dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: Data Management and Storage in the Cloud
Modules:
Introduction to Course 2, Eric: Data analytics skills translate across industries and roles, Welcome to module 1, Data storage and connections, Gerrit: Experience with a variety of tools can help you as an analyst, Common ways to store data, Structured, unstructured, and semi-structured data, Example of a data lakehouse, Aspects of table schema, Introduction to nested data structure, Overview of data processing methods, Wrap-up
Welcome to module 2, Denormalized data, Data governance for effective data management, MK: Risk management in a cloud-first world, Introduction to master data management, Introduction to data catalogs, Technical and business metadata, Overview of data lakehouse architecture, Components of data lakehouse architecture, Wrap-up
Welcome to module 3, Ryan: Curiosity can help you understand and connect data, Data lineage and traceability, Introduction to Analytics Hub, Data discovery, curation, and unification, Benefits of using Dataplex, Wrap-up
Welcome to module 4, Methods for defining BigQuery table schemas, Basic SQL commands for querying data, Steps and models for accessing data with machine learning, Introduction to machine learning with Vertex AI and BigQuery, Overview of Google Colab, Essentials of database partitioning, Methods for partitioning tables, Strategies for querying partitioned tables, Key processes and benefits of Dataproc, Wrap-up, Vince and George: Interview role play, Course wrap-up
Course: Essential Cloud Infrastructure: Foundation - Português Brasileiro
Modules:
Introdução ao curso
Visão geral do módulo, Como usar o Google Cloud, Introdução ao laboratório: Como trabalhar com o console do Google Cloud e o Cloud Shell, Coursera: Como começar a usar o Google Cloud Platform e o Qwiklabs, Revisão do laboratório: Como trabalhar com o console do Google Cloud e o Cloud Shell, Introdução ao laboratório: Visualização da infraestrutura, Revisão do laboratório: Visualização da infraestrutura, Demonstração: projetos, Revisão do módulo
Visão geral do módulo, Nuvem privada virtual, Projetos, redes e sub-redes, Demonstração: expandir uma sub-rede, Endereços IP, Demonstração: IP interno e externo, Como mapear endereços IP, Rotas e regras de firewall, Preços, Introdução ao laboratório: Rede VPC, Revisão do laboratório: Rede VPC, Designs de rede comuns, Introdução ao laboratório: Implementar o Acesso privado do Google e o Cloud NAT, Revisão do laboratório: Implementar o Acesso privado do Google e o Cloud NAT, Revisão do módulo
Visão geral do módulo, Compute Engine, Demonstração: criar uma VM, Acesso e ciclo de vida da VM, Introdução ao laboratório: Como criar máquinas virtuais, Revisão do laboratório: Como criar máquinas virtuais, Opções de computação, Preços do Compute, Configurações especiais do Compute, Imagens, Opções de disco, Ações comuns do Compute Engine, Introdução ao laboratório: Como trabalhar com máquinas virtuais, Revisão do laboratório: Como trabalhar com máquinas virtuais, Revisão do módulo, Revisão do curso
Course: C# for .NET Developers
Modules:
Specialization introduction video, Course Introduction, Meet Your Instructor, What you will learn in this Lessson, Introduction to .NET Core and its features, .NET Core Version History, Difference Between .NET Framework and .NET Core, Setting up a development environment with VS code, What you will learn in this Lessson, Introduction to .NET CLI, .NET CLI Commands, The .Net Core Platform, Demo: Building a basic .NET Core console application
What you will learn in this Lessson, Introduction to C#, History of C# Version, C# Code Execution, Installing and Configuring C# in Visual Studio, Variable and DataType, Demo: C# Hello World Program, What you will learn in this Lessson, Operators and Operators Precedence, Conditional Statements, Loops, Jump Statements, What you will learn in this Lessson, Arrays and Types of Arrays, Manipulating Arrays, Strings and String Methods, Manipulating Strings, What you will learn in this Lessson, Object-Oriented Programming Concepts, Classes and Objects, Encapusulation and Abstraction, Constructors, Inheritance
What you will learn in this Lessson, Polymorphism, Abstract Classes, Interfaces, Static Class and Static Methods, Extension Methods, Partial Class and Partial Methods, What you will learn in this Lessson, Property, Indexer, Enum in C#, Exception Handling, Handling Exceptions in Console Application, What you will learn in this Lessson, Anonymous Type, Delegates, Events, Anonymous Methods, Lambda Expression, Expression Tree, What is Synchronous and Asynchronous?, Asynchronous Programming Patterns in .NET, Asynchronous Programming Model (APM), Event-based Asynchronous Pattern (EPM), Task-based Asynchronous Pattern (TAP)
Course: Science and Technology in the Silla Cultural Heritage
Modules:
Welcome to Science and Technology in Silla Cultural Heritage (English), Intro, The façade, Background Math & The Rest, Ending
Intro, Cheomseongdae and Queen Seonduk, Functions of Cheomseongdae, Structure & its Characteristics of Cheomseongdae, Ecliptic Curve and The Winter-Solstice-Sunrise Direction on Cheomseongdae, Seismic Design of Cheomseongdae and Conclusion, Ending
Intro, Historical Records on Poseokjeong, Meandering Watercourses in Asia, The Role of Poseokjeong, Fluid Mechanical Investigation, Basic Principle of Vortex Formation in Poseokjeong, Ending
Intro, Visitors’ Overview, Discussion: Mathematical Sciences & Technology, Ending
Intro, Introduction, The Legend of Emille, Appearance, Metallurgy of the Bell, Physics of the Bell, Ending
Intro, The Birth of Metallurgy, Metalcrafts in Korea, Metallurgy in Silla, Ending
Course: Building Production-Ready Apps with Large Language Models
Modules:
Introduction to LLMs: Benefits and Applications, Prompt Engineering, LLM Development, Production Readiness, Getting Started with HuggingFace, Building UIs with Gradio, Developing the FAQ Chatbot: Part 1 - Getting Started, Developing the FAQ Chatbot: Part 2 - Finalizing and Deployment, Ethical Considerations for LLMs, Mitigating AI Risks, Ensuring Transparency, Maintaining User Trust
Course: AWS: Compute and Data Transfer
Modules:
AWS Lambda, Amazon ECS, Amazon ECS: Tasks and Task Definitions, Amazon EKS, AWS Batch
Introduction to Data Migration, AWS Migration Hub, AWS Application Discovery Service, AWS Snow Family, AWS Transfer family, AWS SAM, AWS Server Migration Service, AWS Backup
Course: Teaching for Justice and Inclusivity In Challenging Times
Modules:
Introduction Video, Week 1 Overview
Week 2 Overview
Week 3 Overview
Week 4 Overview
Week 5 Overview, Exit Video: Closing Thoughts
Course: Sustainability and the Circular Economy
Modules:
Design for the Circular Economy: Program Overview, Introduction to the Course, Course Overview, Introduction to Module 1, Is the Planet Warming?, Consequences of a Warming Planet, Ocean Acidification, Plastic Planet, Biodiversity on the Brink, Welcome to the Anthropocene, Finally Some Good News
Introduction to Module 2, Sustainability Defined, The IPAT Equation, The UN’s Sustainable Development Goals, The Business of Business – The Ideas Behind Neoliberal Economics, Doughnut Economics and Progressive Capitalism
Introduction to Module 3, Global Warming and the Greenhouse Effect, GHGs are Increasing, GHGs are Increasing Due to Us!, GHGs — Not Just CO2, Albedo and Reinforcing Effects, Sources of Anthropogenic GHGs, The Paris Accord and the Need for Change — Part 1, The Paris Accord and the Need for Change — Part 2
Introduction to Module 4, Power Generation Basics, Energy and Heat — Getting our Units Right, Determining GHGs from Power Plants, Nuclear Power Plants and How they Work, Nuclear Pros and Cons and Technologies on the Horizon, Making the Transition to Renewable Energy, Pathways to Net Zero — Part 1, Pathways to Net Zero — Part 2
Introduction to Module 5, Sustainable Transportation - Part 1: GHGs from Transportation, Sustainable Transportation - Part 2: Our Transportation Carbon Footprint, The EVs are Coming - Part 1: EVs are an Old Idea!, The EVs are Coming - Part 2: EVs Hit the Tipping Point, The EVs are Coming - Part 3: Electrification of Everything Else, Sustainable Homes, Livable Cities, Our Current Food Production Systems, Sustainable Food and Regenerative Agriculture, The Challenges of Fast Fashion, Sustainable Fashion
Introduction to Module 6, Introduction to the Circular Economy, The 3 Principles of the Circular Economy, The Butterfly Diagram – Technical Nutrient Cycles, The Butterfly Diagram – Biological Nutrient Cycles, Course Wrap-Up
Course: Cómo captar talento en la era de la digitalización
Modules:
Presentación del curso
Presentación de la semana, Introducción, Qué tipo de servicios ofrecen, Cuándo son necesarios, Elementos de un profesiograma, Aplicaciones del profesiograma, Dificultades y riesgos a considerar
Presentación de la semana, Finalidad, Tipología, Concepto, Características, Origen, Aplicación y perfil, Diseñar un AC
Presentación de la semana, Introducción, Entrevista curricular, Entrevista competencial, Entrevista digital, Elección de formatos, Introducción, Metodología para entrevista competencial. Parte I, Metodología para entrevista competencial. Parte II, Metodología para entrevista competencial. Ejemplos, Indicadores genéricos de potencial
Presentación de la semana, Concepto, Finalidad, Tipología e implementación, Preparación, Implementación, Seguimiento, Despedida
Course: Estima la carga de trabajo de tu equipo
Modules:
Bienvenida, Estimaciones ineficientes, ¿Cómo estimar correctamente?, ¿Cómo cumplir con lo que te comprometes?
Course: Hardware Security
Modules:
Introduction, Digital System Specification, Digital System Implementation, Function Simplification and Don't Care Conditions, Sequential System Specification, Sequential System Implementation, Vulnerabilities in Digital Logic Design
Introduction to IP Protection, Watermarking Basics, Watermarking Examples, Good Watermarks, Fingerprinting, Hardware Metering
Physical Attacks (PA) Basics, Physical Attacks and Countermeasures, Building Secure Systems, Modular Exponentiation (ME) Basics, ME in Cryptography, ME Implementation and Vulnerability, Montgomery Reduction
Introduction to Side Channel Attacks, Memory Vulnerabilities and Cache Attacks, Power Analysis, More Attacks and Countermeasures, Modified Modular Exponentiation
Hardware Trojan (HT) and Trusted IC, Hardware Trojan Taxonomy, Hardware Trojan Detection Overview, Hardware Trojan Detection Methods, Trusted IC Design with HT Prevention
FPGA Implementation of Crypto, Vulnerabilities and Countermeasures in FPGA Systems, Role of Hardware in Security and Trust, Physical Unclonable Functions (PUF) Basics, RO PUF: Reliability, Trust Platform Module and Other Good Practices
Final Exam
Course: Detección de objetos
Modules:
Bienvenida, L1.1. Introducción a la detección de objetos, L1.2. Formación de la imagen, L1.3. Características de píxel, L1.4. Componentes conexas, L1.5. Template matching, L1.6. Características locales
L2.1. Introducción, L2.2.a. Local Binary Patterns, L2.2.b. Local Binary Patterns - Variantes (LBP Uniforme), L2.2.c. Histograma LBP por bloques, L2.3.a. Regresión logística - Clasificación (I), L2.3.b. Regresión logística - Clasificación (II), L2.4.a. Regresión Logística – Aprendizaje (I), L2.4.b. Regresión Logística – Aprendizaje (II), L2.4.c. Regresión Logística – Aprendizaje (III)
L3.1. Introducción, L3.2.a. Generación de Candidatos – Ventana Deslizante, L3.2.b. Generación de Candidatos – Pirámide, L3.3. Generación de Candidatos – Refinación, L3.4. Anotación, Bootstrapping, Aprendizaje Activo, L3.5.a. Evaluación de la clasificación por ventana (I), L3.5.b.  Evaluación de la clasificación por ventana (II), L3.6 Evaluación del rendimiento - Evaluación del detector, L3.7 Conjuntos de Entrenamiento, Evaluación y Validación
L4.1. Detector de peatones basado en HOG + SVM, L4.2. HOG - Cálculo del gradiente, L4.3. HOG – Cálculo de los histogramas, L4.4. HOG – Cálculo del descriptor, L4.5. Support Vector Machines (SVM) – Conceptos básicos, L4.6. Support Vector Machines (SVM) – Desarrollo matemático
L5.1. Detector de caras basado en filtros de Haar + Adaboost, L5.2. Características de Haar, L5.3. Imagen Integral, L5.4. Adaboost, L5.5. Cascada de clasificadores, L5.6. Detalles de implementación
L6.1. Introducción, L6.2. Modelos no holísticos: DPM, L6.3. Modelos no holísticos: conjunto de expertos locales, L6.4. Adaptación de Dominio, L6.5. Convolutional Neural Networks (CNNs), L6.6. Otras modalidades de imagen, L6.7. Generación de candidatos
Course: Gemini for end-to-end SDLC - 한국어
Modules:
Gemini가 그려 나가는 소프트웨어 개발의 미래
Course: Train Machine Learning Models
Modules:
Course Intro: Train Machine Learning Models, Machine Learning, Machine Learning Algorithms, Algorithm Selection, Iterative Tuning, Bias and Variance, Model Generalization, The Bias–Variance Tradeoff, Holdout Method, Parameters, Hypothesis and DOE, Hypothesis Testing, A/B Tests, p-value, Confidence Interval
Logistic Regression, Multinomial Logistic Regression, k-Nearest Neighbor (k-NN), Support-Vector Machines (SVMs), Naïve Bayes, Decision Tree, Customer Retention Example Tree, Pruning, Ensemble Learning and Random Forests, Gradient Boosting, Hyperparameter Optimization, Evaluation Metrics, Classification Model Performance, Confusion Matrix, Accuracy, Precision, Recall, and Specificity, Precision–Recall Tradeoff and F₁ Score, Receiver Operating Characteristic (ROC) Curve, Learning Curve
Linear Regression, Linear Regression in Machine Learning, Matrices in Linear Regression, Normal Equation, Regression Using Decision Trees and Ensemble Models, Forecasting, Autoregressive Integrated Moving Average (ARIMA), Cost Function, Regularization, Gradient Descent, Grid/Randomized Search for Regression, Mean Squared Error (MSE) and Mean Absolute Error (MAE), Coefficient of Determination
k-Means Clustering, Hierarchical Clustering, Latent Class Analysis, Clustering Hyperparameters and Tuning, Evaluation Metrics for Clustering, Elbow Point, Cluster Sum of Squares, Silhouette Analysis, When to Stop Hierarchical Clustering
Online Retailer: Developing Classification, Regression, or Clustering Models
Course: Non-Communicable Diseases in Humanitarian Settings
Modules:
Siri Tellier: Why is it important?, Alessandro Demaio: The "big four" NCDs Explained, Sylvia Khamati: The double burden of disease - Kenya refugee camps, Mouna Mayoufi: Lack in quality of care - Syria, Heidi Christensen: Challenges for refugees on the move - Lesbos, Experiences from refugees affected by NCDs
Siri Tellier: What is being done?, Sylvia Khamati: Community awareness needed - Kenya, Mouna Mayoufi: Data needed to improve preparedness - Libya, Heidi Christensen: Treatment dilemmas - Pakistan
Siri Tellier: Challenges and Opportunities, Sylvia Khamati: Financial Dilemmas - Kenya, Heidi Christensen: Dilemmas in long term treatment in India, Sigiriya A. Perone: Do's and Dont's
Course: Bending the Curve: Climate Change Solutions 2
Modules:
Energy Demand and Greenhouse Gas (GHG) Intensity Through 2030 [S. Samuelsen, 2:37], Role of Combustion [S. Samuelsen, 13:18], Paradigm Shifts in Electricity & Transportation [S. Samuelsen, 12:09], Alternatives to Combustion [S. Samuelsen, 4:58], Fuel Cell Technology [S. Samuelsen, 17:52], Evolution of the Electric Grid [S. Samuelsen, 7:32], Smart Grid Technology [S. Samuelsen, 5:15], Overview of Energy Efficiency Management [J. Brouwer, 4:08], University of California Campus Operations [J. Brouwer, 10:02], Generations of Power [J. Brouwer, 4:12], Utilization of Power [J. Brouwer, 7:22]
Major Concerns of Transportation [M. Barth, 8:08], Transportation Emissions and Energy Impacts [M. Barth, 6:17], Sustainable Transportation Solutions [M. Barth, 4:01], Impacts of Intelligent Transportation Systms on Energy & Emissions [M. Barth, 7:17], Role of Vehicle Automation on Energy & Emissions [M. Barth, 5:25], Transportation Pathways: Vehicles [D. Sperling, 9:40], Transportation Pathways: Fuels [D. Sperling, 8:48], Transportation Pathways: Mobility [D. Sperling, 13:03]
Introduction to Technologies for Short Lived Climate Pollutants (SLCPs) Mitigation [V. Ramanathan & D. Zaelke, 3:35], Short Lived Climate Pollutants (SLCPs): Reduce Near-Term Warming [V. Ramanathan, 10:41], Black Carbon: Major Climate Pollutant [V. Ramanathan, 6:03], Methane Mitigation [V. Ramanathan, 4:07], Montreal Protocol [D. Zaelke, 19:58], Kigali Amendment [D. Zaelke, 15:27]
Introduction to Enhancing Carbon Sinks [D. Silver, 1:05], Introduction to Land Based Solutions [W. Silver, 6:42], Enhancing Carbon Sinks: Soils [W. Silver, 5:56], Enhancing Carbon Sinks: Agriculture and Forestry [W. Silver, 3:49], Enhancing Carbon Sinks: Carbon Sequestration Case Study [W. Silver, 10:18]
Removing and Storing CO2 [R. Aines, 24:35], Recycling CO2 [R. Aines 8:53], The California Story [R. Aines, 12:24], Summary [R. Aines, 4:25]
Course: Incident Management and Continuous Improvement
Modules:
Welcome Video, Introduction to Remote Work Policies, Developing Remote Work Policies, Legal and Regulatory Considerations in Remote Work, Employee Engagement and Feedback in Policy Development, Communicating Remote Work Policies, Providing Remote Work Resources and Support, Monitoring and Measuring Remote Work Performance, Assembling a Multidisciplinary Team
Selecting a Compliance and Regulatory Framework, Components of an Incident Response Plan, Tools for Efficient Incident Management, Incident Response Roles and Responsibilities, Methods for Evaluating Incident Response Effectiveness, Refining the Incident Response Plan Post-Incident, Learning From Incidents: Continuous Improvement in Incident Management, Case Studies in Incident Management in Remote Teams
The Importance of Continuous Improvement in Cybersecurity, A Scenario: Responding to a Zero-Day Threat, The Plan-Do-Check-Act Cycle, Managing Change in Security Practices, Analyzing Trends in Cybersecurity, Integration of New Tools and Services in Security Practices, Remote Team Security Evolution Roadmap, Remote Team Security Evolution Roadmap Case Study, Course Complete!
Course: AI Workflow: Business Priorities and Data Ingestion
Modules:
Course Introduction, IBM Watson Studio - Create a project, Workflow Overview
Data Collection Overview, Introduction to Business Opportunities, Introduction to Scientific Thinking for Business, Introduction to Gathering Data, AI Workflow: Gathering data
Introduction to Data Ingestion, AI Workflow: Data ingestion, AI Workflow: Sparse Matrices for Data Pipeline Development, Using Watson Studio to Complete the Case Study, Case Study
Course: Introduction to Generative AI - 简体中文
Modules:
生成式 AI 简介
Course: Pilares de Marketing Digital
Modules:
Universidad Austral, ¿De qué hablamos cuando hablamos de Marketing Digital?, Relacionándose con los clientes, A modo de Conclusión
La evolución de los medios: transmedia, nuevos medios y nuevas audiencias, El móvil como “pantalla total”, Las nuevas audiencias y las conversaciones
Plan de Marketing Digital, SEO vs. SEM, Marketing Viral, E-Mail Marketing
Planificar, implementar, testear / medir (Analizar)  y corregir, KPIs del Negocio y Métricas de Web Analytics, Funnel de Ventas, Video Investigación de Mercados Online
Course: Models & Frameworks to Support Sales Planning
Modules:
Video 0 - Introduction to Course 3, Video 1 - Planning your sales: Operational variables, Video 1 - Key Account Management: Structuring Sales to Manage Special Customers - Part 1, Video 2 - Key Account Management: Structuring Sales to Manage Special Customers - Part 2, Video 1 - The Leadership Role in Sales, Video 1 - The Strategizer: Episode 10, Video 1 - Resource Allocation, Video 1 - Performance Management, Video 1 - Post-sales Framework, Video 2 - Closing Module 1: Sales Management
Video 1 - Consultative Selling Model, Video 1 - Customer Centric Model, Video 1 - PSS Model (Professional Selling Skills), Video 2: PSS – Presentation & Objections handling, Video 3 - PSS - Closing, Video 1 - Relationship Selling Model, Video 1 - SPIN Selling P1, Video 2 - SPIN Selling P2, Video 1 -The three stages of a Sales call, Video 1 - Conceptual Selling - Miller-Heiman Model, Video 2 - Closing Module 2: Selling Models and Frameworks
Video 1 - Cognitive Bias and communications, Video 2 - Influence and Sales, Video 3 - Body Language, Video 4 - NLP Topics, Video 1 - Physiological variables and how thay affect Sales, Video 2 - Psychological variables and how they affect Sales, Video 1 - Customer Engagement, Video 1 - The Strategizer: Episode 11 - Interview with Flávia Muraro, Video 1 - Sales Closing, Video 2 - Closing Module 3: Soft Skills
Video 1 - Course 3: Assignment developing process, Video 2 - Course 3: Assignment developing process
Course: MLOps Platforms: Amazon SageMaker and Azure ML
Modules:
Meet your Course Instructor: Noah Gift, Using Sagemaker Studio Lab, Getting Started with AWS CloudShell, Advantages of Using Cloud Developer Workspaces, Prototyping AI APIs in CloudShell, Cloud9 with AWS Codewhisperer AI Pair Programming Tool, Introduction to Data Storage, Determining the Correct Storage Medium, Working with Amazon S3, Batch vs. Streaming Job Styles, Introduction to Data Ingestion and Processing Pipelines, Working with AWS Batch, Working with AWS Step Functions, Transforming Data in Transit, Handling Map Reduce for Machine Learning, Working with EMR Serverless
Cleaning Up Data, Scaling Data, Labeling Data, Identifying and Extracting Features, Feature Engineering Concepts, Graphing Data, Clustering Data
When to Use Machine Learning?, Supervised vs. Unsupervised Machine Learning, Selecting a Machine Learning Solution, Selecting a Machine Learning Model, Modeling Demo with Sagemaker Canvas, Using Train, Test and Split, Solving Optimization Problems, Selecting GPU vs. CPU, Neural Network Architecture, Overfitting vs. Underfitting, Selecting Metrics, Comparing Models using Experiment Tracking
Monitoring and Logging, Multiple Regions, Reproducible Workflows, AWS-Flavored DevOps, Reviewing Compute Choices, Provisioning EC2, Provisioning EBS, AWS AI ML Services, Principle of Least Privilege AWS Lambda, Integrated Security, Overview of Sagemaker Studio Workflow, Model Predictions with Sagemaker Canvas, Data Drift and Model Monitoring, Running PyTorch with AWS App Runner
Introduction to Azure Certifications, Learning Resources for Azure Certifications, Microsoft Learning Paths and Study Notes, Creating an Azure ML Workspace, Creating an Azure Auto ML Job, Introductory Azure ML and MLOps Concepts, Prerequisite Technology, Real Time and Batch Deployment, Azure Open Datasets, Exploring Open Datasets SDK, More Advanced Azure ML and MLOps Concepts, Exploring Azure ML Command Line, Triggering Azure ML with GitHub, Using Hyperparameters, Train a Model using the Python SDK
Course: From prototyping to validating business models
Modules:
Welcome to the course, Course requirements, Engaging with your tasks, Sustainable business value, Thoughts from your course instructor, Customer value peak, Week 1 summary
Welcome to Week 2, Sustainable business concepts and their value types, Mapping your sustainable business concept value types, Value proposition statements, Sustainable value proposition canvas, Prototyping sustainability value, Thoughts from your course instructor, Case study: Riversimple, Create your initial sustainable business value map, Monetising your value exchanges, Enriching your sustainable business network value map, Week 2 summary
Video 4.1  Interview with Helen Burdett, Head of Circular Economy at the World Economic Forum
Welcome to Week 4, Transitioning to experimentation, Thoughts from your course instructor, Documenting your assumption outcomes, Pitching your sustainable business concepts effectively, Conclusion and next steps
Course: Infraestructura sostenible en la agenda de desarrollo
Modules:
1.2.1 ¿Qué es la infraestructura sostenible?, 1.2.2 El Acuerdo de París, 1.2.5 Una visión común de infraestructura sostenible, 1.3.1 Los desafíos globales y la sostenibilidad durante el proyecto, 1.3.2 La infraestructura sostenible en la recuperación económica, 1.3.4 El rol del sector privado en las inversiones, 1.3.7 La infraestructura sostenible en el ciclo de proyecto
2.1.1 Actividad práctica: Proyectos alineados a la estrategia de desarrollo del país, 2.1.3 ¡Solicita tu insignia digital!, 2.2.1 Principales lecciones del curso, 2.2.2 Lecturas y otros recursos opcionales, 2.2.4 Sigue aprendiendo
Course: Fundamentals for Implementing a Hypertension Program
Modules:
How to navigate this course, Resources for Course Introduction, Resources for "Module Overview", Resources for "Basic Concepts of Hypertension", Resource for "Global Burden of Hypertension", Resources for "Treatment of Hypertension", Resources for "Reduction of Hypertension-Related Complications", Resources for "Major Challenges of Hypertension Management", Resources for "Hypertension Control Programs", Module 1 References
Resources for "Module Overview", Resources for "Measuring Blood Pressure", Resources for "Devices to Measure Blood Pressure", Resources for "Hypertension Diagnosis", Resources for "Treatment Options for Hypertension", Resources for "Case Study", Resource for "Module Takeaways"
Resource for "Facilities and Staffing", Resource for "Evaluating Existing Blood Pressure Measurement Devices and Selecting for Purchase", Resource for "Optimizing Clinics to Promote Effective Hypertension Treatment", Resources for "Blood Pressure Documentation and Information Systems", Resources for "Staff Training", Resources for "Module Takeaways"
Resources for "Module Overview", Resources for "Community-Based Healthcare", Resources for " 'Task-Shifting' and 'Task-Sharing': Definitions and Rationale", Resources for "Key Factors Affecting Implementation of Task-Sharing in Hypertension Management, Module 4 Resources
Resources for "Systems of Medication Supply and Management", Resources for "Major Challenges in Medication Supply and Potential Solutions", Resource for "Success Stories", Resources for "Module Takeaways"
Resources for "Program Planning for Effective Hypertension Management", Resources for "Program Monitoring and Evaluation", Resources for "Effective Communications and Teamwork", Resources for "Module Takeaways"
Course: Architecting Google Kubernetes Engine: Foundations in italiano
Modules:
Introduzione al corso
Introduzione, Cloud computing e Google Cloud, Gestione delle risorse, Fatturazione, Interazione con Google Cloud, Introduzione al lab, Coursera: Introduzione a Google Cloud e Qwiklabs, Soluzione del lab, Riepilogo
Introduzione, Introduzione ai container, Container e immagini container, Introduzione al lab, Soluzione del lab, Introduzione a Kubernetes, Introduzione a Google Kubernetes Engine, Opzioni di calcolo nel dettaglio, Riepilogo
Introduzione, Concetti di base di Kubernetes, Piano di controllo Kubernetes, Concetti di base di Google Kubernetes Engine, Gestione degli oggetti di Kubernetes, Introduzione al lab, Soluzione del lab, Introduzione a Migrate for Anthos, Architettura di Migrate for Anthos, Percorso di migrazione, Installazione di Migrate for Anthos, Riepilogo
Risorse del corso Foundations (English only)
Course: Launching into Machine Learning em Português Brasileiro
Modules:
Introdução ao curso
Introdução, Melhorar a qualidade dos dados, Coursera: Guia inicial do Google Cloud Platform e do Qwiklabs, Introdução ao laboratório: Melhore a qualidade dos seus dados, Demonstração do laboratório: Melhore a qualidade dos seus dados, O que é a análise de dados exploratória?, Como a EDA é usada no machine learning?, Análise e visualização de dados, Introdução ao laboratório: Explore os dados usando Python e o BigQuery
Introdução, Aprendizado supervisionado, Regressão linear, Introdução ao laboratório: Introdução à regressão linear, Demonstração do laboratório: Introdução à regressão linear, Regressão logística
Introdução, Machine learning x aprendizado profundo, O que é machine learning automatizado?, Modelo de regressão de AutoML, Avaliar modelos de AutoML
Introdução, Como treinar um modelo de ML usando o BigQuery ML, Modelos suportados no machine learning do BigQuery, Introdução ao laboratório: Como usar o BigQuery ML para prever o peso de um pinguim (BigQuery ML e Explainable AI), Demonstração do laboratório: Como usar o BigQuery ML para prever o peso de um pinguim (BigQuery ML e Explainable AI), Ajuste de hiperparâmetros do BigQuery ML, Como criar e implantar um sistema de recomendações com o BigQuery ML
Introdução, Como definir modelos de ML, Introdução ao conjunto de dados do curso, Introdução às funções de perda, Gradiente descendente, Como solucionar problemas de curvas de perda, Problemas dos modelos de ML, Laboratório da aula:  Introdução ao TensorFlow Playground, Laboratório da aula:  TensorFlow Playground - Avançado, Laboratório da aula:  Como praticar usando redes neurais, Métricas de desempenho, Matriz de confusão
Introdução, Generalização e modelos de ML, Quando interromper o treinamento de modelo, Como criar amostras repetíveis no BigQuery, Demonstração: Como dividir os conjuntos de dados no BigQuery
Resumo, Recurso: Todas as perguntas dos testes, Recurso: Todas as leituras, Recurso: Todos os slides (English only)
Course: Gemini for Network Engineers - 日本語版
Modules:
ネットワーク エンジニア向けの Gemini の概要, Gemini を使用したエンタープライズ ネットワークの設計
Course: Creative Coding for Designers Using Python
Modules:
Specialization Overview, Meet Your Instructor, Summary of Course 2, Course Overview, Introduction to Our Learning Environment, Project 1: Particle Systems, Adding Forces, Particle Lifespan, Drawing Particle Trails, Creating a Force Class, Closest Object Calculation, Particles Interact with Force/s, Creating Forces & Particles Dynamically
Project 2: Vector Fields, Vector Data From Perlin Noise, Calibrating the Vector Field, Calculating a Vector from Position Data, Vector from Mouse History, Painting Vectors with Mouse History, Neighboring Vectors, Neighboring Vectors 2, Calibrating the Paint Tool, Particles Over Vector Field
Project 3 - Ecosystem Simulation, Herbivore Simulation, Herbivore Simulation 02 - Decision Tree, Herbivore Simulation 03 - Transitions, Herbivore Simulation 04 - Wander, Herbivore Simulation 04 - Seek Food, Herbivore Simulation 05 - Eating Food, Herbivore Simulation 06 - Starvation, Calibrating the Ecosystem, Expanding the Ecosystem
Project 4: Pathfinding, Environment Customization, Accessing Neighbors, Flood Fill Calculation, Considering Obstacles, Optimal Path, A-Star Algorithm, A-Star Algorithm Part 2, Visualizing A-Star Data, Expanding the Pathfinding System
Project 5: Wave Function Collapse, Environment, Tile Compatibility, Collapsing a Cell, Propagation, Neighbor Compatibility, Lowest Entropy, Visualizing Possibilities, Image Tile Sets, Wrap Up, What's Next?
Course: UX Design in Practice: Accessibility and Collaboration
Modules:
Introduction to Applying UX Design in Practice: Accessibility and Collaboration, Bringing mockups to life: Using visual design principles, Crafting high-fidelity mockups in Figma, Conquering challenges in high-fidelity mockups, Incorporating user feedback into mockups, Mobile vs. web design: A user's journey, Mobile vs. web design: A case study, Visual design, high-fidelity mockups, and platform considerations wrap up
Module introduction: Accessibility and inclusive design, The business case for inclusive design, A day in the life of a user with visual impairments, Ensuring readability: Using a color contrast checker tool, WCAG success criteria for beginners, Practical application of WCAG, Accessibility and inclusive design wrap up
Module introduction: AI for UX design, The future of UX design with AI, Beyond automation: The art and science of AI in UX design, AI for UX design wrap up
Module introduction: Collaborative design and communication, The power of collaboration in UX design, Collaboration tools for UX designers, Design storytelling: Captivating your audience, Conflicting or ambiguous direction, Navigating stakeholder and client conversations with key messaging, The importance of feedback in UX design, Case study: Using feedback for a successful design outcome, Turning setbacks into stepping stones, Feedback as a catalyst for growth, Collaborative design and communication wrap up
Module introduction: Portfolio presentation and job resources, UX designer portfolio myths debunked, Using PowerPoint to showcase design, Secrets of a winning design portfolio, Crafting a great UX design resume, Succeeding in the UX interview, Networking for UX designers: Strategies and tips, Portfolio presentation and job resources wrap up, Applying UX Design in Practice: Accessibility and Collaboration summary
Course: Personnes, technologie et futur de la mobilité
Modules:
Quel avenir pour la mobilité ?, Définition de la mobilité, Qu’est-ce que l’électrification ?, Qu’est-ce que l’automatisation ?, Mobilité passée, présente et future : du rail aux routes à ?
Présentation des véhicules électriques, Fonctionnement d’une batterie Li-ion, Gestion des batteries, Fabrication d’une batterie dans le Battery Lab de l’UM, Dans quelle mesure les batteries sont-elles sûres ?
Recharge et infrastructure de recharge, Véhicules électriques et système d’alimentation, Perspectives industrielles sur les applications de l’électrification (1re partie), Perspectives industrielles sur les applications de l’électrification (2e partie), Perspectives publiques sur les applications de l’électrification | Entretien avec Missy Stults, Partenariats public-privé, Processus de cartographie des acteurs
Quels liens entre équité et mobilité ?, Définition du développement durable dans le contexte de la mobilité, Perspectives industrielles sur le développement durable, Répercussions de l’électrification—Perspective environnementale, Répercussions de l’électrification—Perspective en matière de santé, Répercussions de l’électrification—Perspective en matière de justice énergétique, Électrification et emplois du futur
Présentation des véhicules autonomes, Technologie de détection embarquée, Facultatif : balade en navette autonome et conférence, Les bases de l’intelligence artificielle, Chat sur les données de conduite et l’intelligence artificielle, Perspectives industrielles sur les technologies d’automatisation, Perspectives industrielles sur l’automatisation des véhicules, Perspectives des administrations locales sur l’automatisation des véhicules, Perspectives des administrations étatiques sur l’automatisation des véhicules
Répercussions de l’automatisation—Considérations relatives à la sécurité, Répercussions de l’automatisation—Perspective de l’urbanisme, Risques et problèmes relatifs à la confidentialité/aux données, Répercussions de l’automatisation—Perspective juridique, Répercussions de l’automatisation sur les emplois, Le futur de la mobilité : et ensuite ?
Course: AWS: Monitoring, Logging and Governance
Modules:
Tagging Resources in AWS, Amazon CloudWatch - Logs, Amazon CloudWatch - Metrics & Alarms, Amazon EventBridge - Events, AWS X-ray - Overview, AWS X-ray - Implementation, Implement Tagging
AWS Service Catalog, AWS Service Catalog: Data Protection, AWS Service Catalog - Lab, AWS Proton, AWS Proton: Templates and Bundles, AWS Proton - Lab Part 1, AWS Proton - Lab Part 2, AWS Resilience Hub, AWS Resilience Hub Workflow, AWS Resilience Hub Interface Introduction, AWS Resilience Hub - Lab Part 1, AWS Resilience Hub - Lab Part 2
AWS Serverless Application Repository, AWS Serverless Application Repository: Benefits and Workflow, AWS Serverless Application Repository: Publish SAM, AWS Serverless Application Repository: Create S3 Bucket, AWS Serverless Application Repository: Test and Verify
Course: Angular for Front End Engineers
Modules:
Navigating Codio Assignments, How to Reset an Assignment in Codio, Creating HTML Elements, Decorating Elements with CSS, JavaScript Overview
Angular CLI, Angular Components, Developing Todo Items
Storing Todo List, Multiple Components & Emits, Introduction to Testing
Course: Hot Topics in Criminal Justice
Modules:
Welcome and Course Introduction (4:34), Incarceration Rates in the United States and Europe (7:29), Legal Reasons for Differences Between U.S. and European Incarceration Rates (11:00), Cultural Reasons for Differences Between U.S. and European Incarceration Rates (15:40), Additional Cultural Reasons for Differences Between U.S. and European Incarceration Rates (19:08), Can Incarceration Trends Be Reversed?  (8:29)
Introduction: Reducing Reliance on Harsh Prison Terms (8:28), Purposes of Punishment (11:36), The Accuracy of Sentencing Determinations (11:09), Treatment Programs (10:48), The Autonomy Principle (11:32), Pure Preventive Detention (14:50)
Cases in Which the Insanity Defense is Raised (10:14), Legal Definitions of Defenses Based on Mental Disability (17:19), The Outer Boundaries of Mental State Defenses (15:47), Legal Claims Based on Neuroscience and Neurogenetics (17:31), Mental Disability and Dispositions After Conviction (12:56)
History and Structure of the Death Penalty (11:05), Economics of the Death Penalty & Interrogations (11:40), Eyewitness Identifications (15:11), Labs and Adversarialism (16:09), The Influence of Elections, Jury Confusion, and Race on Death Sentences (13:23)
How Often do Police Use Force and Against Whom? (12:40), The Law of Deadly Force and Stop and Frisk (12:07), The Law of Car Stops and Searches (14:48), The Exclusionary Rule and Damages Remedies (16:11), Oversight Boards, Training, and Structural Reforms (21:47)
The Definition of Search Under the Fourth Amendment (12:09), The Knowing Exposure, General Public Use and Contraband-Specific Doctrines (14:41), The Assumption of Risk Doctrine (20:15), Reasons to Regulate Police Surveillance (12:09)
End of Course Final Quiz
Course: Introducción al marketing en redes sociales
Modules:
Introducción al Certificado de profesional del marketing en redes sociales de Facebook, Presentación de Anke Audenaert, Introducción al marketing en redes sociales: Presentación, Carreras en marketing digital, Panorama de las redes sociales: Presentación, Introducción al marketing, Introducción al marketing digital, Introducción al marketing en redes sociales, Redes sociales y empresas, Redes sociales y ONG, Categorización de las redes sociales, La historia de Facebook, Productos de Facebook: Presentación, Panorama de las redes sociales: Conclusión
Plataformas de redes sociales: Presentación, Usar Facebook para conectar personas y empresas, Atraer y entretener con videos en YouTube, Establecer conexiones en WhatsApp y Messenger, Conexión, interacción y transacciones en WeChat, Encontrar personas interesadas en lo que haces en Instagram, Entablar conexiones profesionales en LinkedIn, Usar videos cortos para conectarse en TikTok, Aprovechar el poder de los mensajes en Snapchat, Ser parte de la conversación en Twitter, Mostrar tus productos y servicios en Pinterest, Conectarse con nichos en las redes, Plataformas de redes sociales: Conclusión
Objetivos y planificación: Presentación, ¿Qué son los objetivos de marketing y para qué sirven?, Establecer tus objetivos SMART de marketing, ¿Qué son los KPI y para qué sirven?, Establecer los KPI de marketing, Objetivos y planificación: Conclusión
Comprender a tu público: Presentación, ¿Qué es el público objetivo y para qué sirve?, Definir tu público objetivo, ¿Qué es el recorrido del cliente y para qué sirve?, Delinear el recorrido de tu cliente, Comprender a tu público: Conclusión
Elegir tus canales de redes sociales: Presentación, Elegir bien tus plataformas, Identificar la plataforma adecuada para tu público, Trabajar con las políticas de redes sociales, Crear una política de redes sociales, Usar un blog empresarial, Gestionar un blog, Elegir tus canales de redes sociales: Conclusión y felicitaciones
Course: Excel Modeling for Professionals: Best Practices & Pitfalls
Modules:
Introduction: Excel Course for Professionals, Expert Video: Ingeborg Hawighorst - Is Excel the answer?, Expert Video: Importance of good input data, and how to check it, Expert Video: The importance of Formatting in Excel, Expert Video: Why is documentation important?
Recap “Fundamentals” and Intro “Functions & Formulas” in Excel, Expert Video: Pitfalls of commonly used Functions & Formulas, Expert Video: Functions and Formulas, Expert Video: Functions and Alternatives
Recap “Functions & Formulas” and Intro “Structure & Flow” in Excel, Expert Video: Linear and logical spreadsheet flow, Expert Video: Keep it Simple, Expert Video: Protection and Hidden Information
Recap “Structure & Flow” and Intro “Finishing Touches” in Excel, Charts, Pivot Tables, and Reporting (Gasper Kamensek), Charts, Pivot Tables, and Reporting (Henk Vlootman), Expert Video: Checking, Testing, and Validation, Expert Video: Finalization
Course: Advanced R Programming
Modules:
Welcome to Advanced R Programming
Control Structures Overview, if-else, for Loops, Nested for loops, next, break, Summary, Functions Overview, Code, Function interface, Default values, Re-factoring code, Dependency Checking, Vectorization, Argument Checking, R package, When Should I Write a Function?, Summary
Swirl Lesson
What is Functional Programming?, Core Functional Programming Functions, Map, Reduce, Search, Filter, Compose, Partial Application, Side Effects, Recursion, Summary, Expressions, Environments, Execution Environments, What is an error?, Generating Errors, When to generate errors or warnings, How should errors be handled?, Summary
Swirl Lesson
Debugging Overview, traceback(), Browsing a Function Environment, Tracing Functions, Using debug() and debugonce(), recover(), Final Thoughts on Debugging, Summary, Profiling Overview, microbenchmark, profvis, Find out more, Summary, Non-standard evaluation, Summary
OOP Overview, Object Oriented Principles, S3, S4, Reference Classes, Summary, Overview, Reuse existing data structures, Compose simple functions with the pipe, Embrace functional programming, Design for humans
Course: Water Governance & Economics
Modules:
Welcome to the PepsiCo Water Stewardship Training Program!
Module 2 Assessment, 2.1 - 2.2 Knowledge Check, 2.3 - 2.4 Knowledge Check
Module 3 Assessment, 3.1 - 3.3 Knowledge Check, 3.4 - 3.6 Knowledge Check
Module 4 Assessment, 4.1 - 4.3 Knowledge Check, 4.4 - 4.7 Knowledge Check
Final Course Assessment
Course: Creating Trust & Support
Modules:
Intro to Leading StandOut Teams: Course 5, Authenticity Builds Trust, The Right Information at the Right Time, Removing Obstacles, Firsthand Information
Dangling from Ropes above a Pit of Crocodiles, Future Focused, Yes, Do More of That, It's a Tricky Conversation
Be Up Front About Having Their Backs, Protect and Praise, Leveraging Strengths, Rituals and Commitments, Congratulations, You Did It!
Course: Learn React Router 6
Modules:
React Router Section 1 Quiz
React Router Section 2 Quiz
React Router Section 3 Quiz
React Router Section 4 Quiz
React Router Section 5 Quiz
React Router Section 6 Quiz
Course: Mastering Ansible Automation
Modules:
Navigating Codio Assignments, How to Reset an Assignment in Codio, YAML: Files and Syntax (Optional Download), Managing Hosts (Optional Download), Error Handling (Optional Download)
Navigating Codio Assignments, How to Reset an Assignment in Codio, File Management (Optional Download), Package Management (Optional Download), User Management (Optional Download)
Navigating Codio Assignments, How to Reset an Assignment in Codio, Creating Your Own Roles (Optional Download), Third Party Modules (Optional Download), Capstone Project (Optional Download)
Course: Foundations of Teaching for Learning: Introduction to Student Assessment
Modules:
How societies use assessment and what you believe are the purposes of assessment, Formative & Summative: Understanding the impact of timing on assessment decisions, The Curriculum-Teaching-Assessment cycle: A framework for integrating assessment with instruction, Cultural Concern: Perspectives of minorities on educational assessment, Discussion 1
Feedback Effectiveness: Hattie & Timperley’s framework; Gan’s Question prompts, Building Feedback into Teaching: Goals/Intentions; Strengths & Weaknesses, Teacher & Student perceptions of feedback, Cultural Concern: Perspectives of minorities on appropriate feedback mechanisms, Interview 1
Reporting useful feedback: Where now, where going, what next?, Grades, ranks, and scores: Problems with using these approaches, Reporting against objectives, not test questions or items, Cultural Concern: Perspectives of minorities on appropriate reporting mechanisms, Discussion 2
Anatomy of a good MCQ: The Question and Answer, Anatomy of a good MCQ: The Wrong Answers, Valid alternatives to bad MCQ: Binary choice; Matching, Valid alternatives to bad MCQ: Sequencing; Sorting, Interview two
Human judgement: Being aware of the errors we make, Guiding judgements: Analytic & Holistic Rubric design and use, Essay marking: Working towards more reliable and valid scoring, Moderation: A key to ensuring reliable and valid scoring, Discussion 3
Rationale and Goals of Involving Students: Improved learning & self-regulation, Good Peer Assessment practices, Good Self-Assessment practices, Concerns with peer and self-assessment: Keeping in mind validity, Interview 3
Course: Foundations of DevOps and Git
Modules:
DevOps Introduction, What Is DevOps and Tools Covered, Resources, Create an AWS Account
Git Introduction, Content Overview, Before Starting with the Course, About Your Trainer, What Is Version Control System and Why Git, Install Git on Window, Set Up an EC2 Instance and Install Git, Working with Git Bash, Creating a Repository on Git, Git Workflow, Working with Git Stages, Compare Code Changes with Different Git Stages, Compare Code Changes with Different Local Commits, Why Do We Need GitHub, Creating GitHub Account, Creating a Repo on GitHub Account, Cloning a Repo from GitHub, Push Code onto Remote Repository, Working with Other Developer Code, Git Clone Versus Git Pull, Unable to Push Changes onto Remote Repository, Connecting to GitHub Using SSH, Map Local Repo with Remote Repository - Git Remote Add, How a Java Developer Pushes Code onto a Remote Repository, Working with Commits on Git, Know Information about Specific Commit on Git, Working with Commits on GitHub, Commit Changes Directly on GitHub
Course: Educación Matemática para profesores de infantil. Curso 1
Modules:
Bienvenida al programa, Bienvenida al curso 1
Introducción al curso, Introducción al módulo, Tipos de lógica, Conectar proposiciones, Formas de expresar cantidad, Relaciones lógicas
Enseñanza y aprendizaje de la lógica. Parte 1, Enseñanza y aprendizaje de la lógica. Parte 2, Clasificación. Parte 1, Clasificación. Parte 2, Seriación, Tipos de tareas sobre patronoes, Representación gráfica de la lógica elemental
Introducción, Elementos geométricos en el plano, Elementos de los polígonos, Regularidades y simetrías, Elementos geométricos básicos en el espacio
Pensamiento espacial, Espacio y tiempo, Posición de los objetos, Reconocimiento de formas geométricas, Enseñanza del espacio y la geometría, Estrategias para la enseñanza y el aprendizaje del espacio de la geometría. Parte 1, Estrategias para la enseñanza y el aprendizaje del espacio de la geometría. Parte 2, Cierre curso 1
Course: Cannabis, Chronic Pain, and Related Disorders
Modules:
Introduction to Module, Lecture - What is Chronic Pain?, Interview with Beth Darnall, Lecture - The Epidemiology of Chromic Pain, Lecture - The Etiology of Chronic Pain, Lecture - Current Treatments for Chronic Pain, Lecture - Cannabis and Chronic Pain
Introduction to Module, Lecture - What is Opioid Use Disorder?, Lecture - Epidemiology of Opioid Use Disorder, Lecture - The Etiology of Opioid Use Disorder, Lecture - Traditional Treatments for Opioid Use Disorder, Lecture - Cannabis and Opioid Use Disorder, Interview with Ziva Cooper
Introduction to Module, Lecture - Definition and Epidemiology of Obesity and Type II Diabetes, Lecture - Current Treatments for Obesity and Type II Diabetes, Lecture - Cannabis, Obesity, and Type II Diabetes, Lecture - Sleep and Sleep Disorders, Lecture - Etiology and Current Treatments for Sleep Disorders, Lecture - Cannabis and Sleep, Interview with Russell Bowler
Introduction to Module, Lecture - Cancer Overview, Interview with David Camidge, Lecture - Can Cannabis Cause Cancer?, Lecture - Studies on Cannabis Use in Patients, Lecture - Is Cannabis Effective in Treatment of Cancer Symptoms?, Interview with Donald Abrams