dipopotamus/custom_instruct_coursera_course_module_list huggingface dataset:
Course: ERPO: A Civil Approach to Gun Violence Prevention Teach-Out
Modules:
Welcome to "ERPO: A Civil Approach to Gun Violence Prevention Teach-Out"
An Introduction to Clinicians as Petitioners for ERPO from Dr. Katherine Hoops, Psychiatric Inpatient Clinical Scenario, Pediatric/Emergency Department Clinical Scenario, Geriatric/Ambulatory Clinical Scenario, Final Summary on Clinicians as Petitioners for ERPO from Dr. Katherine Hoops
An Introduction to Law Enforcement as Petitioners for ERPO from Dr. Shannon Frattaroli, Interview with Major Martin Bartness of Baltimore City Police Department, Interview with Commonwealth's Attorney Anton Bell of Hampton, VA, Concluding Thoughts on Law Enforcement as Petitioners for ERPO from Dr. Shannon Frattaroli
Interview with Dorothy Paugh, Suicide Prevention Activist of Bowie, MD, Interview with Lauren Footman, Director of Outreach & Equity at Coalition to Stop Gun Violence, Interview with Sergeant Carol Adams of Richmond, VA Police Department & the Carol Adams Foundation
Public Health Advocacy Overview, Elements of Policy Advocacy, Translating Data, Power Analysis and Opportunity, Implementation
Recording of Live Webinar Discussion
Course: Los Objetivos de Desarrollo Sostenible para las empresas
Modules:
Introducción al curso
Introducción al módulo, ¿Qué es el desarrollo sostenible?, ¿Por qué es importante el desarrollo sostenible para las empresas?, ¿Qué son los ODS?
Introducción al módulo 2, ¿Qué es la empresa?, Modelo de negocio, Cadena de valor, Introducción a los servicios ecosistémicos, ¿Qué son los servicios ecosistémicos y cuáles son?, ¿Quiénes son los interesados?, Cómo dar foco a la priorización
Introducción al módulo 3, Diálogo sobre priorización, Ruta de priorización, Estructura de proyectos, Malas prácticas frecuentes
Introducción al módulo 4, ¿Qué papel juega la comunicación?, Estrategia de comunicación, Conversatorio sobre greenwashing, Cierre del curso
Course: PM4R Agile: 5 pasos para gestión híbrida de proyectos
Modules:
0.1.1 Bienvenida al curso, 0.1.2 Información importante del curso, 0.1.3 Conoce a tu instructor y al equipo del curso
1.1.3 El caso de reconversión urbana acceso sur. Paso 1
2.1.3 El caso de reconversión urbana acceso sur. Paso 2
3.1.3 El caso de reconversión urbana acceso sur. Paso 3
4.1.3 El caso de reconversión urbana acceso sur. Paso 4
5.1.3 El caso de reconversión urbana acceso sur. Paso 5
6.1.1 Conclusiones del curso, 6.1.3 ¿Es interesante aplicar PM4R agile en alguna parte de tu proyecto?, 6.1.4 Profundiza tus conocimientos, 6.1.6 Fin del curso
Course: International Business I
Modules:
Module 1, Intro, Module 1, Part 1, Module 1, Part 2, Module 1, Part 3, Module 1, Part 4, Module 1, Part 5
Module 2, Intro, Module 2, Part 1, Module 2, Part 2, Module 2, Part 3, Module 2, Part 4, Module 2, Part 5, Module 2, Part 6
Module 3, Intro, Module 3, Part 1, Module 3, Part 2, Module 3, Part 3, Module 3, Part 4, Module 3, Part 5, Module 3, Part 6, Module 3, Part 7
Module 4, Intro, Module 4, Part 1, Module 4, Part 2, Module 4, Part 3, Module 4, Part 4, Module 4, Part 5
Module 5, Intro, Module 5, Part 1, Module 5, Part 2, Module 5, Part 3, Module 5, Part 4, Module 5, Part 5
Module 6, Intro, Module 6, Part 1, Module 6, Part 2, Module 6, Part 3, Module 6, Part 4, Module 6, Part 5, Module 6, Part 6
Course: ART of the MOOC: Public Art and Pedagogy
Modules:
Introduction to Art of the MOOC
Sculptures and Monuments, From Land Art to the Production of Space, Memorial Reenactments & Public Acts, Prompt-Overview of Project Assignment, Claire Doherty (CC), Tom Finklepearl, Rick Lowe, Enrique Peñalosa (CC)
Displacement Project, Movement at Site of Tension Project
Media as Social Form, State, Church, and Corporation as Media, Intentional Communities and Science as Muse, Prompt-Overview of Project Assignment, Fran Ilich, Cesare Pietroiusti, Ruangrupa, Greg Sholette, Caroline Woolard
Invent a Country, Church, or Corporation Project, Transform an Institution Project
Experimental Pedagogy, Prompt-Overview of Project Assignment, Tania Bruguera, Sean Dockray (CC), Suzanne Lacy, Cesare Pietroiusti
The Anti-Lecture Project, Mass Drawing Experiment Project
Course: The Ancient Greeks
Modules:
Introduction: the Natural Setting, Geography and Climate, Minoan Civilization (ca. 1800-1500 BCE), Mycenaean Civilization (ca. 1500-1150 BCE), The Dark Ages (ca. 1150-800 BCE), Homer 1 - Iliad, Homer 2 - Odyssey
The Polis, "The Greeks Overseas": Colonization, Literacy, Lawgivers and Law Codes, The Works of Ares - Hoplite Warfare, New Voices, the Lyric Poets, Hesiod: Gods and Farmers
Sparta 1- Conquest, Sparta 2 - Consolidation and the Spartan Way of Life, Tyrants and Sages, Athens 1 - The Social and Economic Situation Through 600 BCE, Athens 2 - Solon: Poetry, Politics and Economics, Athens 3 - Peisistratos: Tyranny and Civic Identity
The End of Athenian Tyranny and the Democratic Revolution, The Reforms of Kleisthenes, Herodotus and the Creation of Historical Writing, Persian Wars 1 - From the Ionian Revolt (499-494 BCE) to the Battle of Marathon (490 BCE), "Wooden Walls": Themistocles and the Athenian fleet, Persian Wars 2 - Endgame - to the Battles of Thermopylae and Salamis (480 BCE) and Plataea (479 BCE)
The Aftermath of the Persian Wars; the Delian League, From Delian League to Athenian Empire, Pericles: aristocrat, orator, and radical democrat, Tragedy and Athenian civic life; Sophocles' Antigone (441 BCE), Women in Greek Society, The Periclean Building Program
"Thucydides the Athenian Wrote the War", The Outbreak of the War (431 BCE) and Pericles' Strategy, Kleon, a "New Politician." The Peace of Nicias (421 BCE), Comedy and Athenian Civic Life, War Resumes; the Conquest of Melos (416 BCE), Alcibiades: Aristocrat, General, and Libertine
The Sicilian Expedition (416-413 BCE) and its Aftermath, Slaves and Foreigners in Athenian Life, The Last Years of the War; the Battles of Arginusae (406 BCE) and Aegospotami (404 BCE). The Thirty Tyrants, Socrates, The Fourth Century. Philip II and Alexander, Conclusion
Syllabus, Assessment and Grading
Course: Hacking COVID-19 — Course 1: Identifying a Deadly Pathogen
Modules:
Biological Data Analytics: Introduction Video, Chapter 1: The Emergence of COVID-19
Hacking COVID-19 — Chapter 2: Sequencing the Virus
Course: Gestão de Captação, Recompensas, Remuneração e Diversidade
Modules:
Desenvolvimento de Fontes de Captação, Marca Organizacional (Employer Branding), Técnicas para Definição do Perfil de Pessoas, Formas de Realizar a Captação, Técnicas Utilizadas para Selecionar, Acolhimento das Pessoas pela Organização
Formas de Remuneração e Recompensa, Definição da Remuneração Fixa - Cargos, Definição da Remuneração Fixa - Competências, Remuneração Variável de Curto e Longo Prazos, Benefícios e Práticas Flexíveis, Gestão da Massa Salarial da Organização
Critérios para Definição de Potenciais, Retenção de Talentos: Monitoramento, Indicadores de Sucesso na Retenção de Talentos, Passos para o Dimensionamento do Quadro, Técnicas para Dimensionar o Quadro, Análise do Fluxo de Pessoas
Diversidade nas Organizações, Inclusão, Diversidade e Inclusão de Gênero, A Questão de Gênero nas Organizações, Letramento Racial para Empresas - Parte 1, Letramento Racial para Empresas - Parte 2, Diversidade e Dimensões da Sexualidade, Segurança Psicológica no Contexto LGBTI+, A Evolução dos Programas de Gestão da Diversidade nas Empresas, As Práticas de RH Voltadas para a Diversidade
Course: Agile Software Development
Modules:
Welcome and Course Intro, What software development looks like?, Intro to Software Development Models, Why Agile?, Agile Manifesto: Principles, Benefits and Challenges of Agile, Agile: When to Use and When NOT to!, Applying an Agile Mindset to a Project, Agile Frameworks
Gathering Requirements: The agile way, User Stories: The currency of agile development, Characteristics of good user stories, Generating User Stories, Agile Estimation and Planning, Estimation Styles and Process, Velocity, Release Planning, Release Tracking
Scrum Overview, Sprint Planning, Sprint Tracking, Sprint Execution and Daily Standups, Sprint Review, Sprint Retrospective
XP Overview, XP Values, XP Practices - Part 1, XP Practices - Part 2, XP Process Model
Course: Blockchain Opportunities Beyond Crypto Assets
Modules:
Module introduction, Transactions, blocks, and fees overview, UTXO versus account models, Throughput and settlement, Zero-knowledge proof, Zero-knowledge proof (continued), Domain-specific applications and supply chain, Supply chain question debrief, Supply chain, Health care and digital identity, Financial services, Accounting and auditing, Auditchain, Tax and decentralized marketplaces, Legal, Smart contracts, Module summary
Course: BigQuery Fundamentals for Snowflake Professionals
Modules:
Coursera: Getting Started with Google Cloud Platform and Qwiklabs
BigQuery Data Definition Model
BigQuery and Google Cloud IAM
BigQuery Data Ingestion
BigQuery Schema Design and Optimization
SQL in BigQuery
Course: Financial Reporting Capstone
Modules:
Capstone Overview, About Prof Li, Learn on Your Terms
Project 1 Overview, Instructions for Project 1.1 Journal Entries for Accrual Accounting, Instructions for Project 1.2 Journal Entries for Inventory & Accounts Receivable, Instructions for Project 1.3 Journal Entries for Investments, Instructions for Project 1.4 Journal Entries for Long-Term Assets, Instructions for Project 1.5 Journal Entries for Contingencies
Project 2 Overview, Instructions for Project 2.1 Journal Entries for Bonds, Instructions for Project 2.2 Journal Entries for Leases, Instructions for Project 2.3 Journal Entries for Pension, Instructions for Project 2.4 Journal Entries for Equity Transaction & Equity-Based Compensation
Project 3 Overview, Instructions for Projects 3.1-3.3 Balance Sheet & Income Statement (Including Basic & Diluted EPS), Congratulations on completing the course!, Get Your Course Certificate
Course: Deep Learning - Crash Course 2023
Modules:
Welcome, Course Introduction
Artificial Neural Networks, Activation Function, Bias, Data, Applications of Data, Models, Loss Functions, Learning Algorithms and Model Performance
Installing Jupyter Notebook, Accessing Google Colab, Python Basics - Data Types, Python Basics - Containers in Python, Control Statements Python if…else, Python Control statements - While and For, Functions and Classes in Python
NumPy Part 1, NumPy Part 2, NumPy Part 3, Pandas in Python - Pandas Series, Pandas Data Frame, Cleaning and Examining the data, Plotting with Matplotlib, Contour Plots
MP Neuron Introduction, Intuition of Data, Loss and Finding Parameters, Mathematical Intuition
MP Neuron - Data Import, Train Test Split, Modify Data, MP Neuron in Python, MP Neuron Class
Summary
Perceptron, Perceptron Model and Its Representation, Loss Function and Parameter Update, Why Update Rule Works, Update Rule in Programs
Perceptron in Python, Visualize the Accuracy with Epochs
Perceptron Limitations, Sigmoid Neuron Introduction, Sigmoid Neuron Data, Sigmoid Intuition, Manual Fitting of Data, Gradient Descent, Program Overview, Program in Python
Download Dataset, Data Standardization - 1, Data Standardization - 2, Class Sigmoid
Introduction to Probability and Random Variables, Why Random Variable Is Important, Random Variable - Types, Probability Distribution Table, Why Do We Require Entropy Loss
Why Deep Neural Networks, Linear Separation of Data
Understanding Universal Approximation Theorem, Confirming Universal Approximation Theorem Works, Going Deep into Neural Networks, Challenges in Creating Deep Neural Networks from Scratch
Quick Recap on Deep Learning, Introducing TensorFlow, Building a Neural Network with TensorFlow, Create First Neural Network with TensorFlow, Training the Neural Network, Training Evaluation, Summary
Activation Functions in Deep Learning Neural Networks - Introduction, Various Activation Functions, Summary on Activation Functions, Common Network Configuration
Moving from Shallow Learning to Deep Learning, Keras Basics, Types of Problems, ReLU, SoftMax, and Cross Entropy, Implementing Multi-Class Classification Using Keras, Regression Problem, TensorFlow Advanced Tricks - Ways to Create Neural Networks, TensorFlow - Subclassing Methods
Course: Fundamentos de Inteligência Artifical em Marketing
Modules:
Aula 1 | Transformação Digital em Marketing, Data-Driven Marketing - Parte 1, Data-Driven Marketing - Parte 2, Ciência de Dados e o Marketing, Cientista de Dados: O Novo Profissional de Marketing, Desafios Tecnológicos, Aplicações da Ciência de Dados
Inteligência Artificial, O que é Inteligência Artificial, Machine Learning, Deep Learning, Aplicações de I. A.
Introdução ao Aprendizado de Máquina, Processos do Machine Learning, Métodos Supervisionados, Métodos não-supervisionados, Métodos de Aprendizado por Reforço
Modelos de Regressão, Modelos de Regressão - Regressão Linear, Algoritmos de Classificação, Algoritmos de Agrupamento, Deep Learning e Redes Neurais, Encerramento
Course: Topics in Applied Econometrics
Modules:
Welcome to Topics in Applied Econometrics, Random Regressors, Simultaneous Equation Models, Identification of Parameters, The Estimating Equation
Panel Data, The Solow Growth Model, Fixed Effects Models, Estimation of the Model
Random Effects Model, Fixed or Random Effects, The Use of Time, Dynamic Panel Data
Linear Probability Models, Logit and Probit Models, Marginal Effects, The Multinomial Model
Course: ML Pipelines on Google Cloud en Español
Modules:
Introducción al curso, Empezar a usar Google Cloud y Qwiklabs
TensorFlow Extended (TFX), Conceptos de TFX, Componentes de datos estándar de TFX, Componentes de modelos estándar de TFX, Nodos de canalizaciones de TFX, Bibliotecas de TFX, Introducción al lab: Explicación de TFX
Organizadores de TFX, Apache Beam, TFX en Cloud AI Platform, Introducción al lab: Canalizaciones de TFX en Cloud AI Platform
Componentes personalizados de TFX: funciones de Python, Componentes personalizados de TFX: contenedores y subclases, CI/CD para flujos de trabajo de canalizaciones de TFX, Introducción al lab: Explicación del lab de CI/CD
Metadatos de canalizaciones de TFX, Modelo de datos de ML Metadata de TFX, Introducción al lab: Metadatos de canalizaciones de TFX
Aplicaciones de entrenamiento alojadas en contenedores, Aloje en contenedores aplicaciones de PyTorch, scikit‑learn y XGBoost, Kubeflow y AI Platform Pipelines, Entrenamiento continuo, Introducción al lab: Entrenamiento continuo con modelos de TensorFlow, PyTorch, XGBoost y scikit-learn con KubeFlow y AI Platform Pipelines
¿Qué es Cloud Composer?, Conceptos básicos de Apache Airflow, Canalizaciones de entrenamiento continuo con Cloud Composer (datos), Canalizaciones de entrenamiento continuo con Cloud Composer (modelo), Apache Airflow, contenedores y TFX, Introducción al lab: Canalizaciones de entrenamiento continuo con Cloud Composer
Introducción, Descripción general de los desafíos de desarrollo del AA, Cómo se superan estos desafíos con MLflow, Seguimiento de MLflow, Proyectos de MLflow, Modelos de MLflow, Registro del modelo de MLflow, Demostración: Implemente MLflow de forma local., Demostración: MLflow con Databricks Community Edition
Resumen del curso
Course: Bienestar, equidad y derechos humanos
Modules:
Para comenzar...1.1, ¿Por qué tomar este curso?, Para terminar... 1.1, Para comenzar...1.2, El concepto de bienestar, Dimensiones del bienestar, Para terminar...1.2, Para comenzar...1.3, Los conceptos de desigualdad, inequidad y equidad, Los conceptos de equidad y posición social, Posición social e inequidad, Diferenciando las desigualdades de las inequidades, Para terminar...1.3
Para comenzar...2.1, Concepto de derechos humanos, Características de los derechos humanos, Tipos de derechos humanos, Mecanismos para asegurar que disfrutamos de lo que nos merecemos, Tú y yo también participamos en la realización de los derechos, Para terminar...2.1, Para comenzar...2.2, El concepto de enfoque basado en los derechos humanos, Características del enfoque basado en los derechos humanos, Características relacionadas con los agentes sociales implicados y las metas que se persiguen, Para terminar...2.2, Para comenzar...2.3, ¿Cómo promovemos el bienestar desde el enfoque basado en los derechos humanos?, Criterio # 1. Disponibilidad, Criterio # 2. Accesibilidad, Criterio # 3. Aceptabilidad, Criterio # 4. Calidad, Para terminar...2.3, Para comenzar...2.4, Mecanismos de exigibilidad: una particularidad del enfoque basado en los derechos humanos, El enfoque de derechos y otras aproximaciones de intervención, Ventajas y desafíos del enfoque basado en los derechos humanos, Para terminar...2.4
Para comenzar...3.1, Enfoque Vs Perspectiva, El prisma de la igualdad, Diferentes perspectivas, múltiples inequidades, Para terminar...3.1, Para comenzar...3.2, Reconociendo nuestra posición social, Quitándole la máscara a la inequidad: Pasos 1 y 2, Quitándole la máscara a la inequidad: Pasos 3 y 4, Quitándole la máscara a la inequidad: Pasos 5, 6 y 7, Para terminar...3.2, Para comenzar...3.3, Las herramientas de la perspectiva diferencial, Características de la persona, Características de la familia y de la red social, Características de los servicios y del contexto normativo, político y cultural, Cambiando de perspectiva, Para terminar...3.3, Para comenzar...3.4, Las ideas principales de este curso, Lecciones aprendidas, Para terminar...3.4
Course: The Growth Mindset
Modules:
Welcome to the Growth Mindset!, Introduction to Thomas and Priya, Foundations of a Growth Mindset, Benefits and Characteristics of a Growth Mindset, 4-Step Mindset Shift Process, The Art of Becoming, Mindset Is A Spectrum, Organizations Can Exhibit a Growth Mindset
External Roadblocks to Growth Mindset, Limiting Beliefs, Comparison Trap Syndrome, Negative Self-Talk
Organizational Mindset, Fostering An Organization, Fixed vs. Growth Mindset of Leaders, Fixed vs. Growth Mindset of CEOs, Growth Mindset Leadership, Positivity Quotient, Group Think, Navigating Change
The Perfectionist Syndrome, The Five-Minute Pity Party, Redemptive Story Reframe, Giving and Receiving Feedback, Thomas Reframe Example, Reality Check of Growth Mindset, Course Summary and Moving Forward
Course: Perspectives in Digital Transformation: Manufacturing
Modules:
0.1 Course Welcome
1.1.1 The importance of manufacturing for Latin America and the Caribbean, 1.2.1 Manufacturing and today’s world, 1.2.4 Manufacturing needs for Digital Transformation
2.1.1 Global perspectives of digital solutions in manufacturing, 2.1.5 Interview: Trends and best practices in manufacturing, 2.2.1 Digital solutions to achieve transformation, 2.3.3 Digital Transformation for sustainable manufacturing
3.1.1 Key best practices for successful Digital Transformation, 3.2.1 Digital Transformation roadmap, 3.2.5 From strategy to a comprehensive Digital Transformation, 3.4.1 Digital maturity levels, 3.4.5 Course Ending
Course: From Figma to Code
Modules:
Test your knowledge!
Test your knowledge!
Test your knowledge!
Test your knowledge!
Test your knowledge!
Course: MaaS: Adoption and Use
Modules:
Course introduction, Definition and potentials, MaaS Typology, Conclusion, MaaS subscription decision, The bundling configuration decision, Effect of MaaS on travel patterns, Is MaaS truly a sustainable alternative?
Course: Persone, tecnologia e futuro della mobilità
Modules:
Qual è il futuro della mobilità?, Definizione di mobilità, Che cos'è l'elettrificazione?, Che cos'è l'automazione?, Passato, presente e futuro della mobilità: dai binari alle strade a...?
Introduzione ai veicoli elettrici, Come funziona una batteria agli ioni di litio?, Come vengono gestite le batterie, Realizziamo una batteria nel Battery Lab dell'Università del Michigan, Quanto sono sicure le batterie?
Ricarica e infrastrutture di ricarica, Veicoli elettrici e sistema di alimentazione, Opinioni del settore sulle applicazioni dell'elettrificazione (Parte 1), Opinioni del settore sulle applicazioni dell'elettrificazione (Parte 2), Opinioni del governo sulle applicazioni dell'elettrificazione | Intervista con Missy Stults, Partenariati pubblico-privato, Processo di mappatura delle parti interessate
Cosa c'entra l'equità con la mobilità?, Cos'è la sostenibilità nel contesto della mobilità?, Opinioni del settore sulla sostenibilità ambientale, Impatti dell'elettrificazione: prospettiva ambientale, Impatti dell'elettrificazione: prospettiva sulla salute, Impatti dell'elettrificazione: prospettiva di giustizia energetica, Elettrificazione e lavori del futuro
Introduzione ai veicoli autonomi, Tecnologia di rilevamento basata sul veicolo, Facoltativo: Giro su navetta autonoma e dibattito, Nozioni di base sull'intelligenza artificiale, Discorso su dati di guida e intelligenza artificiale, Opinioni del settore sulle tecnologie di automazione, Opinioni del settore sull'automazione dei veicoli, Opinioni del governo locale sull'automazione dei veicoli, Opinioni del governo statale sull'automazione dei veicoli
Impatti dell'automazione: considerazioni sulla sicurezza, Impatti dell'automazione: prospettiva di pianificazione urbana, Rischi e privacy/problemi relativi ai dati, Impatti dell'automazione: punto di vista legale, Impatti dell'automazione sui posti di lavoro, Il futuro della mobilità: cosa ci aspetta?
Course: Prompt Engineering for Web Developers
Modules:
Welcome to the Course!, Intro: What is Prompt Engineering?, Prompt Engineering Basics, Part 1, Prompt Engineering Basics, Part 2, Quiz: Prompt Engineering Basics, Control the length and format of GPT's responses, Challenge: Haiku-ish Generator, Break Tasks Into Smaller Steps, Quiz: Break Tasks into Smaller Steps, Prompt Iteratively: Prompt, Evaluate, Repeat, Optimize prompts, Challenge: Build a Simple Modal with an Optimized Prompt, Role-based prompting, Practice: Plan an App with Role-Based Prompting, Prompt with Examples, Challenge: Seltzer Flavor Generator, Solution: Seltzer Flavor Generator, Beware Hallucinating!, Recap: Prompt Engineering
Intro: AI Assisted Coding, Generate code with pseudocode, Generate code using a pseudo language, Challenge: Generate a Form with Pseudo Language, Generate Edge Cases, Generate Test Cases, Practice: Test a function and generate edge cases, Debugging and Error Messages, Convert Code, Challenge: Convert Code, Document Code, Study Web Development via Prompt Engineering, Pt 1, Study Web Development via Prompt Engineering, Pt 2, Review and Practice: Study Web Development, Explore APIs with Bard, Get Help with Git and Github, Get Help Deploying, When to Step Back from AI, Recap: AI-Assisted Coding
New Quiz
Course: Creating Global Brands with Jagdish Sheth
Modules:
Course Intro, How to Create a Successful Global Brand - 01, How to Create a Successful Global Brand - 02, How to Create a Successful Global Brand - 03, How to Create a Successful Global Brand - 04, How to Create a Successful Global Brand - 05, How to Create a Successful Global Brand - 06, How to Create a Successful Global Brand - 07, How to Create a Successful Global Brand - 08, How to Create a Successful Global Brand - 09, How to Create a Successful Global Brand - 10, How to Create a Successful Global Brand - 11, How to Create a Successful Global Brand - 12, How to Create a Successful Global Brand - 13, How to Create a Successful Global Brand - 14, How to Create a Successful Global Brand - 15, How to Create a Successful Global Brand - 16
How Great Companies Build World Class Brands - 01, How Great Companies Build World Class Brands - 02, How Great Companies Build World Class Brands - 03, How Great Companies Build World Class Brands - 04, How Great Companies Build World Class Brands - 05, How Great Companies Build World Class Brands - 06, How Great Companies Build World Class Brands - 07, How Great Companies Build World Class Brands - 08, How Great Companies Build World Class Brands - 09, How Great Companies Build World Class Brands - 10, How Great Companies Build World Class Brands - 11
Course: Git for beginners with Hands-on Labs
Modules:
GIT Course Introduction, GIT Introduction, Local and Remote Repositories, Install GIT, Intialize a GIT Repository, Demo: Initialize a GIT Repository, GIT Log
Git Branches, GIT Merging branches
Initialize Remote Repositories, Pushing to remote repositories, Cloning remote repositories, Pull Requests, Fetching and Pulling, GIT - Merge Conflicts, Fork
Rebasing, Interactive Rebasing, Cherry Picking
Resetting and Reverting, Stashing, Reflog, Understanding GIT, Conclusion
Course: Innovation publique et pensée design, l'innovation sociale au service des territoires
Modules:
Introduction générale, Introduction de l'épisode 1, MDPH du Val d'Oise, Hôpital gériatrique de jour du CHU de Strasbourg, Médiathèque intercommunale de Lezoux, Laure de la Bretèche, SGMAP, Florence Bannerman, Conseil départemental du Val d'Oise, Frédéric Moulin, Deloitte, Stéphane Vincent, 27ème Région, Gaël Guilloux, Ecole de design Nantes Atlantique, Prenons du recul, Allons plus loin Partie 1, Allons plus loin Partie 2, Consignes du travail en correction par les pairs
Introduction de l'épisode 2, MDPH du Val d'Oise, Hôpital de jour du CHU de Strasbourg, Médiathèque intercommunale de Lezoux, Julie de Brito Ventura, Conseil départemental de Loire Atlantique, Cécile Lachaux et Brigitte Daniel, Conseil Départemental du Val d'Oise, Jean-Claude Charlet, ESSEC, Prenons du recul Partie 1, Prenons du recul Partie 2, Allons plus loin Partie 1, Allons plus loin Partie 2, Consignes du travail en correction par les pairs
Introduction de l'épisode 3, MDPH du Val d'Oise, Hôpital de jour du CHU de Strasbourg, Médiathèque intercommunale de Lezoux, Sandrine Dujardin-Frère et Véronique Petitjean, Conseil départemental de Seine-Maritime, Alexandre Mussche et Khadija El Mennani Vives, Conseil départemental du Val d'Oise, Romain Thévenet, DTA, Paul Hubert des Mesnards, Xavier Pavie, ESSEC, Prenons du recul, Allons plus loin Partie 1, Allons plus loin Partie 2, Consignes du travail en correction par les pairs
Introduction de l'épisode 4, MDPH du val d'Oise, Hôpital de jour du CHU de Strasbourg, Médiathèque intercommunale de Lezoux, Stéphane Gauthier, Babel, Catherine Neveu, Conseil départemental du Val d'Oise, Vincent Guesdon, Deloitte, Yoan Ollivier, Plausible Possible, David L'Hote, Strate College, Prenons du recul, Allons plus loin, Consignes du travail en correction par les pairs
Course: Social Impact Strategy with Goldman Sachs 10,000 Women
Modules:
Why do businesses care about social purpose?, Embedding your values into your core business practices, How has embedding their values helped our alumni?, Theories of Change: Outcomes, outputs and impacts
Course: Crystal Structures and Properties of Metals
Modules:
Mini Course #2 Introduction Video
Crystal Structure, Part 1, Crystal Structure, Part 2, Planes in Unit Cells, Part 1, Planes in Unit Cells, Part 2, Planes in Unit Cells, Part 3
Crystal Structure, Part 4, Crystal Structure, Part 5, Crystal Structure, Part 6, Crystal Structure, Part 7
Mechanical Properties, Part 1, Mechanical Properties, Part 2, Mechanical Properties, Part 3, Tensile Testing, Part 1, Tensile Testing, Part 2, Tensile Testing, Part 3
Mechanical Properties, Part 1, Mechanical Properties, Part 2, Mechanical Properties, Part 3, Mechanical Properties, Part 4, Failure, Part 1, Failure, Part 2, Failure, Part 3, Course Review
Course: Smart Analytics, Machine Learning, and AI on GCP en Français
Modules:
Présentation du cours
Présentation du module, Qu'est-ce que l'IA ?, Prendre des décisions basées sur les données à partir d'analyses de données ad hoc, Options pour les modèles de ML sur Google Cloud
Présentation du module, Les données non structurées sont difficiles à traiter, API de ML pour enrichir les données, Présentation de l'atelier : Utiliser l'API Natural Language pour classer du texte non structuré, Coursera : Premiers pas avec Google Cloud Platform et Qwiklabs
Présentation du module, Qu'est-ce qu'un notebook ?, La magie de BigQuery et la liaison avec Pandas, Présentation de l'atelier : BigQuery dans JupyterLab sur Vertex AI
Présentation du module, Différentes façons d'exploiter le ML sur Google Cloud, Vertex AI Pipelines, TensorFlow Hub, Présentation de l'atelier : Exécuter des pipelines sur Vertex AI, Résumé
Présentation du module, BigQuery ML pour créer rapidement des modèles, Modèles compatibles, Présentation de l'atelier : Prédire la durée des trajets à vélo avec un modèle de régression dans BigQuery ML, Présentation de l'atelier : Recommandations de films dans BigQuery ML, Résumé
Présentation du module, Pourquoi Auto ML ?, AutoML Vision, Service AutoML de traitement du langage naturel, AutoML Tables, Résumé
Résumé du cours
Smart Analytics, Machine Learning and AI on Google Cloud
Course: Google Cloud Platform Big Data and Machine Learning Fundamentals em Português Brasileiro
Modules:
Introdução ao curso
Introdução, Computação, Armazenamento, A história de produtos de ML e Big Data, Categorias de produtos de machine learning e Big Data, Exemplo de cliente: Gojek, Primeiros passos com o Google Cloud Platform e o Qwiklabs, Introdução ao laboratório: Como analisar um conjunto de dados público do BigQuery, Resumo
Introdução, Desafios do Big Data, Arquitetura orientada por mensagens, Como projetar pipelines de streaming com o Apache Beam, Como implementar pipelines de streaming no Cloud Dataflow, Visualização com o Looker, Visualização com o Data Studio, Introdução ao laboratório: Como criar um pipeline de dados de streaming para um painel em tempo real com o Dataflow, Resumo
Introdução, Armazenamento e análise, Demonstração do BigQuery: compartilhamento de bicicletas em São Francisco, Introdução ao BigQuery ML, Como usar o BigQuery ML para prever o valor de vida útil do cliente, Fases dos projetos do BigQuery ML, Principais comandos do BigQuery ML, Introdução ao laboratório: Como usar o BigQuery ML para prever as compras dos visitantes, Resumo
Introdução, Opções para criar modelos de ML, APIs pré-criadas, AutoML, Treinamento personalizado, Vertex AI, Soluções de IA, Resumo
Introdução, Preparação de dados, Treinamento de modelos, Avaliação de modelos, Implantação e monitoramento de modelos, Introdução ao laboratório: Como prever o risco de empréstimos com o AutoML, Resumo do laboratório: Como prever o risco de empréstimos com o AutoML, Resumo
Resumo do curso
Course: 心理学与生活
Modules:
课程介绍
颜色：超越视觉, 知觉：超越理解, 错觉：超越事实, 记忆：给我一杯忘情水, 重构：那些不真实的回忆, 大脑中有记忆开关吗？, 时间都去哪儿了？, 梦：你有第六感吗？
延迟满足, 婴儿气质, 情感依恋, 咿呀学语, 性别认同, 游戏人间, 学习方式, 行为塑造
需要：情绪和情感的催化剂, 具身认知：谁说情绪是主观的, 微表情：你会察言观色吗, 所谓爱情：认知神经的视角, 互补：你们是因为这个相爱的吗？, 共情：学会与他人联接！, 吃喝玩睡：与压力同行, 上网：痛并快乐着
你未必知道的人格, 你不知道的东西潜意识知道, 你运用自如的自我防御机制, 为什么广告会有用：人本主义的解释, 你的心理正常吗？, 挨千刀的心灵鸡汤：行为主义的视角, 人心，可测吗？, 血型与星座，你信吗？
情境：你并没有那么自由, 服从：唤醒内心的“邪恶”, 归因：保护自己的尊严, 社会认知：情人眼里出西施, 助人行为：不能相信的媒体, 认知失调：求助的女神最美, 态度：谁能改变你的行为, 群体行为：被别人“惯”坏的你
Course: Powering the Drive: Unveiling EV Electronics
Modules:
Welcome and Meet Your Instructor, Role and Significance of Power Electronics in Electric Vehicles, Key Components of Electric Vehicle Power Electronics, Fundamentals of Inverters and Converters in EVs, Overview of Power Electronics Topologies in Electric Vehicles, Pulse-Width Modulation (PWM) in EV Power Electronics, H-Bridge and Multilevel Converters in Electric Vehicles, Control Strategies in Electric Vehicle Power Electronics, Algorithms for Efficient Power Conversion in EVs, Real-World Applications of Control Strategies, Energy Management and Range Optimization
Course: How Google does Machine Learning 日本語版
Modules:
専門講座「GCP での機械学習」の概要, Google が選ばれる理由, Google Cloud が選ばれる理由
AI ファーストとは, ML の 2 つの段階, Google のサービスにおける機械学習, Google フォトの機械学習, Google 翻訳と Gmail, ヒューリスティック ルールの置き換え, 事前トレーニング済みモデル, Sara Robinson と機械学習について学習する（単なるルールではない ML）, Vision API の実用例, Video Intelligence API, Cloud Speech-to-Text API, 翻訳と NL4, Text-to-Speech, DialogFlow, ラボの概要: 事前トレーニング済み機械学習 API の概要, ラボでのソリューション: 機械学習 API を呼び出す, 機械学習にはデータが最重要, データ戦略, トレーニング / サービング スキュー, 機械学習のトレーニング フェーズ, ラボの概要 - ML の問題のフレーム化, ラボのまとめ, デモ: アプリケーションにおける ML
ML 戦略, ビジネスの変革, 概要, ML の意外性, 秘訣, ML とビジネス プロセス, フェーズの終了についての詳細な説明
ML と人間のバイアス, 包括性の評価指標, 統計的判断指標と許容されるトレードオフ, 機会均等, 判断のシミュレーション, Facets を使用したデータセット内のエラーの検出
モジュールの概要, AI Platform Notebooks, デモ: AI Platform Notebooks, 開発プロセス, コンピューティングとストレージ, ラボの概要: AI Platform Notebooks と BigQuery を使用したデータの分析, ラボのまとめ: AI Platform Notebooks と BigQuery を使用したデータの分析
コースのまとめ
Course: Visualizing Data in the Tidyverse
Modules:
About This Course, Data Visualization Background, General Features of  Plots
Plot Types, Histogram, Densityplot, Scatterplot, Barplot, Boxplot, Line Plots
Choose the Right Type of Plot, Be Mindful When Choosing Colors, Label the Axes, Make Sure the Numbers Add Up, Make Sure the Numbers and Plots Make Sense Together, Make Comparisons Easy on Viewers, Use y-axes That Start at Zero, Keep It Simple
Three Questions You Should Ask
ggplot2 Background, Example Dataset: diamonds, Scatterplots: geom_point(), Aesthetics, Facets, Geoms, EDA Plots
Colors, Labels, Themes, Custom Theme, Legends, Scales, Coordinate Adjustment, Annotation, Vertical and Horizontal Lines
Tables, Tables in R, Getting the Data in Order, An Exploratory Table, Improving the Table Output, Annotating Your Table
ggrepel, directlabels, cowplot, patchwork, gganimate
Case Study #1: Health Expenditures, Exploratory Data Analysis (EDA), Q1: Relationship between coverage and spending?, Q2: Spending Across Geographic Regions?, Q3: Coverage and Spending Change Over Time?, Case Study #2: Firearms, Exploratory Data Analysis (EDA), Q: Relationship between Fatal Police Shootings and Legislation?
Visualizing Data in the Tidyverse Course Project
Course: Measuring and Modeling Impact in Evaluations
Modules:
Introduction to course and instructors, Overview of Impact Measures for Reproductive, Maternal, Neonatal and Child Health (RMNCH), Course learning objectives
Introduction and Challenges in Measuring Mortality, Maternal Mortality
Intro to Under-five mortality, Using Household Surveys and Censuses to Estimate Mortality: Direct and Indirect Methods, Modeling Mortality: Examples of IGME and LiST, Exercise on under-five mortality: Child Mortality, Deaths around the time of birth
Nutrition and Growth as Impact: Introduction, Nutrition and Growth as Impact: Indicators, Nutrition Data sources and methods
Additional Impact Measures, Morbidity, Birth Outcomes
Learning objectives and outline, Learning objectives and outline, What is LiST, LiST History, LiST's General Approach, Calculating Impact in LiST, Estimating Intervention Coverage, Impact and Results in LiST, LiST in Spectrum, Advantages and Limitations of LiST, Learning objectives and outline, Desktop LiST vs. LiST Online, Overview of LiST on Desktop, LiST Online: Explore Data, LiST Online: Create a Projection, Learning objectives and outline, LiST for Strategic Planning, LiST for Evaluation, LiST for Advocacy
Learning objectives and outline, Overview of Nutrition in LiST, Stunting in LiST, Maternal Anemia in LiST, Birth Outcomes in LiST, Breastfeeding in LiST, Wasting in LiST, Additional Features, Creating a projection using nutrition targets, Learning objectives and outline, Background and Terminology, Maternal Mortality in LiST, Neonatal Deaths in LiST, Stillbirths in LiST, Exploring Maternal Mortality, Neonatal Mortality and Stillbirths in the LiST Visualizer, Learning objectives and outline, Subnational Models in LiST, Subnational Modeling Challenges, Creating a Subnational Projection in LiST Online, Learning Objectives and Outline, Missed Opportunities, Using Missed Opportunities in LiST Online, Equity Tool, LiST Visualizer
Course: Challenges of Agribusiness Management
Modules:
Introductory Video, Intro Week 1, Population growth, The calories challenge, Income growth, Prosumerism and food scares, Perceptions and embeddedness, Sources and causes of climate changing emissions, Commoditization and price transmission in the chain, Agriculture value added
Intro Week 2, Players of the agribusiness, Competitive Dynamics 1, Competitive Dynamics 2, From subsistence to complexity, The US Agricultural System, The Brazilian Agricultural System, The Chinese Agricultural System, The Indian Agricultural System, The EU Agricultural System, The Italian Case: Industry History and Evolution, The Italian Case: Cultivating Excellence, The Italian Case: Techniques and technology in an unfavourable landscape
Intro Week 3, Sustainability in agriculture, Analysing the large-scale land acquisitions phenomenon, Crafting a sustainable strategy in the agrifood business, Enhancing ecosystem services, Natural and Organic, Complementarity and multifunctionality, The benefits of cooperation, Engaging farmers on common business strategies
Intro Week 4, Innovation essentials, Product and Service Innovation, Vertical Farming, Biotech, Efficiency and Big Data, Earth observation: Agriculture from high above
Wrap up - Challenges of Agribusiness Management
Course: Sprachtechnologie in den Digital Humanities
Modules:
1.1 - Wege in die digitale Welt, 1.2 - Herausforderungen bei der Korpusakquisition, 1.3 - Digitalisierungszentrum ZB
2.1 - XML-Standards zur Textrepräsentation, 2.2 - Textsegmentierung
3.1 - Eigenschaften von Korpora und Analysemethoden, 3.2 - Hands-on Korpusanalysen, 3.3 - Visualisierung und graphische Darstellung
4.1 - Bestimmung von Wortarten und Grundformen, 4.2 - Erkennung, Klassifikation und Linking von Named Entities, 4.3 - Syntaktische Analyse
5.1 - Manuelle Annotation und Evaluation, 5.2 - Möglichkeiten und Probleme beim Crowdsourcing
6.1 - Automatische Sprachidentifikation, 6.2 - Sprachübergreifende Alignierung
Course: Составление бюджета и графиков проектов
Modules:
Обзор курса, Опрос по курсу
2.1. Лекция, 2.3. Практический пример, Бонусное видео: Советы для определения потребностей проекта в ресурсах
3.1 Лекция, 3.3. Практический пример, Бонусное видео: Избегайте этих ошибок при оценке
4.1 Лекция, 4.3. Практический пример, Бонусное видео: Возвращение к сетевой диаграмме
Дискуссия по управлению проектами
Course: 工程圖學 3D CAD 專題
Modules:
CAD/BIM專項課程歡迎你！, 101 認識本課程, 103 如何通過本課程
201 3D建築模型繪製順序, 202 建模注意事項, 203 SketchUp匯入CAD圖
301 群組(Group), 302 SketchUp 繪製一樓樓板, 303 SketchUp 繪製柱, 304 SketchUp 繪製牆, 305 SketchUp 繪製梁, 306 SketchUp 調整牆高至梁底
401 SketchUp 繪製第一段樓梯與樓梯平台, 402 SketchUp 繪製第二、三段樓梯, 403 SketchUp 修整樓梯與建立群組, 404 SketchUp 繪製第一段樓梯扶手, 405 SketchUp 繪製第二段樓梯扶手, 406 SketchUp 繪製第三段樓梯扶手, 407 SketchUp 繪製二樓樓板
測驗一
601 元件(Component), 601 SketchUp 繪製Ｗ2窗戶元件, 602 SketchUp 繪製DW1窗戶元件, 603 SketchUp 繪製DW2窗戶元件, 604 SketchUp 繪製D4門基本外型, 605 SketchUp D4門上色與修飾, 606 SketchUp 繪製D4門門把
701 SketchUp 匯入元件, 702 SketchUp 建立開口與放置W2元件, 703 SketchUp 建立冷氣口元件, 704 SketchUp 放置SD1鐵捲門元件, 705 SketchUp 放置D1大門與D4房間門元件, 706 SketchUp 放置衛浴門
801 模型組合, 802 材質與陰影, 803 SketchUp 模型表面檢查, 804 SketchUp 材質蒐集、建立與調整, 805 SketchUp 元件上材質, 806 SketchUp 各樓層模型組合, 807 SketchUp 模型陰影, 808 SketchUp 匯出圖檔
測驗二
回顧 Part 1, 回顧 Part 2, GO! 前進BIM!
Course: Business Transformation with Google Cloud en Español
Modules:
Le damos la bienvenida al curso
Introducción e innovaciones en la historia, ¿Qué es la nube?, El peligro de mantener el statu quo, Un cambio de paradigma, Potencia de procesamiento extraordinaria, Los datos como moneda, Productividad y automatización, Percibir, categorizar, predecir y recomendar, ¿Qué significa esto para usted?
Introducción y cambio de mentalidad: El garaje de la innovación, Cultura: Lleve la mentalidad innovadora a gran escala, Empresas: Tres reglas simples, Cultura de innovación: Industria bancaria, ¿Qué significa esto para usted?
Introducción y transformación frente al proyecto de mejora a gran escala, Cómo escribir un desafío de transformación sólido, Cree un mapa de su ecosistema de datos para obtener estadísticas, Priorice los desafíos comerciales según las estadísticas, Cómo evaluar los posibles resultados con un marco de trabajo de transformación, Cómo elaborar un desafío empresarial sólido
Introducción y términos principales: privacidad, seguridad, cumplimiento y disponibilidad, ¿Cuáles son los desafíos actuales de la seguridad cibernética?, ¿Cómo puede un modelo de seguridad compartida ayudar a garantizar el éxito empresarial?, ¿Cuál es su función en el modelo de responsabilidad compartida?, ¿Cuáles son los requisitos actuales de cumplimiento y cómo puede Google Cloud ayudarlo a satisfacerlos?, ¿Cuál es su responsabilidad al mantener el cumplimiento?, ¿Qué significa esto para usted?
Introducción y cómo identificar la solución ideal para su desafío, Cómo identificar la solución ideal para su desafío, Cómo elaborar una estrategia de datos de alto nivel para su proceso de transformación, Cómo capturar los datos correctos, Cómo crear su caso empresarial, Cómo socializar su caso empresarial
Conclusión del curso y próximos pasos
Course: Introduction to Cannabis
Modules:
Preface
Cannabis Flower Production Full-Cycle
Differences Between Cannabis, Marijuana, & Hemp
Cannabis Botany
Uses of Cannabis
Cannabis Taxonomy
Cannabis Morphology
Reproductive Biology Part I
Reproductive Biology Part II
Cannabis Chemistry
Congratulations!
Course: Design and Analyze Secure Networked Systems
Modules:
Course Overview, Lesson 1.  Vulnerabilities and Threats, Method, Opportunity, and Motive, Confidentiality, Integrity, and Availability, Risk, Risk Assessment and Method of Defense, Security Principles:  Defense in Depth, Defense with Diversity, Cyber Resilience
Apply Principle of Least Privileges for Access Control, Principle of Adequate Data Protection, In Software We Trust.  Really?
Sign Software with GPG, Verify Software Integrity and Authenticity, Web of Trust
Public Key Infrastructure, What are in a Certificate?, Being Your Own CA, Server Certificate and Installation, Setup Client Certificate, Client Server Mutual Authentication
Course: TensorFlow on Google Cloud - Français
Modules:
Introduction
Présentation de l'écosystème TensorFlow, Introduction à TensorFlow, Hiérarchie des API TensorFlow, Composants de TensorFlow : Tensors et variables
Présentation, Rappel sur le ML, Entraîner un modèle avec des ensembles de données volumineux à l'aide de l'API tf.data, Travailler en mémoire avec des fichiers, Préparer les données pour l'entraînement du modèle, Représentations vectorielles continues, Coursera : Premiers pas avec Google Cloud et Qwiklabs, Présentation de l'atelier : API Dataset TensorFlow, Effectuer le scaling du traitement des données à l'aide de tf.data et de couches de prétraitement Keras, Présentation de l'atelier : Classer des données structurées à l'aide de couches de prétraitement Keras
Présentation, Fonctions d'activation, Entraîner des réseaux de neurones avec Tensorflow 2 et l'API Keras Sequential, Inférer des modèles dans le cloud, Présentation de l'atelier : Présentation de l'API Keras Sequential sur Vertex AI Platform, Entraîner des réseaux de neurones avec TensorFlow 2 et l'API Keras Functional, Présentation de l'atelier : Créer un DNN à l'aide de l'API Keras Functional sur Vertex AI Platform, Sous-classement des modèles, Principes de base de la régularisation, Mesurer la complexité d'un modèle :  comparaison entre les régularisations L1 et L2
Présentation, Entraîner des modèles à grande échelle avec Vertex AI, Présentation de l'atelier : Entraîner un modèle à grande échelle avec le service Vertex AI Training
Résumé, Ressources : toutes les questions des quiz, Ressources : tous les documents, Ressources : toutes les diapositives (English only)
Course: How To Create a Website in a Weekend! (Project-Centered Course)
Modules:
Module 1 Introduction
Module 2 Introduction
Introduction to Module 3
Introduction to Module 4, Principles of Good Web Design, Part I (Guest Lecture: Melody Kim, Coursera), Principles of Good Web Design, Part II (Guest Lecture: Melody Kim, Coursera), How to Use Your Web Browser to Inspect Website Elements (Guest Lecture: Archana Sankaranarayanan, Coursera), Using Browser Extensions to Learn About Font and Color (Guest Lecture: Archana Sankaranarayanan, Coursera), Font Color, Size and Family (Guest Lecture: Joel Aguero, Coursera), Color on the Web (Guest Lecture: Joel Aguero, Coursera), Images on the Web (Guest Lecture: Joel Aguero, Coursera)
Course: Dynamical Modeling Methods for Systems Biology
Modules:
Lecture 1 - Introduction, Lecture 2 - Computing with MATLAB - Part 1, Lecture 3 - Computing with MATLAB - Part 2, Lecture 4 - Computing with MATLAB - Part 3, Lecture 5 - Computing with MATLAB - Part 4
Lecture 6 - Introduction to Dynamical Systems - Part 1, Lecture 7 - Introduction to Dynamical Systems - Part 2, Lecture 8 - Introduction to Dynamical Systems - Part 3, Lecture 9 - Introduction to Dynamical Systems - Part 4
Lecture 10 - Bistability in Biochemical Signaling Models - Part 1, Lecture 11 - Bistability in Biochemical Signaling Models - Part 2, Lecture 12 - Bistability in Biochemical Signaling Models - Part 3, Lecture 13 - Bistability in Biochemical Signaling Models - Part 4, Lecture 14 - Bistability in Biochemical Signaling Models - Part 5, Lecture 15 - Bistability in Biochemical Signaling Models - Part 6
Lecture 16 - Computational Modeling of the Cell Cycle - Part 1, Lecture 17 - Computational Modeling of the Cell Cycle - Part 2, Lecture 18 - Computational Modeling of the Cell Cycle - Part 3, Lecture 19 - Computational Modeling of the Cell Cycle - Part 4
Lecture 20 - Mathematical Models of Action Potentials - Part 1, Lecture 21 - Mathematical Models of Action Potentials - Part 2, Lecture 22 - Mathematical Models of Action Potentials - Part 3, Lecture 23 - Mathematical Models of Action Potentials - Part 4, Lecture 24 - Mathematical Models of Action Potentials - Part 5, Lecture 25 - Mathematical Models of Action Potentials - Part 6
Lecture 26 - Modeling with Partial Differential Equations - Part 1, Lecture 27 - Modeling with Partial Differential Equations - Part 2, Lecture 28 - Modeling with Partial Differential Equations - Part 3
Lecture 29 - Stochastic Modeling - Part 1, Lecture 30 - Stochastic Modeling - Part 2
Course: Health After Cancer: Cancer Survivorship for Primary Care
Modules:
Introduction to Health After Cancer, Orientation to Health After Cancer, Words of a Patient, Case 1: Amelia, Case 2: Bob, Case 3: Seema, Case 4: Richard, Conclusion
Course: Data Visualization and Dashboards with Excel and Cognos
Modules:
Course Intro, Introduction to Charts, Interview: Using Visualizations to Tell a Data Story, Creating Basic Charts in Excel (Line, Pie, and Bar Charts), Introduction to Creating Pivot Tables in Excel, Using the Excel PivotChart Feature
Creating Treemaps, Scatter Charts, and Histograms, Creating Filled Map Charts and Sparklines, Introduction to Dashboards, Interview: Using Dashboards to Present Data Results, Creating a Simple Dashboard using Excel
Cognos Analytics: Introduction and How to Sign Up, Navigating in Cognos Analytics, Creating a Simple Dashboard in Cognos Analytics, Advanced Capabilities in Cognos Analytics Dashboards
Congratulations and Next Steps, Course Credits and Acknowledgements
Course: Driving Customer Equity with AI
Modules:
A Customer Centric View of Marketing- Part 1, A Customer Centric View of Marketing- Part 2, Connecting Customer Equity to Market Value
Acquisition Tactics and Tools- Part 1, Acquisition Tactics and Tools- Part 2, Acquisition Tactics and Tools- Part 3
Managing Retention- Part 1, Managing Retention- Part 2
Automating Marketing Interventions- Part 1, Automating Marketing Interventions- Part 2
Course: Reading and Comprehension of Text in English
Modules:
Main front page of the course, Learning Objectives and alignments
Objectives of the Unit
New Video
Objectives of the unit
Objectives of the Unit
Objectives of the Unit
Objectives of the Unit