chen Uncomfortable at Work, Continued, 3.5.3: Framing, 3.5.4: Framing in Chen’s Situation, 3.5.5: Using Reframing as a Tool for Chen, 3.5.6: What Happened Next? Chen Uncomfortable at Work, 3.6.1: What Happened Next? Commission Sales
4.1.1: When Things Go Wrong, 4.2.1: 2MC: Speak Up or Keep Quiet, 4.3.1: Identifying Problems, 4.3.2: 2MC: Leaving Off a Data Point, 4.3.3: Mindset, 4.3.4: Are You Sure You Have a Problem?, 4.3.5: What Happened Next? Leaving Off a Data Point, 4.4.1: When You Are in the Wrong: Professional Apologies, 4.4.2: 2MC: You Messed Up, 4.4.3: The Four Rs of Apologizing: Remorse and Responsibility, 4.4.4: The Four Rs of Apologizing: Rehabilitation and Recompense, 4.4.5: What Happened Next? You Messed Up, 4.5.1: Having Disputes Professionally, 4.5.2: 2MC: Just Don't Hire Anyone Over 40..., 4.5.3: Having Disputes Professionally: Rules One and Two, 4.5.4: Having Disputes Professionally: Rules Three, Four, and Five, 4.5.5: Review - and What Happened Next? Hire No One Over 40, 4.6.1: What Happened Next? Speak Up or Keep Quiet, 4.7.1: Bringing it All Together
Course: GenAI for Sales Development Representatives
Modules:
Introduction to GenAI for Sales Development Representatives, History & Background for GenAI and Sales Development Representatives, Demo for Generating and Qualifying Sales Leads with Copilot, Remediating Risks and Ethical Concerns, Demo for Crafting Personalized Email Templates and Sales Scripts with ChatGPT, Closing Thoughts: What’s Next
Course: Building Batch Data Pipelines on GCP 日本語版
Modules:
コース概要
モジュールの概要, EL、ELT、ETL, 品質に関する考慮事項, BigQuery におけるオペレーションの実行方法, 欠点, データ品質の問題を解決する ETL
モジュールの概要, Hadoop エコシステム, Dataproc での Hadoop の実行, HDFS の代わりとなる Cloud Storage, Dataproc の最適化, Dataproc ストレージの最適化, Dataproc テンプレートと自動スケーリングの最適化, Dataproc モニタリングの最適化, ラボの概要: Dataproc での Apache Spark ジョブの実行, Coursera: Google Cloud Platform と Qwiklabs を使用する, まとめ
モジュールの概要, Dataflow の概要, お客様が Dataflow を重視する理由, コードで Dataflow パイプラインを構築する, パイプライン設計で考慮すべきポイント, PTransforms を使用してデータを変換する, ラボの概要: シンプルな Dataflow パイプラインの構築, GroupByKey と Combine を使用した集約, ラボの概要: Beam での MapReduce, 副入力とデータのウィンドウ, ラボの概要: Dataflow を使用したサーバーレスのデータ分析: 副入力, パイプライン テンプレートの作成と再利用, まとめ
モジュールの概要, Cloud Data Fusion の概要, Cloud Data Fusion の構成, Cloud Data Fusion UI, パイプラインのビルド, Wrangler を使用してデータを探索する, ラボの概要: Cloud Data Fusion でパイプライン グラフを作成して実行する, Cloud Composer を使用して Google Cloud サービス間の作業をオーケストレートする, Apache Airflow 環境, DAG と演算子, ワークフローのスケジュール設定, モニタリングとロギング, ラボの概要: Cloud Composer の概要
コースのまとめ
Google Cloud でバッチデータ パイプラインを構築する
Course: Processar os dados para limpá-los
Modules:
Introdução ao foco na integridade, Por que a integridade dos dados é importante, Como equilibrar os objetivos e a integridade dos dados, Como lidar com a insuficiência de dados, A importância do tamanho da amostra, Como usar a potência estatística, Como determinar o melhor tamanho da amostra, Como avaliar a confiabilidade dos dados
Limpeza geral!, Por que a limpeza de dados é importante, Angie: Por que eu adoro limpar dados, Como reconhecer e limpar dados sujos, Ferramentas e técnicas para limpar dados, Limpe dados de diferentes fontes, Funções de limpeza de dados em planilhas, Otimizar o processo de limpeza de dados, Diferentes perspectivas de dados, Ainda mais técnicas de limpeza de dados
Como usar o SQL para limpar dados, Sally: Por amor ao SQL, Noções sobre recursos SQL, Planilhas versus SQL, Consultas SQL muito utilizadas, Evan: Brincando com SQL, Limpeza de variáveis de string com SQL, Funções avançadas de limpeza de dados, parte 1, Funções avançadas de limpeza de dados, parte 2
Verificar e gerar relatórios dos resultados, Limpeza e expectativas em relação aos dados, A etapa final da limpeza de dados, Registro das mudanças da limpeza, Por que a documentação é importante, Feedback e limpeza
Sobre o processo de contratação de um analista de dados, O processo de candidatura para vagas de analista de dados, Criando um currículo, Como criar um currículo que se destaca, Joseph: A inclusão de negros e afro-americanos no setor de dados, Como traduzir a experiência profissional prévia, Kate: minha carreira como analista de dados, Quais são seus interesses?
Prepare-se para o Desafio do curso, Parabéns!
Course: Crear esquemas de página y prototipos de baja fidelidad
Modules:
Introducción al curso 3: Crear esquemas de página y prototipos de baja fidelidad, Karen: mi recorrido hacia el diseño de UX, Bienvenido a la semana 1, Usa la investigación para determinar la ideación, Craig: la investigación determina la ideación en el mundo real, Crea declaraciones de metas, Introducción a los flujos de usuarios, Introducción a los flujos de usuarios de creación de guiones gráficos, Comprende los dos tipos de guiones gráficos, Introducción a los esquemas de página, Empieza a dibujar, Dibuja tu primer esquema de página, Comprende los beneficios de crear esquemas de página, Actividad de cierre: guiones gráficos y creación de esquemas de página
Bienvenido a la semana 2, Fundamentos de la arquitectura de la información (IA), Crear esquemas de página en papel, Transición de los esquemas de página en papel a los digitales, Introducción a Figma, Crea esquemas de página digitales en Figma, Opcional. Aprende de Figma: Crea esquemas de página para una aplicación, Erika: herramientas del oficio, Utiliza los principios de la Gestalt al crear esquemas de página, Actividad de cierre: Creación de esquemas de página en papel y digitales.
Bienvenido a la semana 3, Más información sobre prototipos de baja fidelidad, Crear un prototipo de papel, Introducción a la construcción de prototipos de baja fidelidad en Figma, Crea prototipos de baja fidelidad en Figma, Opcional. Aprende de Figma: Crea prototipos, Reconocer el sesgo implícito en el diseño, Ayan: Sesgo en el trabajo de diseño UX, Identificar patrones engañosos en el diseño de UX, Explora los efectos de los diseños que engañan, Priya: La importancia del diseño equitativo, Actividad de cierre: Construcción de prototipos de baja fidelidad, Felicitaciones por completar el Curso 3: Crear esquemas y prototipos de baja fidelidad
Course: Deep Learning for Business
Modules:
1.0 Introduction to Deep Learning for Business, 1.1 Future Industry Evolution & Artificial Intelligence, 1.2 IBM Watson, 1.3 Amazon Echo, Echo Dot, Alexa, 1.4 LettuceBot / 1.5 Athelas / 1.6 AIVA (Artificial Intelligence Virtual Artist) / 1.7 Apple watchOS 4, HomePod speaker
2.1 Business Considerations in the Machine Learning Era, 2.2 Business Strategy with Machine Learning & Deep Learning, 2.3 Why is Deep Learning Popular Now?, 2.4 Characteristics of Businesses with DL & ML
3.1 Deep Learning Open Source Software / 3.2 Google TensorFlow, 3.3 Microsoft CNTK (Cognitive Toolkit) / 3.4 NVIDIA DGX-1, 3.5 Google AlphaGo, 3.6 ILSVRC (ImageNet Large Scale Visual Recognition Challenge)
4.1 What is Deep Learning & Machine Learning?, 4.2 NN (Neural Network), 4.3 Neural Network Learning (Backpropagation)
5.1 Deep Learning with CNN (Convolutional Neural Network), 5.2 Deep Learning with RNN (Recurrent Neural Network)
6.1 Introduction to TensorFlow Playground, 6.2 Project Setup, Project 1, and Project 2, 6.3 Project 3 and Project 4
Course: Disaster Recovery Planning for Organizations
Modules:
What are Disaster Recovery Plans?, BIA - Business Impact Analysis & Risk Assessments, RTO vs RPO, DRP Logistics, Backup Recovery Strategies, Testing and Exercises, What are the DRP Best Practices?, What Industry Standards should DRP's Follow?, How to Develop a DRP (Part 1), How to Develop a DRP (Part 2), How to Develop a DRP (Part 3), How to Implement a DRP, How to Maintain a DRP
Course: CBRS Professional Training
Modules:
Introduction, Citizens Broadband Radio Service and shared spectrum, CBRS ecosystem
The role of CPIs in CBRS
SAS-CBSD Communication
When is a CPI required?, Determining installation  parameters, Determining antenna orientation and characteristics, Getting information from the CPI to the SAS, Google's SAS Portal, What can go wrong?
Steps to become a CPI
Course: Hybrid Connectivity and Network Management - Português
Modules:
Este é o curso "Networking in Google Cloud"
Informações gerais do módulo, Informações gerais sobre conexão, Interconexão dedicada, Informações gerais sobre a Interconexão por parceiro, Criação da Interconexão por parceiro, Conexões L2 e L3, Recomendações para a Interconexão por parceiro, Cross-Cloud Interconnect, Demonstração: Criar uma Interconexão dedicada, Informações gerais sobre o Cloud VPN, Topologias da VPN de alta disponibilidade, Recomendações para a VPN, Introdução ao laboratório: Como configurar a VPN de alta disponibilidade do Google Cloud, Coursera: Introdução ao Google Cloud Platform e o Qwiklabs, Como influenciar a escolha do melhor caminho, Recursos do Network Connectivity Center, Detalhes do produto, Advertências, Revisão do módulo
Informações gerais do módulo, Informações gerais sobre o Acesso privado do Google, Acesso privado do Google, Advertências, Regras de encaminhamento, Balanceadores de carga, Benefícios e advertências, Acesso a serviços particulares, Cloud NAT, Introdução ao laboratório: Implementar o Acesso privado do Google e o Cloud NAT, Revisão do módulo
Informações gerais do módulo, Preços de rede, Níveis de serviço de rede, Introdução ao laboratório: Como otimizar os gastos usando os Níveis de rede, Faturamento, Demonstração: Analisar o faturamento usando rótulos, Revisão do módulo
Informações gerais do módulo, Monitoramento, Network Intelligence, Introdução ao laboratório: Monitoramento de recursos, Cloud Logging, Introdução ao laboratório: Analisar o tráfego de rede com os registros de fluxo de VPC, Revisão do módulo
Course: OpenAI: Consistent Response Strategies
Modules:
Introduction to the Course and Instructor
Prompt Engineering: Clear and Specific Prompts, Prompt Engineering: Reference Text and Contextual information
Fine-Tuning Techniques to Adapt OpenAI's Large Language Models to Specific Domains for More Consistent Responses, Temperature Adjustment Parameter Tuning Technique
Text Filtering and Language Correction Techniques, Context Sensitivity and Consistency Checking, Hands-On Activity: Practice Consistent Response Techniques
Course: Measuring and Maximizing Impact of COVID-19 Contact Tracing
Modules:
Welcome to Measuring and Maximizing Impact of COVID-19 Contact Tracing, Review of SARS-CoV-2 transmission, Infectious period and generation time, Reproductive number as indicator of impact of contact tracing, Introduction to performance metrics, Surveillance: Detection and isolation of infected people, Completeness and timing of contact tracing and quarantine, Summary
Contact Tracing Evaluation and Strategic Support Application (ConTESSA), Introduction to ConTESSA, Review: Surveillance Metrics, Entering Surveillance and Isolation Data, Review: Contact Tracing Metrics, Entering Household Contact Tracing Data, Entering Community Contact Tracing Data, Model of Contact Tracing Impact, Viewing the Dashboard and Generating a Report, Summary of ConTESSA
Examining Strategies to Increase the Impact of Contact Tracing, Comparing programs using Scenario B, Understanding the Underlying Assumptions, Advanced options
Course: Create a Professional Online Presence
Modules:
Welcome to the course, What does your online presence say about you?, Assessing your online presence, Managing your settings
Making connections
Course: ممارسات التدريب
Modules:
نظرة عامة على الدورة التدريبية, نظرة عامة حول الوحدة 1, استمرارية أداء الموظفين, تدريب الموظفين المتطورين باستمرار, تدريب الموظفين أصحاب الأداء الثابت, تدريب الموظفين أصحاب الأداء الضعيف, وضع ثقافة تدريب
نظرة عامة حول الوحدة 2, استخدام مؤشرات الأداء الرئيسية لتشخيص الأداء, الأهداف والأداء, ضمان الاتساق في ممارسة التدريب, العناصر الأساسية لجدول أعمال التدريب, التحكم في عملية التدريب, أدوات التدريب, عوائق القيادة
نظرة عامة حول الوحدة 3, تدريب شخص دائم التأخر, تدريب شخص يتشتت بسهولة, تدريب شخص يفوت مواعيد التسليم, تدريب شخص لم يعد ناجحًا, تدريب شخص على نزاع مع زميل له, تدريب الموظفين صعاب المراس
نظرة عامة حول الوحدة 4, إستراتيجيات تدريب للمديرين, تحسين الأداء التدريبي للمديرين, مسائل شائعة عند تدريب المديرين
نظرة عامة حول المرحلة 2, التدريب خلال التغيير المؤسسي, نصائح لتقديم تعقيبات, ملخص الدورة التدريبية
Course: Capstone: Preparing to work as a Cloud Support Associate
Modules:
Course Introduction, Module 1 Introduction, Cloud Support Associate Skills Recap, Considerations for Supporting Workloads on AWS, Determining the Cause, Escalating the Issue, Troubleshooting an Architecture, Exercise Introduction: Troubleshooting an Architecture, AI and Support, Module 1 Close
Module 2 Introduction, Resume Building, Creating a Portfolio, Finding Gaps in Knowledge, Module 2 Close
Module 3 Introduction, Preparing for Interviews Part 1, Preparing for Interviews Part 2, Interviewing an Operations Manager (Nery), Interviewing a Cloud Support Engineer (Daisy), Interviewing an Enterprise Support Manager (Anjali), Mock Interviews: Technical Question, Mock Interviews: Culture Fit Question, Module 3 Close
Module 4 Introduction, Creating an Architecture, Documenting the Architecture, Exercise Introduction: Documenting the Architecture, Interviewing about Architectures, Exercise Introduction: Creating Questions, Module 4 Close, Course Close
Course: Life 101: Mental and Physical Self-Care
Modules:
Introduction to Good Habits, Good Habits - Part 1, Good Habits - Part 2, Good Habits - Part 3, Interview with Giovanni Douresseau
Introduction to Stress Management, Stress Management - Part 1, Stress Management - Part 2, Stress Management - Part 3
Introduction to Nutrition, Nutrition - Part 1, Nutrition - Part 2, Nutrition - Part 3
Introduction to Mindfulness, Mindfulness - Part 1, Mindfulness - Part 2, Mindfulness - Part 3, Interview with James Hicks
Introduction to Exercise, Exercise - Part 1, Exercise - Part 2, Exercise - Part 3
Introduction to Sleep, Sleep - Part 1, Sleep - Part 2, Sleep - Part 3, Interview
Introduction to Volunteering, Volunteering - Part 1, Volunteering - Part 2, Volunteering - Part 3
Introduction to Bad Drugs, Bad Drugs - Part 1, Bad Drugs - Part 2, Bad Drugs - Part 3
Introduction to Personal Finances, Personal Finances - Part 1, Personal Finances - Part 2, Personal Finances - Part 3
Conservation - Part 1, Conservation - Part 2, Conservation - Part 3, Interview with Ariel Tweto
Course: Create Image Captioning Models - Français
Modules:
Créer un modèle de sous-titrage d'images : présentation, Créer un modèle de sous-titrage d'images : tutoriel de l'atelier
Course: Données au service de la santé de la population
Modules:
Bienvenue au cours, Introduction au Module 1, Comprendre le cycle de la génération à l’utilisation des données, Contexte de l’utilisation des données, Étude de cas sur le cycle de la génération à l’utilisation des données, Prise en considération du genre dans le cycle de la génération à l’utilisation des données, Suivi des inégalités de santé, Résumé du Module 1
Introduction au Module 2, Culture organisationnelle d’utilisation des données, Promouvoir une culture des données probantes, Rôles et responsabilités essentiels, Engagement des utilisateurs et des producteurs de données, Qualité des données, Résumé du Module 2
Introduction au Module 3, Types d’histoires de données, Histoires de données et visualisations, Principes de conception pour des visualisations efficaces, Exemple d’histoire, Rôle de la stratégie de communication dans la promotion d’un système de santé publique solide, Outils de communication des données, Rôle des rapports sur la santé publique, Diffusion des rapports de données, Le projet du bulletin de santé publique, Exemples de bulletins nationaux de santé publique, Fournir un schéma directeur pour construire des fondations solides, Élaborer une définition commune de la qualité, Élargir et améliorer l’assistance technique fournie aux rédacteurs en chef des bulletins de santé publique, Considérations de genre pour l’action politique, Présentation de HEAT et HEAT Plus, Décrire les inégalités à l’aide de la boîte à outils d’évaluation de l’équité en matière de santé (HEAT), Utiliser vos propres données sur l’inégalité dans la boîte à outils pour l’évaluation de l’équité en matière de santé (HEAT Plus), Renforcer les capacités d’évaluation des inégalités, Résumé du Module 3
Introduction au Module 4, Des données à l’action : Traduire les données en politiques et en pratiques, Traduire les données en politiques et en pratiques : Réduire la consommation de sel au Sri Lanka, Des données à l’action : Le cas de la base de données de l’OMS sur la mortalité, Transformer les données en politique de santé publique, Lier la politique au coût, Résumé du Module 4
Course: إدارة الأزمات | Crisis Management
Modules:
مفهوم (Crisis Management) ومفهوم (Risk Management), أنواع الأزمات (Crisis), دراسة حالة (1), دراسة حالة (2), دراسة حالة (3), دراسة حالة (4), قواعد وأسس خطط إدارة الأزمات (Crisis Management Plan), صفات الـ (Crisis Management Team), نموذج للتعامل مع الأزمات وخطوات إدارتها
Course: واجهات برمجة التطبيقات
Modules:
مقدمة إلى الدورة التدريبية, ما الاستخدامات الواقعية لواجهات برمجة التطبيقات؟, ما تعرفه عن HTTP, حالة RESTful, اصطلاحات التسمية, الأدوات الأساسية لتطوير واجهة برمجة التطبيقات, إنشاء مشروع Django باستخدام pipenv, أفضل ممارسات REST, الأمان والمصادقة في واجهة برمجة تطبيقات REST, التحكم في الوصول, مشروع واجهة برمجة تطبيقات قائمة الكتب, تنظيم مشروع واجهة برمجة تطبيقات, تصحيح أخطاء واجهة برمجة التطبيقات الخاصة بك, استخدام أدوات المتصفح والامتدادات لتطوير واجهة برمجة التطبيقات, ملخص الوحدة: واجهات برمجة تطبيقات REST
ما هو إطار عمل Django REST (DRF)؟, تثبيت DRF وإعداده, عرض أفضل لواجهة برمجة التطبيقات باستخدام عناصر التنسيق, طرق العرض المستندة إلى الوظيفة والفئة, شريط أدوات تصحيح أخطاء Django, مشروع واجهة برمجة التطبيقات لقائمة مطعم باستخدام DRF, المحولات التسلسلية, المحولات التسلسلية للنموذج, المحولات التسلسلية للعلاقة, إلغاء التسلسل والتحقق من الصحة, أجهزة العرض, ملخص الوحدة: إطار عمل Django REST
التصفية والبحث, الترتيب, تعيين فواصل الصفحات, التخزين المؤقت, المصادقة المستندة إلى الرمز المميز في DRF, أدوار المستخدم, إعداد تقييد واجهة برمجة التطبيقات, مقدمة إلى مكتبة Djoser لمصادقة أفضل, نقاط نهاية التسجيل والمصادقة باستخدام JWT, إدارة حساب المستخدم, ملخص الوحدة: تأمين واجهة برمجة التطبيقات في إطار عمل Django REST
ملخص الدورة التدريبية: واجهات برمجة التطبيقات, مقدمة المشروع, إنشاء نماذج, اختتام الدورة التدريبية
Course: Preparing for Your Associate Cloud Engineer Journey - Português Brasileiro
Modules:
Visão geral do módulo, Introdução ao papel do Associate Cloud Engineer, Valor e benefícios da certificação, Processo de certificação, Como criar seu plano de estudos
Visão geral do módulo, Configurar o ambiente de nuvem da Cymbal Superstore, Introdução: Perguntas de diagnóstico, Como criar seu plano de estudos
Visão geral do módulo, Selecionar os recursos das soluções de nuvem da Cymbal Superstore, Introdução: Perguntas de diagnóstico, Como criar seu plano de estudos
Visão geral do módulo, Implantar e implementar as soluções recomendadas da Cymbal Superstore, Introdução: Perguntas de diagnóstico, Como criar seu plano de estudos
Visão geral do módulo, Gerenciar as soluções de nuvem da Cymbal Superstore, Introdução: Perguntas de diagnóstico, Como criar seu plano de estudos
Visão geral do módulo, Gerenciar o acesso das soluções de nuvem da Cymbal Superstore, Introdução: Perguntas de diagnóstico, Como criar seu plano de estudos
Suas próximas etapas
Course: Derivatives
Modules:
Welcome!, Introduction, Bonds: definitions, Classification of bonds, Reasons and risk of trading bonds, Stocks: definition, Trading Stocks, Future contracts: definition, Options: definition (part 1), Options: definition (part 2), Options: Bounds of option prices, Options: Trading strategies involving options
A simple period model of security prices: portfolios, A single period model of security prices: pricing via replication, Pricing options by state prices, Pricing assets using risk neutral probabilities: examples, Pricing options using risk neutral probabilities, Pricing assets by state prices: examples, A Multi-period model of security prices, Pricing american options
The Geometric Brownian motion, The Itô’s rule, The MBS model: completeness, The MBS model: the price of European options (part 1), The MBS model: the price of European options (part 2)
The binomial model of interest rate, Pricing bonds with a Binomial Interest Rate Tree, Recovering the risk neutral probability from bond prices, Building a realistic tree, Continuous time models of interest rates, Pricing bonds with continuous time interest rates, Introduction to credit risk models: the Merton model, Introduction to credit risk models: the intensity-based approach
Generating random numbers from the uniform distribution, Generating random numbers from a normal distribution, Simulation of BM, GBM and Vasicek processes, Monte Carlo simulations and option pricing, Variance reduction techniques: Antithetic Variables, Variance reduction techniques: Control variates, Variance reduction techniques: Importance sampling
Course: Talend Data Integration Certification Preparation training
Modules:
Data Integration in context, Introduction to the Integration perspective, Implementing a simple ETL, Working with schemas, Reading from files, Reading and writing databases, Introduction to tMap, Joining data with tMap, Filtering data with tMap
Creating and using Repository Metadata, Contexts and context variables, Trigger connections, Error handling and logging, Connections in Talend Studio, Revision Control in Talend Studio, Reference projects
Parent and Child Jobs, Joblets, Parallelization in Jobs, Remote Job execution, Debugging a Job
Course: Diseño instruccional para el aprendizaje activo
Modules:
Presentación del curso, 1. ¿Qué es el aprendizaje?, El aprendizaje activo, Aportaciones del aprendizaje activo para la mejora de tu proyecto
¿Qué son los ambientes de aprendizaje innovadores?, ¿Cómo decidir qué ambiente de aprendizaje diseñaré?, ¿Qué metodologías o estrategias potencian el aprendizaje activo?, La innovación como eje transversal
Ejemplos de ambientes de aprendizaje vinculado, Competencias digitales, Ejemplos de aplicación de competencias digitales en proyectos educativos, Generalidades de los recursos educativos abiertos (REA)
Movimiento educativo abierto, Opiniones de expertos sobre tecnologías emergentes innovadoras, Opiniones de expertos sobre diseminación de REA
Evaluación de la integración de tecnologías emergentes en el diseño innovador, Factores para considerar en la implementación de proyectos, ¿En qué consiste la colección de datos para evaluar proyectos de innovación?, Cierre del curso
Course: Las personas, la tecnología y el futuro de la movilidad
Modules:
¿Cuál es el futuro de la movilidad?, Definición de movilidad, ¿Qué es la electrificación?, ¿Qué es la automatización?, Movilidad en el pasado, presente y futuro: ¿Del ferrocarril a las carreteras?
Introducción a los vehículos eléctricos, ¿Cómo funciona una batería de iones de litio?, Cómo se gestionan las baterías, Fabriquemos una batería en el laboratorio de baterías de Universidad de Michigan, ¿Qué tan seguras son las baterías?
Carga e infraestructura de carga, Vehículos eléctricos y sistema de alimentación, Perspectivas de la industria sobre los usos de la electrificación (parte 1), Perspectivas de la industria sobre los usos de la electrificación (parte 2), Perspectivas del Gobierno sobre las aplicaciones de la electrificación | Entrevista con Missy Stults, Asociaciones entre los sectores público y privado, Proceso de asignación de las partes interesadas
¿Qué relación hay entre la equidad y la movilidad?, ¿Qué es la sostenibilidad en el contexto de la movilidad?, Perspectivas de la industria sobre la sostenibilidad medioambiental, Consecuencias de la electrificación: Perspectiva medioambiental, Consecuencias de la electrificación: Perspectiva de la salud, Consecuencias de la electrificación: Perspectiva de la justicia energética, La electrificación y los empleos del futuro
Introducción a los vehículos autónomos, Tecnología de detección basada en vehículos, Opcional: Charla y paseo en transporte autónomo, Conceptos básicos de la inteligencia artificial, Charla sobre datos de conducción e inteligencia artificial, Perspectivas de la industria sobre las tecnologías de automatización, Perspectivas de la industria sobre la automatización de vehículos, Perspectivas de los gobiernos locales sobre la automatización de vehículos, Perspectivas de los gobiernos estatales sobre la automatización de vehículos
Consecuencias de la automatización: Consideraciones de seguridad, Consecuencias de la automatización: Perspectiva de la planificación urbanística, Riesgos y problemas de privacidad y datos, Consecuencias de la automatización: Perspectiva jurídica, Consecuencias de la automatización en el mercado laboral, El futuro de la movilidad: ¿Qué es lo que sigue?
Course: Getting Started with Amazon Timestream
Modules:
Getting Started with Amazon Timestream
Course: Gobierno Digital
Modules:
0.1 Bienvenida al curso, 1.2.2 Trámites: la experiencia de la ciudadanía en América Latina y el Caribe, 1.2.5 Gobierno digital: una revolución del sector público, 1.3.4 ¿Qué necesitan los gobiernos para impulsar la transformación digital?, 1.3.7 La transformación de un país: el caso de Estonia, 1.3.9 ¿Cuáles son los riesgos de no hacer una transformación digital?, 1.4.3 Mejorando la relación gobierno-ciudadanos, 1.4.5 Soluciones digitales para mejorar vidas
2.2.1 Servicios digitales: ventajas y buenas prácticas, 2.3.1 Interoperabilidad para la transformación digital
3.2.1 El valor de los datos, 3.3.1 Identidad digital y firma digital, 3.4.1 Iniciativas nacionales de ciberseguridad, 4.1 Próximos pasos
Course: Meta Marketing Science Certification Exam
Modules:
Introduction to the Program, Introduction to Anke Audenaert, Introduction to the Meta Marketing Science Certification Exam, Practice Exam Overview
Congratulations!
Course: Data Acquisition, Risk, and Estimation
Modules:
Welcome to Acquisition, Risk and Estimation, Introduction to Fundamentals of Sampling, Sample Versus Population, Types of Sampling - Part 1, Types of Sampling - Part 2, Sampling Error, Random Sampling Distributions - Part 1, Random Sampling Distributions - Part 2, RSD of the Mean, The Central Limit Theorem, Solving Problems with the RSD of the Mean Part 1, Solving Problems with the RSD of the Mean Part 2
Introduction to Estimation, Estimators and Point Estimates, Interval Estimates, Confidence Interval for the Mean, Sigma Known, Confidence Interval for the Mean, Sigma Unknown, Confidence Interval for Variance / Standard Deviation, Confidence Interval for Proportion / Rate (Count), Practice Activity 1, Practice Activities 2 and 3
Introduction to Best Case / Worst Case Analysis, Best / Worst Case Analysis Introduction and Step 1, Best / Worst Case Analysis Steps 2 and 3, Best  / Worst Case Analysis Steps 4 and 5, Creating the table using RStudio, Visualization and Joint Probability, Best / Worst Case Example 1, Best / Worst Case Example 2 Part 1, Best / Worst Case Example 2 Part 2
Introduction to Foundations of Hypothesis Testing, Introduction to Hypothesis Testing, Testing Hypotheses, Significance Level, Risk, One-Two-Tailed Tests, Error and Power in Hypothesis Testing, Understanding Beta and Power, Calculating Beta and Power for Means, Calculating Beta and Power for Variance, Calculating Beta and Power for Proportions and Rates, Sample Size Calculations for Means, Sample Size Calculations for Variances, Sample Size Calculations for Proportions
Introduction to Essentials for Effect Size Calculations, Essentials for Effect Size Calculations, Risk Analysis - Implications of Decisions, Effect Size Calculation OSCD Example Part 1, Effect Size Calculation OSCD Example Part 2, Effect Size Calculation OSCD Example Part 3, Effect Size Calculation for the Mean Part 1, Effect Size Calculation for the Mean Part 2, Effect Size Calculation for the Mean Part 3, Effect Size Calculation for the Standard Deviation, Effect Size Calculation for the Proportion