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Google AI Essentials | 1. Introduction to AI
2. Maximize Productivity With AI Tools
3. Discover the Art of Prompt Engineering
4. Use AI Responsibly
5. Stay Ahead of the AI Curve | Introduction to AI: Discover how AI works and explore foundational AI concepts, such as machine learning (ML). Learn about the rise of generative AI and how to perform tasks with it. By the end of this module, you’ll have an understanding of the capabilities and limitations of AI tools and how to integrate generative AI in the workplace.
Maximize Productivity With AI Tools: Leverage generative AI tools to speed up work tasks and boost your productivity. Examine the important role humans play in the effective use of AI, and understand the types of workplace tasks you can augment with AI. By the end of this module, you will be able to determine if AI is right for a given task and how to use AI to accelerate workflows.
Discover the Art of Prompt Engineering: Write effective prompts to get the output you want. Learn how to incorporate prompting techniques, such as few-shot prompting, into your work. Understand how generative AI tools produce output and the importance of evaluating output before using it. By the end of this module, you will be able to write clear and specific prompts and produce outputs that help accomplish workplace tasks.
Use AI Responsibly: Use AI responsibly by mitigating unfair biases and inaccuracies. Learn how to apply a framework of AI harms to sample workplace scenarios and recognize the security risks of using AI in the workplace. By the end of this module, you will gain an understanding of how to use AI responsibly and effectively, and a checklist to help you do it.
Stay Ahead of the AI Curve: Continue developing your skills within the current and emerging AI landscape. Learn about the ways organizations have leveraged AI and consider how these innovations may inspire your own AI-powered workplace solutions. By the end of this module, you will develop a strategy to stay up-to-date with future AI developments. | Introduction to AI: Introduction to Google AI Essentials,AI and the future of work,Learn from AI success stories,Maya: The exciting world of AI,Explore how AI uses machine learning,Foundations of generative AI,Understand the capabilities and limitations of AI,Vint: Use AI for positive change,Use AI as a collaborative tool,Aleck: Make daily tasks easier with AI,Wrap-up
Maximize Productivity With AI Tools: Module 2 introduction: Maximize productivity with AI tools,Discover generative AI applications,Tris: My favorite ways to use AI,Understand how AI tools work,Transform your work with generative AI,Work with Gemini,Manvinder: Ways I use AI in my work,Leverage the human-in-the-loop approach to AI,Kathy: Explore how people improve AI models,Determine if generative AI is right for the task,Wrap-up
Discover the Art of Prompt Engineering: Module 3 introduction: Discover the art of prompt engineering,Understand large language models,Yufeng: Experiment with prompt engineering,Write clear and specific prompts,Leverage an LLM's capabilities at work,Improve AI output through iteration,Discover few-shot prompting,Rachna: Improve prompts through exploration,Wrap-up
Use AI Responsibly: Module 4 introduction: Use AI responsibly,Understand bias in AI,Identify AI harms,Emilio: My path to working in responsible AI,Security and privacy risks of AI,Jalon: My work on the responsible AI team,Shaun: Develop AI that works for everyone,Wrap-up
Stay Ahead of the AI Curve: Module 5 introduction: Stay ahead of the AI curve,Sharbani: The future of AI,Anoop: Become AI-empowered,Take inspiration from AI innovation,Reena: Find inspiration in how others have used AI,Benefits of staying up to date with AI,Greg: Keep exploring with AI,Wrap-up,Google AI Essentials Conclusion |
Foundations of Project Management | 1. Embarking on a career in project management
2. Becoming an effective project manager
3. The project management life cycle and methodologies
4. Organizational structure and culture | Embarking on a career in project management: You will learn how the program is structured, what project management is and what a project manager does, how to apply your skills from previous work experience to project management roles, what types of project management roles you could pursue after completing this certificate, and how to search for those positions.
Becoming an effective project manager: You will learn how project managers add value to organizations and to their teams, what the role and responsibilities of a project manager entail, and what core skills a project manager needs to be successful.
The project management life cycle and methodologies: You will learn about the phases of the project life cycle, what tasks they involve, and why it is important to complete them. You will also learn about the different project management methodologies and approaches and which is most effective for a given project.
Organizational structure and culture: You will learn about common organizational structures and how they impact project management, how organizational culture impacts project management, and how a project manager contributes to the change management process. Optionally, you can start to develop your strategy and professional network to help you prepare for your job search. | Embarking on a career in project management: Welcome to the Google Project Management Certificate,Introduction to Course 1,What is project management?,What does a project manager do?,Transferable project management skills,X: Path to becoming a project manager,From certificate to career success,Finding the perfect role,Gilbert: Project management skills in my role,Wrap-up
Becoming an effective project manager: Introduction: Becoming an effective project manager,The value of a project manager,JuAnne: Path to becoming a project manager,Key project manager roles and responsibilities,A project manager’s role within a team,Elita: A day in the life of a project manager,The core skills of a project manager,Rachel: My journey to becoming a project manager,Leadership and team dynamics,Ellen: Traits of a successful project manager,Wrap-up
The project management life cycle and methodologies: Introduction: The project management life cycle and methodologies,Exploring the phases of the project life cycle,Phases in action: Initiating and planning,Phases in action: Executing and closing,Introduction to project management methodologies,Overview of Waterfall and Agile,Introduction to Lean and Six Sigma,Wrap-up
Organizational structure and culture: Introduction: Organizational structure and culture,Overview of Classic and Matrix structures,How organizational structure impacts project management,Lan: Working in a Project Management Office,Introduction to organizational culture,Amar: Project management in life and in the organization,Introduction to change management,Participating in change management,Preparing for your job search,Congrats! What's coming in Course 2 |
Foundations: Data, Data, Everywhere | 1. Introducing data analytics and analytical thinking
2. The wonderful world of data
3. Set up your data analytics toolbox
4. Become a fair and impactful data professional | Introducing data analytics and analytical thinking: Data helps us make decisions in both everyday life and in business. In this part of the course, you’ll learn how data analysts use a variety of tools and skills to inform those decisions. You’ll also get to know more about this course and the overall program expectations.
The wonderful world of data: In this part of the course, you'll learn about the data life cycle and data analysis process. They are both relevant to your work in this program and on the job. You’ll also be introduced to applications that help guide data through the data analysis process.
Set up your data analytics toolbox: Spreadsheets, query languages, and data visualization tools are all a big part of a data analyst’s job. In this part of the course, you’ll learn the basic concepts to use them for data analysis. You’ll also understand how they work through interesting examples.
Become a fair and impactful data professional: In this part of the course, you’ll examine different types of businesses and the jobs and tasks that analysts do for them. You’ll also learn how a Google Data Analytics Certificate will help you meet many of the requirements for an analyst position with these organizations. | Introducing data analytics and analytical thinking: Welcome to the Google Data Analytics Certificate,Introduction to the course,Data analytics in everyday life,Cassie: Dimensions of data analytics,What is the data ecosystem?,How data informs better decisions,Discover data skill sets,Key data analyst skills,All about thinking analytically,Explore core analytical skills,Data drives successful outcomes,Witness data magic,What to expect moving forward
The wonderful world of data: Learn about data phases and tools,Stages of the data life cycle,The phases of data analysis and this program,Molly: Example of the data analysis process,Explore data analyst tools
Set up your data analytics toolbox: The ins and outs of core data tools,Make spreadsheets your friend,SQL in action,Angie: Everyday struggles when learning new skills,Become a data viz whiz,Lilah: The power of a visualization
Become a fair and impactful data professional: Let's get down to business,The job of a data analyst,Joey: Path to becoming a data analyst,Tony: Supporting careers in data analytics,The power of data in business,Rachel: Data detectives,Understand data and fairness,Alex: Fair and ethical data decisions,Data analysts in different industries,Samah: Interview best practices,Congratulations! Course wrap-up |
Foundations of Cybersecurity | 1. Welcome to the exciting world of cybersecurity
2. The evolution of cybersecurity
3. Protect against threats, risks, and vulnerabilities
4. Cybersecurity tools and programming languages | Welcome to the exciting world of cybersecurity: Begin your journey into cybersecurity! You'll explore the cybersecurity field, and learn about the job responsibilities of cybersecurity professionals.
The evolution of cybersecurity: You will explore how cybersecurity threats have appeared and evolved alongside the adoption of computers. You will also understand how past and present cyber attacks have influenced the development of the security field. In addition, you'll get an overview of the eight security domains.
Protect against threats, risks, and vulnerabilities: You will learn about security frameworks and controls, which are used to mitigate organizational risk. You'll cover principles of the CIA triad and various National Institute of Standards and Technology (NIST) frameworks. In addition, you'll explore security ethics.
Cybersecurity tools and programming languages: You’ll discover common tools used by cybersecurity analysts to identify and mitigate risk. You'll learn about security information and event management (SIEM) tools, network protocol analyzers, and programming languages such as Python and SQL. | Welcome to the exciting world of cybersecurity: Welcome to the Google Cybersecurity Certificate,Welcome to week 1,Introduction to cybersecurity,Toni: My path to cybersecurity,Responsibilities of an entry-level cybersecurity analyst,Nikki: A day in the life of a security engineer,Core skills for cybersecurity professionals,Veronica: My path to working in cybersecurity,The importance of cybersecurity,Wrap-up
The evolution of cybersecurity: Welcome to module 2,Past cybersecurity attacks,Attacks in the digital age,Sean: Keep your cool during a data breach,Introduction to the eight CISSP security domains, Part 1,Introduction to the eight CISSP security domains, Part 2,Wrap-up
Protect against threats, risks, and vulnerabilities: Welcome to module 3,Introduction to security frameworks and controls,Secure design,Heather: Protect sensitive data and information,Ethics in cybersecurity,Holly: The importance of ethics as a cybersecurity professional,Wrap-up
Cybersecurity tools and programming languages: Welcome to module 4,Common cybersecurity tools,Introduction to Linux, SQL, and Python,Wrap-up,Course wrap-up |
AI For Everyone | 1. What is AI?
2. Building AI Projects
3. Building AI In Your Company
4. AI and Society | What is AI?:
Building AI Projects:
Building AI In Your Company:
AI and Society: | What is AI?: Week 1 Introduction,Machine Learning,What is data?,The terminology of AI,What makes an AI company?,What machine learning can and cannot do,More examples of what machine learning can and cannot do,Non-technical explanation of deep learning (Part 1, optional),Non-technical explanation of deep learning (Part 2, optional)
Building AI Projects: Week 2 Introduction,Workflow of a machine learning project,Workflow of a data science project,Every job function needs to learn how to use data,How to choose an AI project (Part 1),How to choose an AI project (Part 2),Working with an AI team,Technical tools for AI teams (optional)
Building AI In Your Company: Week 3 Introduction,Case study: Smart speaker,Case study: Self-driving car,Example roles of an AI team,AI Transformation Playbook (Part 1),AI Transformation Playbook (Part 2),AI pitfalls to avoid,Taking your first step in AI,Survey of major AI application areas (optional),Survey of major AI techniques (optional)
AI and Society: Week 4 Introduction,A realistic view of AI,Discrimination / Bias,Adversarial attacks on AI,Adverse uses of AI,AI and developing economies,AI and jobs,Conclusion |
Supervised Machine Learning: Regression and Classification | 1. Week 1: Introduction to Machine Learning
2. Week 2: Regression with multiple input variables
3. Week 3: Classification | Week 1: Introduction to Machine Learning: Welcome to the Machine Learning Specialization! You're joining millions of others who have taken either this or the original course, which led to the founding of Coursera, and has helped millions of other learners, like you, take a look at the exciting world of machine learning!
Week 2: Regression with multiple input variables: This week, you'll extend linear regression to handle multiple input features. You'll also learn some methods for improving your model's training and performance, such as vectorization, feature scaling, feature engineering and polynomial regression. At the end of the week, you'll get to practice implementing linear regression in code.
Week 3: Classification: This week, you'll learn the other type of supervised learning, classification. You'll learn how to predict categories using the logistic regression model. You'll learn about the problem of overfitting, and how to handle this problem with a method called regularization. You'll get to practice implementing logistic regression with regularization at the end of this week! | Week 1: Introduction to Machine Learning: Welcome to machine learning!,Applications of machine learning,What is machine learning?,Supervised learning part 1,Supervised learning part 2,Unsupervised learning part 1,Unsupervised learning part 2,Jupyter Notebooks,Linear regression model part 1,Linear regression model part 2,Cost function formula,Cost function intuition,Visualizing the cost function,Visualization examples,Gradient descent,Implementing gradient descent,Gradient descent intuition,Learning rate,Gradient descent for linear regression,Running gradient descent
Week 2: Regression with multiple input variables: Multiple features,Vectorization part 1,Vectorization part 2,Gradient descent for multiple linear regression,Feature scaling part 1,Feature scaling part 2,Checking gradient descent for convergence,Choosing the learning rate,Feature engineering,Polynomial regression
Week 3: Classification: Motivations,Logistic regression,Decision boundary,Cost function for logistic regression,Simplified Cost Function for Logistic Regression,Gradient Descent Implementation,The problem of overfitting,Addressing overfitting,Cost function with regularization,Regularized linear regression,Regularized logistic regression,Andrew Ng and Fei-Fei Li on Human-Centered AI |
Indigenous Canada | 1. Worldview
2. Fur Trade
3. Trick or Treaty
4. New Rules, New Game
5. “Killing the Indian in the Child”
6. A Modern Indian?
7. Red Power
8. Sovereign Lands
9. Indigenous Women, Girls, and Genderful People
10. Indigenous in the City
11. Current Social Movements
12. ‘Living’ Traditions – Expressions in Pop Culture and Art | Worldview: In this introductory module, students learn the significance of stories and storytelling in Indigenous societies. We explore history that comes from Indigenous worldviews, this includes worldviews from the Inuit, Nehiyawak, Kanien:keha’ka and Tlingit peoples.
Fur Trade: This module discusses pre-contact trading systems between Indigenous peoples of North America with a focus on the geographical region of Canada. We examine the chronological events of contact with Europeans and the events leading up to, and during the fur trade. This module also explores the long lasting social, political and economic ramifications of the fur trade on Indigenous peoples.
Trick or Treaty: Examines Indigenous and settler perspectives of treaty making. Discusses the variation of treaties in Canada and the unique circumstances surrounding these events. Outlines the temporal and geographical history of the numbered treaties (beginning on the east) and ends with a discussion of the historical events and policies leading up to Métis scrip.
New Rules, New Game: This lesson begins with a discussion about what is distinctive in Indigenous legal traditions. Explores impacts of policies put in place as British North America attempted to solidify itself geographically and socially. Examines the ways in which the Indian Act contributed to assimilation.
“Killing the Indian in the Child”: Outlines characteristics of teaching and learning in Indigenous communities, and discusses how relationships were critical in teaching and learning. Traces the development and implementation of the Residential school system in the period after Confederation. Discusses intergenerational impact of Residential school system and the creation of the Truth and Reconciliation Commission.
A Modern Indian?: This lesson examines the burgeoning resistance of Indigenous leaders and the formation of Indigenous-led organizations as the Canadian government employed strategies to encourage assimilation of Aboriginal peoples and communities into mainstream society, specifically relating to urbanization.
Red Power: In this lesson students will learn about key characteristics of a few different Indigenous political structures and the impacts of colonialism on these structures (e.g. Indian Act, Red Power/AIM, White Paper, Red Paper -Citizens Plus) Concepts explored include self-government, self-determination, and Indigenous resurgence.
Sovereign Lands: Utilizing contemporary and traditional examples, this lesson connects Indigenous worldviews and traditional ecological knowledge. As well, this lesson traces the historical impacts of settlement. Discusses key concepts of case law associated with Aboriginal title, rights to land and resources. List the on-going threats to Indigenous lands and how these threats and challenges are being addressed.
Indigenous Women, Girls, and Genderful People: Exploring Indigenous concepts of gender, and the traditional roles and responsibilities, this lesson then moves into an examination of how colonization can be characterized as a gendered project. Identifies some concrete examples of the impact of colonialism on Indigenous women.
Indigenous in the City: Looking critically at the statement: “Cities are the place where Aboriginal culture goes to die”, this lesson explores sites of urban Aboriginal agency/active participation, urban Aboriginal governance practices, and urban reserves.
Current Social Movements: What is an Indigenous concept of community? How do Indigenous people form communities traditionally and today? This module will explain how social and environmental activism can mobilize and create communities. This module identifies key moments such as the Oka Crisis, Idle No More and Missing and Murdered Indigenous Women and Girls are grassroots resistance movements.
‘Living’ Traditions – Expressions in Pop Culture and Art: Finally, we will explore how geographical location, trading networks and partnerships have influenced Indigenous art in the past. As well, we will examine contemporary iterations of Indigenous art and explore some of the artistic responses of Indigenous artists, musicians, and writers to the impacts of colonialism. | Worldview: Introduction,Storytelling,Indigenous Worldviews,Reuben Quinn
Fur Trade: Pre-Contact North American Networking,Colonization,The Fur Trade,Frank Tough
Trick or Treaty: Perspectives on Treaty Making,Numbered Treaties,The Métis Nation
New Rules, New Game: Indigenous Concepts of Law,Outside Influences,Outside Influences Part 2
“Killing the Indian in the Child”: Indigenous Teaching and Learning,Residential Schooling Part 1,Residential Schooling Part 2,Truth and Reconciliation Commission
A Modern Indian?: Traditional Economies,Resource Extraction & Shifting Roles,Aboriginal Women,Education in the City Shifting Roles
Red Power: Indigenous Political Structures,Influences of the Political System of the Canadian State,Sovereignty and Governance
Sovereign Lands: Indigenous Relationship to the Land,Aboriginal Title and Right to Land,Disconnection From Indigenous Lands
Indigenous Women, Girls, and Genderful People: Indigenous Concepts of Gender,Indigenous Women,Billy-Ray Belcourt
Indigenous in the City: Urban Indigeneity,Impact of City Life,Governance
Current Social Movements: Community,Resistance,Social Media
‘Living’ Traditions – Expressions in Pop Culture and Art: Indigenous Art in the Past and Present,Indigenous Art is Political,Indigenous Voices of Relations and Community,Course Art |
Generative AI with Large Language Models | 1. Week 1
2. Week 2
3. Week 3 | Week 1: Generative AI use cases, project lifecycle, and model pre-training
Week 2: Fine-tuning and evaluating large language models
Week 3: Reinforcement learning and LLM-powered applications | Week 1: Course Introduction,Introduction - Week 1,Generative AI & LLMs,LLM use cases and tasks,Text generation before transformers,Transformers architecture,Generating text with transformers,Prompting and prompt engineering,Generative configuration,Generative AI project lifecycle,Introduction to AWS labs,Lab 1 walkthrough,Pre-training large language models,Computational challenges of training LLMs,Optional video: Efficient multi-GPU compute strategies,Scaling laws and compute-optimal models,Pre-training for domain adaptation
Week 2: Introduction - Week 2,Instruction fine-tuning,Fine-tuning on a single task,Multi-task instruction fine-tuning,Model evaluation,Benchmarks,Parameter efficient fine-tuning (PEFT),PEFT techniques 1: LoRA,PEFT techniques 2: Soft prompts,Lab 2 walkthrough
Week 3: Introduction - Week 3,Aligning models with human values,Reinforcement learning from human feedback (RLHF),RLHF: Obtaining feedback from humans,RLHF: Reward model,RLHF: Fine-tuning with reinforcement learning,Optional video: Proximal policy optimization,RLHF: Reward hacking,Scaling human feedback,Lab 3 walkthrough,Model optimizations for deployment,Generative AI Project Lifecycle Cheat Sheet,Using the LLM in applications,Interacting with external applications,Helping LLMs reason and plan with chain-of-thought,Program-aided language models (PAL),ReAct: Combining reasoning and action,LLM application architectures,Optional video: AWS Sagemaker JumpStart,Responsible AI,Course conclusion |
Foundations of Digital Marketing and E-commerce | 1. Introduction to foundations of digital marketing and e-commerce
2. The customer journey and the marketing funnel
3. Digital marketing and e-commerce strategy
4. Measure performance success | Introduction to foundations of digital marketing and e-commerce: You’ll find out what’s in store for Course 1 and the whole certificate program. You’ll also learn about the Coursera platform, procedures, and content types, and meet other learners in the program. Then, you’ll learn about digital marketing and e-commerce basics, the tasks that people who work in these fields do, and the transferable skills you might already have. Finally, you’ll get some tips for embarking on careers in this field.
The customer journey and the marketing funnel: You will learn what digital marketing and e-commerce roles and departments do within organizations and how they create value. You’ll also be introduced to marketing concepts, like the customer journey and the marketing funnel, that form the basis for much of what these roles do.
Digital marketing and e-commerce strategy: You will explore the relationship between digital marketing and branding, and how businesses can leverage both to be successful. You’ll investigate the elements of a digital marketing strategy, including goal setting, channel selection, and content planning. Then you’ll learn about commonly used channels and platforms, like search engine optimization (SEO), search engine marketing (SEM), display advertising, social media marketing, and email marketing.
Measure performance success: You will learn the importance of measuring results and common metrics to track. You’ll also examine how digital marketers and e-commerce specialists use data to assess and improve performance and tell stories with data. You’ll end the course by participating in optional content if you’re interested in preparing for a job search. | Introduction to foundations of digital marketing and e-commerce: Welcome to the Google Digital Marketing & E-commerce Certificate,Introduction to Course 1,What are digital marketing and e-commerce?,What do digital marketing and e-commerce specialists do?,Joi - Career Path To Digital Marketing,Transferable skills for digital marketing and e-commerce,Prisha - My path to working in digital marketing,Melba - My path to working in e-commerce,Andrew - My path to working in digital marketing and e-commerce,Launching your digital marketing or e-commerce career,Agency roles vs. in-house roles,Zuri - A day in the life of an entry-level digital marketer,Jebb - A day in the life of an entry-level e-commerce account manager,Wrap-up
The customer journey and the marketing funnel: Welcome to week 2,How digital marketing and e-commerce create value,Jen - Diversity in digital marketing,Janice - Inclusive marketing,Xiomara - Inclusive marketing,The customer journey and journey maps,The marketing funnel,The top of the funnel: Awareness and consideration,Measuring success at the top of the funnel,The bottom of the funnel: Conversion and loyalty,Measuring success at the bottom of the funnel,Wrap-up
Digital marketing and e-commerce strategy: Welcome to week 3,The value of brands for digital marketing,The elements of a digital marketing strategy,Define your marketing goals,Paid, owned, and earned media,Attract customers with search engine optimization,Reach customers with search engine marketing,Introduction to social media and email marketing,Social media marketing basics,Build relationships with email marketing,Wrap-up
Measure performance success: Welcome to week 4,Measure progress with performance marketing,Working with data,Attribution models for digital marketing,Data storytelling basics,Prepare for your job search,Elle - Build confidence,Wrap-up,Congrats! What’s coming in Course 2 |
Technical Support Fundamentals | 1. Introduction to IT
2. Hardware
3. Operating System
4. Networking
5. Software
6. Troubleshooting | Introduction to IT: Welcome to Technical Support Fundamentals, the first course of the IT Support Professional Certificate! By enrolling in this course, you are taking the first step to kickstarting your career in tech. In the first module of the course, we'll learn about how computers were invented, how they've evolved over time, and how they work today. We will also learn about what an "IT Support Specialist" is and what they do in their job. By the end of this module, you will know how to count like a computer using binary and understand why these calculations are so powerful for society. So let's get started!
Hardware: In the second module of this course, we'll learn about what's inside a computer. We'll learn all about the hardware components or different pieces inside a computer. We'll discover what each component does and how they work together to make a computer function. By the end of this module, you will also know how to build a computer from scratch!
Operating System: In the third module of the course we will become familiar with operating systems. We discuss the operating systems that are most widely used today and learn how an operating system interacts with computer hardware. We will learn about the startup process of an operating system and show you how to install the Windows, Linux and Mac OS X operating systems from scratch. At the end of this module you will interact directly with the Windows and Linux operating systems via the Qwiklabs environment.
Networking: In the fourth module of this course, we'll learn about computer networking. We'll explore the history of the Internet and what "The Web" actually is. We'll also discuss topics like Internet privacy, security, and what the future of the Internet may look like. You'll also understand why the Internet has limitations even today. By the end of this module, you will know how the Internet works and recognize both the positive and negative impacts the Internet has had on the world.
Software: In the fifth module of this course, we'll learn about computer software. We'll learn about what software actually is and the different types of software you may encounter as an IT Support Specialist. We'll also explore how to manage software and revisit the concept of "abstraction." By the end of this module, you'll use the Qwiklabs environment to install, update and remove software on both Windows and Linux operating systems.
Troubleshooting: Congratulations, you've made it to the last module of the course! In the final module, we'll learn about the importance of troubleshooting and customer support. We'll go through some real-world scenarios that you might encounter at a Help Desk or Desktop Support role. We'll learn why empathizing with a user is super important when working in a tech role. Finally, we'll learn why writing documentation is an important aspect of any IT role. By the end of this module, you will utilize soft skills and write documentation to communicate with others. | Introduction to IT: Program Introduction,What is IT?,What does an IT Support Specialist do?,Course Introduction,From Abacus to Analytical Engine,The Path to Modern Computers,Kevin: Their career path,Computer Language,Character Encoding,Binary,How to Count in Binary,Abstraction,Computer Architecture Overview,Kevin: Advice for the world of IT
Hardware: Module Introduction,Introduction to Computer Hardware,Programs, the CPU, and Memory,Joe: Diversity in IT,CPU,RAM,Motherboards,Physical Storage: Hard Drives,Power Supplies,Mobile Devices,Batteries and Charging Systems,Peripherals and Ports,BIOS,Ben: Skills of IT professionals,Putting it All Together: Installing The Processor,Putting it All Together: Adding the RAM And The Drive,Putting it All Together: Adding Graphics and Other Peripherals.,Mobile Device Repair,One program, many futures
Operating System: Module introduction,Components of an Operating System,Files and File Systems,Process Management,Memory Management and Virtual Memory,I/O Management,Interacting with the OS: User Space,Logs,The Boot Process,Mobile Operating Systems,Cindy: Drive and career path,Choosing an Operating System,Virtual Machines,Installing Windows 10,Installing Linux,What is Chrome OS?,Mac OS,Tri Ngo: How to overcome obstacles and become successful in IT,Introduction to Qwiklabs
Networking: Module Introduction,Basics of Networking,Networking Hardware,TCP/IP,The Web,Victor: First job experiences,History of the Internet,Limitations of the Internet,Changing Careers,Impact,Internet of Things,Gian: What he does in Android Security,Privacy and Security,Heather Adkins: keeping hackers out,Learner Story: Melinda
Software: Module Introduction,How software is built: Coding, scripting, and programming,Types of Software,Revisiting Abstraction,Recipe for Computing,Phelan: Learning IT in the Navy,Managing Software,Installing, Updating, and Removing Software on Windows,Installing, Updating, and Removing Software on Linux,Software Automation
Troubleshooting: Module Introduction,Ask Questions!,Isolating the Problem,Follow the Cookie Crumbs,Start with the Quickest Step First,Troubleshooting Pitfalls to Avoid,Amir: Attributes in an IT support space,Intro to Soft Skills,Anatomy of an Interaction,How to Deal with Difficult Situations Part I,How to Deal with Difficult Situations Part II,Ticketing Systems and Documenting Your Work,Process Documentation,Documenting in Ticketing Systems,Your Opportunity for Success,Standing Out from the Crowd,Getting Ready for the Interview,What to Expect During the Technical Interview,Showing Your Best Self During the Interview,Interview Role Play: Customer Service,Course Wrap Up,Sabrina: Technology can open doors,Congratulations! |
Play It Safe: Manage Security Risks | 1. Security domains
2. Security frameworks and controls
3. Introduction to cybersecurity tools
4. Use playbooks to respond to incidents | Security domains: You will gain understanding of the CISSP’s eight security domains. Then, you'll learn about primary threats, risks, and vulnerabilities to business operations. In addition, you'll explore the National Institute of Standards and Technology’s (NIST) Risk Management Framework (RMF) and the steps of risk management.
Security frameworks and controls: You will focus on security frameworks and controls, along with the core components of the confidentiality, integrity, and availability (CIA) triad. You'll learn about Open Web Application Security Project (OWASP) security principles and security audits.
Introduction to cybersecurity tools: You will explore industry leading security information and event management (SIEM) tools that are used by security professionals to protect business operations. You'll learn how entry-level security analysts use SIEM dashboards as part of their every day work.
Use playbooks to respond to incidents: You'll learn about the purposes and common uses of playbooks. You'll also explore how cybersecurity professionals use playbooks to respond to identified threats, risks, and vulnerabilities. | Security domains: Introduction to Course 2,Welcome to module 1,Explore the CISSP security domains, Part 1,Explore the CISSP security domains, Part 2,Ashley: My path to cybersecurity,Threats, risks, and vulnerabilities,Key impacts of threats, risks, and vulnerabilities,Herbert: Manage threats, risks, and vulnerabilities,NIST’s Risk Management Framework,Wrap-up
Security frameworks and controls: Welcome to module 2,Frameworks,Controls,Explore the CIA triad,NIST frameworks,Explore the five functions of the NIST Cybersecurity Framework,OWASP security principles,Wajih: Stay up-to-date on the latest cybersecurity threats,Plan a security audit,Complete a security audit,Wrap-up
Introduction to cybersecurity tools: Welcome to module 3,Logs and SIEM tools,SIEM dashboards,Parisa: The parallels of accessibility and security,Explore common SIEM tools,Talya: Myths about the cybersecurity field,Wrap-up
Use playbooks to respond to incidents: Welcome to module 4,Phases of an incident response playbook,Zack: Incident response and the value of playbooks,Use a playbook to respond to threats, risks, or vulnerabilities,Erin: The importance of diversity of perspective on a security team,Wrap-up,Course wrap-up |
Generative AI for Everyone | 1. Introduction to Generative AI
2. Generative AI Projects
3. Generative AI in Business and Society | Introduction to Generative AI:
Generative AI Projects:
Generative AI in Business and Society: | Introduction to Generative AI: Welcome,How Generative AI works,LLMs as a thought partner,AI is a general purpose technology,Writing,Reading,Chatting,What LLMs can and cannot do,Tips for prompting,Image generation (optional)
Generative AI Projects: Using generative AI in software applications,Trying generative AI code yourself (optional),Lifecycle of a generative AI project,Cost intuition,Retrieval Augmented Generation (RAG),Fine-tuning,Pretraining an LLM,Choosing a model,How LLMs follow instructions: Instruction tuning and RLHF (optional),Tool use and agents (optional)
Generative AI in Business and Society: Day-to-day usage of web UI LLMs,Task analysis of jobs,Additional job analysis examples,New workflows and new opportunities,Teams to build generative AI software,Automation potential across sectors,Concerns about AI,Artificial General Intelligence,Responsible AI,Course Summary,Building a more intelligent world |
Financial Markets | 1. Module 1
2. Module 2
3. Module 3
4. Module 4
5. Module 5
6. Module 6
7. MODULE 7 | Module 1: Welcome to the course! In this opening module, you will learn the basics of financial markets, insurance, and CAPM (Capital Asset Pricing Model). This module serves as the foundation of this course.
Module 2: In this next module, dive into some details of behavioral finance, forecasting, pricing, debt, and inflation.
Module 3: Stocks, bonds, dividends, shares, market caps; what are these? Who needs them? Why? Module 3 explores these concepts, along with corporation basics and some basic financial markets history.
Module 4: Take a look into the recent past, exploring recessions, bubbles, the mortgage crisis, and regulation.
Module 5: Options and bond markets are explored in module 5, important components of financial markets.
Module 6: In module 6, Professor Shiller introduces investment banking, underwriting processes, brokers, dealers, exchanges, and new innovations in financial markets.
MODULE 7: Professor Shiller's final module includes lectures about nonprofits and corporations, and your career in finance. | Module 1: Welcome video,Financial Markets Introduction,Your Teaching Assistant, Arun!,Good and Evil,VaR and Stress Tests,S&P 500,Joe McNay Story,Distribution and Outliers,Chalk Talk - Covariance,Insurance Fundamentals,Insurance Milestones,Insurance is a Local Phenomenon,Health Insurance,Disasters,Eggs in One Basket,Salon - Risk,CAPM,Chalk Talk: Beta,Chalk Talk: CAPM and Diversification,Short Sales,Calculating the Optimal Portfolio,Efficient Portfolio Frontier,Chalk Talk - Gordon Growth Model
Module 2: Invention Takes Time,Salon - Innovation,Limited Liability,Inflation Indexed Debt,Unidad de Fomento,Real Estate: Risk Management Devices,Forecasting,Intuition of Efficiency,Price as PDV,Doubting Efficiency,Introduction to Behavioral Finance,Prospect Theory,Chalk Talk - More on Prospect Theory,Logical Fallacies,The Brain,Magical Thinking,Personality Disorders
Module 3: 1982 Savings Account,Federal Funds and Interest Rates,Compound Interest,Discount Bonds,Consol and Annuity,Forward Rates and Expectation Theory,Inflation,Leverage,Market Capitalization by Country,The Corporation,Shares and Dividends,Common vs. Preferred,Corporate Charter,Corporations Raise Money,Dilution,Share Repurchase,PDV of Expected Dividends,Why do firms pay dividends?
Module 4: Salon - Recessions,History of Mortgage Lending,Commercial Real Estate Vehicles,Mortgages, part 1,Mortgages, part 2,PMI, CMOs, CDOs,Post Crisis Regulation,Chalk Talks - Excess Reserves,The Bubble, part 1,The Bubble, part 2,The Bubble, part 3,Salon - Bubbles,Regulation Overview,Salon - Regulation and housing,Within Firm Regulation, part 1,Within Firm Regulation, part 2,Trade Groups,Local Regulation,National Regulation, part 1,National Regulation, part 2,National Regulation, part 3,International Regulation
Module 5: Salon - Student Loans,Forwards and Futures Introduction,Forward Contracts,Futures Contracts,Rice Futures,Wheat Futures,Buying, Selling, and Settlement,Fair Value in Futures Contracts,Oil Futures,SPI & FFR Futures,Options Overview,Reading Options Pricing,Why Options exist,Ubiquity of Options,Put / Call parity,Using Options to Hedge
Module 6: Investment Banks Introduction,The Underwriting Process,IPOs,Goldman Sachs and John Whitehead,Ratings Agencies,Glass Steagall,Net Worth of the US,The Prudent Person,Salon - Advisors,Mutual Funds and ETFs,Brokers and Dealers,Exchanges,Limit Order Book,High Frequency Trading,Payment for Order Flow,Government Debt,Government involvement in Corporations,Municipal Finance,Government Social Insurance
MODULE 7: Nonprofits,Cooperatives,Alternative Forms,Salon - Public vs. Private,Critics of Modern Finance,Democratization of Finance,Salon - Democratization of Finance,Finance and War,Finance and Population Growth,The Importance of Financial Theory,Wealth and Poverty,Your Career and Finance,Interview with Roger Ferguson,Interview with Lei Zhang,Guest Georgia Keohane |
Ask Questions to Make Data-Driven Decisions | 1. Ask effective questions
2. Make data-driven decisions
3. Spreadsheet magic
4. Always remember the stakeholder | Ask effective questions: Data analysts are constantly asking questions in order to find solutions and identify business potential. In this part of the course, you’ll learn about effective questioning techniques that will help guide your analysis.
Make data-driven decisions: In analytics, data drives decision-making, and this is your opportunity to explore data of all kinds and its impact on all sorts of business decisions. You’ll also learn how to effectively share your data through reports and dashboards.
Spreadsheet magic: Spreadsheets are a key data analytics tool. Here you’ll learn both why and how data analysts use spreadsheets in their work. You’ll also investigate how structured thinking helps analysts understand problems and come up with solutions.
Always remember the stakeholder: Successful data analysts balance the needs and expectations of their team and the stakeholders they support. In this part of the course, you’ll learn strategies for managing stakeholder expectations while establishing clear communication with your team. | Ask effective questions: Introduction to problem-solving and effective questioning,Data in action,Nikki: The data process works,Common problem types,Continue exploring business applications,Anmol: From hypothesis to outcome,SMART questions,Evan: Data opens doors
Make data-driven decisions: Data and decisions,How data empowers decisions,Qualitative and quantitative data,The big reveal: Sharing your findings,Data versus metrics,Mathematical thinking
Spreadsheet magic: The amazing spreadsheet,Get to work with spreadsheets,Basic spreadsheet tasks,Formulas for success,Spreadsheet errors and fixes,Functions 101,Before solving a problem, understand it,Scope of work and structured thinking,Staying objective
Always remember the stakeholder: Communicating with your team,Balance needs and expectations across your team,Focus on what matters,Clear communication is key,Tips for effective communication,Navigate expectations and realistic project goals,Sarah: How to communicate with stakeholders,The data tradeoff: Speed versus accuracy,Think about your process and outcome,Meeting best practices,Ximena: Joining a new team,From conflict to collaboration,Nathan: From the U.S. Marine Corps to data analytics,Congratulations! Course wrap-up |
Project Initiation: Starting a Successful Project | 1. Fundamentals of project initiation
2. Defining project goals, scope, and success criteria
3. Working effectively with stakeholders
4. Utilizing resources and tools for project success | Fundamentals of project initiation: You will learn how the program is structured, understand the significance of a project’s initiation phase and describe its key components, and understand how to determine a project’s benefits and costs.
Defining project goals, scope, and success criteria: You will learn how to define and create measurable project goals and deliverables; how to define project scope, differentiate among tasks that are in-scope and out-of-scope, and avoid scope creep; and how to define and measure a project’s success criteria.
Working effectively with stakeholders: You will learn how to define project roles and responsibilities, complete a stakeholder analysis, and utilize RACI charts to define and communicate project team member responsibilities.
Utilizing resources and tools for project success: You will learn the typical resources needed to manage a project, recognize the importance of clear and consistent project documentation, understand the key components of project proposals and charters and develop a project charter, and evaluate various project management tools to meet project needs. | Fundamentals of project initiation: Introduction to Course 2,Why is project initiation essential?,Key components of project initiation,Afsheen: Listening to learn,Wrap-up
Defining project goals, scope, and success criteria: Introduction: Defining project goals, scope, and success criteria,Determining project goals and deliverables,How to set SMART goals,Introduction to OKRs,Determining a project's scope,Monitoring and maintaining a project's scope,Managing changes to a project's scope,Torie: The importance of staying within scope,Launching and landing a project,Defining success criteria,Wrap-up
Working effectively with stakeholders: Introduction: Working effectively with stakeholders,Accessibility for project managers,Choosing a project team,Defining project roles,John: The importance of a project team,Completing a stakeholder analysis,Elements of a RACI chart,Certificate completers: Staying motivated in the program,Wrap-up
Utilizing resources and tools for project success: Introduction: Utilizing resources and tools for project success,Essential project resources,The value of project documentation,Project proposals and charters 101,Developing a project charter,Utilizing tools for effective project management,Exploring types of project management tools,Common project management tools,Amar: Tools are our best friends,Course wrap-up |
Foundations of User Experience (UX) Design | 1. Introducing user experience design
2. Thinking like a UX designer
3. Joining design sprints
4. Integrating research into the design process | Introducing user experience design: User experience (UX) designers focus on the experience that users have while using products like websites, apps, and physical objects. UX designers make those everyday interactions useful, enjoyable, and accessible. In the first part of this course, you'll be introduced to the world of UX and the factors that contribute to great user experience design. You'll understand the job of a UX designer and teams that UX designers often work with. You’ll also get to know more about the expectations of the Google UX Design Certificate.
Thinking like a UX designer: UX designers always put the user first. In this part of the course, you'll be introduced to user-centered design and one of the design frameworks that UX designers use on the job. You'll also learn about design best practices, including the importance of inclusive design and accessibility when designing. In addition, you'll learn how to think across platforms to design seamless user experiences.
Joining design sprints: UX designers often participate in design sprints to define the direction of a product. In this part of the course, you'll explore the world of design sprints, including the phases of a design sprint and how to plan and participate in one. You'll also learn about retrospectives, which is a way to constructively reflect on a design sprint and identify areas of improvement to implement next time.
Integrating research into the design process: As a UX designer, it's your job to put the user front-and-center in everything you do. In this part of the course, you'll explore the role of research in the design process to help you better understand and empathize with users. You'll also learn about the benefits and drawbacks of common UX research methods. And, you'll identify and account for biases that can arise when conducting research. | Introducing user experience design: Welcome to the Google UX Design Certificate,Michael: Get started in UX design,Introduction to Course 1: Foundations of User Experience Design,Welcome to module 1,The basics of user experience design,Jobs in the field of user experience,The product development life cycle,Design for good user experience,Job responsibilities of entry-level UX designers,Specialists, generalists, and T-shaped designers,Dane - A day in the life of an entry-level UX designer,Erika - Generalist or specialist designer,Work in a cross-functional team,UX design jobs at different types of companies,From certificate to career success,Juan - A UX design career journey,Mike - A UX design career journey,Wrap-up: Introducing user experience design
Thinking like a UX designer: Welcome to week 2,Universal design, inclusive design, and equity-focused design,The importance of equity-focused design,Get to know platforms,Design for different platforms,User-centered design,Assistive technology,Elise - The importance of assistive technology,Akhil - Thinking about users new to technology
Joining design sprints: Welcome to module 3,Introduction to design sprints,Five phases of design sprints,Benefits of design sprints,Plan design sprints,The design sprint brief,An entry-level designer’s role in a sprint,Jason - All about design sprints,Design sprint retrospectives,Wrap up module 3
Integrating research into the design process: Emily - The power of UX research,Introduction to UX research,Christie - How feedback impacts design,Choose the right research method,Understand benefits and drawbacks of research methods,Craig - My journey to UX,Identify types of bias in UX research,Deana - Identify bias in UX research,Wrap-up: Integrating research into the design process,Congratulations on completing Course 1: Foundations of User Experience Design |
Become a CBRS Certified Professional Installer by Google | 1. What is CBRS?
2. The role of CPIs in CBRS
3. More background on CBRS
4. How to do the CPI job
5. Steps to certification
6. The future
7. CPI Exam | What is CBRS?: A quick overview of shared spectrum and terminology
The role of CPIs in CBRS: What are CPIs and why are they needed?
More background on CBRS: Terminology and concepts
How to do the CPI job: Detailed information on how to fulfill your responsibilities
Steps to certification: The path to become CPI certified
The future: Continuing responsibilities for the CPI and TPA
CPI Exam: | What is CBRS?: Introduction,Citizens Broadband Radio Service and shared spectrum,CBRS ecosystem
The role of CPIs in CBRS: The role of CPIs in CBRS
More background on CBRS: SAS-CBSD Communication
How to do the CPI job: When is a CPI required?,Determining Installation Parameters,Determining antenna orientation and characteristics,Getting information from the CPI to the SAS,Google's SAS Portal,The CPI "password",What can go wrong?
Steps to certification: Steps to certification
The future: The future
CPI Exam: Providing Consent and Contact Information,ProctorU Account Setup |
Connect and Protect: Networks and Network Security | 1. Network architecture
2. Network operations
3. Secure against network intrusions
4. Security hardening | Network architecture: You'll be introduced to network security and explain how it relates to ongoing security threats and vulnerabilities. You will learn about network architecture and mechanisms to secure a network.
Network operations: You will explore network protocols and how network communication can introduce vulnerabilities. In addition, you'll learn about common security measures, like firewalls, that help network operations remain safe and reliable.
Secure against network intrusions: You will understand types of network attacks and techniques used to secure compromised network systems and devices. You'll explore the many ways that malicious actors exploit vulnerabilities in network infrastructure and how cybersecurity professionals identify and close potential loopholes.
Security hardening: You will become familiar with network hardening practices that strengthen network systems. You'll learn how security hardening helps defend against malicious actors and intrusion methods. You'll also learn how to use security hardening to address the unique security challenges posed by cloud infrastructures. | Network architecture: Introduction to Course 3,Welcome to module 1,Chris: My path to cybersecurity,What are networks?,Tina: Working in network security,Emmanuel: Useful skills for network security,Network tools,Cloud networks,Introduction to network communication,The TCP/IP model,The four layers of the TCP/IP model,IP addresses and network communication,Wrap-up
Network operations: Welcome to module 2,Network protocols,Antara: Working in network security,Wireless protocols,Firewalls and network security measures,Virtual private networks (VPNs),Security zones,Proxy servers,Wrap-up
Secure against network intrusions: Welcome to module 3,The case for securing networks,Matt: A professional on dealing with attacks,Denial of Service (DoS) attacks,Malicious packet sniffing,IP Spoofing,Wrap-up
Security hardening: Welcome to module 4,Security hardening,OS hardening practices,Network hardening practices,Network security in the cloud,Kelsey: Cloud security explained,Wrap-up,Course wrap-up |
Advanced Learning Algorithms | 1. Neural Networks
2. Neural network training
3. Advice for applying machine learning
4. Decision trees | Neural Networks: This week, you'll learn about neural networks and how to use them for classification tasks. You'll use the TensorFlow framework to build a neural network with just a few lines of code. Then, dive deeper by learning how to code up your own neural network in Python, "from scratch". Optionally, you can learn more about how neural network computations are implemented efficiently using parallel processing (vectorization).
Neural network training: This week, you'll learn how to train your model in TensorFlow, and also learn about other important activation functions (besides the sigmoid function), and where to use each type in a neural network. You'll also learn how to go beyond binary classification to multiclass classification (3 or more categories). Multiclass classification will introduce you to a new activation function and a new loss function. Optionally, you can also learn about the difference between multiclass classification and multi-label classification. You'll learn about the Adam optimizer, and why it's an improvement upon regular gradient descent for neural network training. Finally, you will get a brief introduction to other layer types besides the one you've seen thus far.
Advice for applying machine learning: This week you'll learn best practices for training and evaluating your learning algorithms to improve performance. This will cover a wide range of useful advice about the machine learning lifecycle, tuning your model, and also improving your training data.
Decision trees: This week, you'll learn about a practical and very commonly used learning algorithm the decision tree. You'll also learn about variations of the decision tree, including random forests and boosted trees (XGBoost). | Neural Networks: Welcome!,Neurons and the brain,Demand Prediction,Example: Recognizing Images,Neural network layer,More complex neural networks,Inference: making predictions (forward propagation),Inference in Code,Data in TensorFlow,Building a neural network,Forward prop in a single layer,General implementation of forward propagation,Is there a path to AGI?,How neural networks are implemented efficiently,Matrix multiplication,Matrix multiplication rules,Matrix multiplication code
Neural network training: TensorFlow implementation,Training Details,Alternatives to the sigmoid activation,Choosing activation functions,Why do we need activation functions?,Multiclass,Softmax,Neural Network with Softmax output,Improved implementation of softmax,Classification with multiple outputs (Optional),Advanced Optimization,Additional Layer Types,What is a derivative? (Optional),Computation graph (Optional),Larger neural network example (Optional)
Advice for applying machine learning: Deciding what to try next,Evaluating a model,Model selection and training/cross validation/test sets,Diagnosing bias and variance,Regularization and bias/variance,Establishing a baseline level of performance,Learning curves,Deciding what to try next revisited,Bias/variance and neural networks,Iterative loop of ML development,Error analysis,Adding data,Transfer learning: using data from a different task,Full cycle of a machine learning project,Fairness, bias, and ethics,Error metrics for skewed datasets,Trading off precision and recall
Decision trees: Decision tree model,Learning Process,Measuring purity,Choosing a split: Information Gain,Putting it together,Using one-hot encoding of categorical features,Continuous valued features,Regression Trees (optional),Using multiple decision trees,Sampling with replacement,Random forest algorithm,XGBoost,When to use decision trees,Andrew Ng and Chris Manning on Natural Language Processing |
Prepare Data for Exploration | 1. Data types and structures
2. Data responsibility
3. Database essentials
4. Organize and protect data
5. Engage in the data community | Data types and structures: A massive amount of data is generated every single day. In this part of the course, you will discover how this data is generated and how analysts decide which data to use for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for analysis.
Data responsibility: Before you work with data, you must confirm that it is unbiased and credible. After all, if you start your analysis with unreliable data, you won’t be able to trust your results. In this part of the course, you will learn to identify bias in data and to ensure your data is credible. You’ll also explore open data and the importance of data ethics and data privacy.
Database essentials: When you analyze large datasets, you’ll access much of the data from a database. In this part of the course, you will learn about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also explore metadata to discover its many facets and how analysts use it to better understand their data.
Organize and protect data: Good organizational skills are a big part of most types of work, especially data analytics. In this part of the course, you will learn best practices for organizing data and keeping it secure. You’ll also understand how analysts use file naming conventions to help them keep their work organized.
Engage in the data community: Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you will explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals. | Data types and structures: Introduction to data exploration,Hallie: Fascinating data insights,Data collection in our world,Determine what data to collect,Discover data formats,Continue exploring structured data,Know the type of data you're working with,Data table components,Meet wide and long data
Data responsibility: Introduction to bias, credibility, privacy, and ethics,Bias: From questions to conclusions,Biased and unbiased data,Understand bias in data,Identify good data sources,What is "bad" data?,Essential data ethics,Optional refresher: Alex and the importance of data ethics,Prioritize data privacy,Andrew: The ethical use of data,Features of open data,Andrew: Steps for ethical data use
Database essentials: All about databases,Database features and components,Demystify metadata,Manage data with metadata,Megan: Fun with metadata,So many places to find data,Import data from spreadsheets and databases,Sort and filter to focus on relevant data,Get to know BigQuery, including sandbox and billing options,BigQuery in action
Organize and protect data: Feel confident in your data,Let's get organized,Security features in spreadsheets
Engage in the data community: Manage your presence as a data analyst,Why an online presence is important,Tips for enhancing your online presence,Networking know-how,Benefits of mentorship,Rachel: Mentors are key,Congratulations! Course wrap-up |
Attract and Engage Customers with Digital Marketing | 1. Introduction to attract and engage customers with digital marketing
2. Understand search engine optimization (SEO)
3. Apply search engine optimization (SEO)
4. Search engine marketing (SEM) and display advertising | Introduction to attract and engage customers with digital marketing: You will continue to learn about the marketing funnel and its stages: awareness, consideration, conversion, and loyalty. You’ll also learn strategies for turning potential customers into paying and repeat customers at each stage of the marketing funnel. Finally, you’ll explore how to use customer personas to understand consumers’ goals, pain points, and preferred online platforms.
Understand search engine optimization (SEO): You will review the fundamentals of SEO. Then, you’ll gain a basic understanding of how the Google Search engine works and how websites are ranked. Then, you’ll learn how to do keyword research.
Apply search engine optimization (SEO): You will examine how to optimize a website for search engine optimization, including strategies for content, images, and linking. You’ll also learn how to help search engines better understand your content. Next, you’ll explore how to craft effective website titles and add structured data markups to help users and search engines find what they need. Then, you’ll learn all about how to use SEO tools to analyze search performance and user behavior.
Search engine marketing (SEM) and display advertising: You will learn about advertising opportunities within search engines, also called SEM and Google Display advertising. You’ll learn best practices for creating an ad in search results or a display ad. You’ll finish the course understanding how to apply and improve display ads. | Introduction to attract and engage customers with digital marketing: Introduction to Course 2,Welcome to module 1,Customer personas for your target audience,How to create a customer persona,Introduction to the marketing funnel and its benefits,Awareness: Strategies to get customers introduced to a brand,Consideration: Strategies to build interest in your product or service,Conversion: Strategies to increase the conversion rate on a website,Loyalty: Strategies to increase the loyalty of customers after a purchase,Wrap-up
Understand search engine optimization (SEO): Welcome to module 2,How does the Google search engine work?,How Google determines website rankings,Breakdown of the Google search engine results pages (SERPs),Jake - The purpose and process of search algorithms,What is SEO and why is it important?,First steps before implementing SEO,Keyword research and recommendations,Daniel - Steps and tips a beginner digital marketer should take to optimize a website for SEO,Organize your website’s pages: Website structure and navigation,Wrap-up
Apply search engine optimization (SEO): Welcome to module 3,Optimize a website's content,Optimize images for a website,Craft effective titles and meta descriptions,Create structured data markup,Introduction to Google Search Console,Google Search Console reports and metrics,Dave: My career path into SEO and SEM,Wrap-up
Search engine marketing (SEM) and display advertising: Welcome to week 4,Understand the benefits of SEM,Common SEM ad formats in Google Ads,Ginny - SEM and how to attract customers,How Google Ads works,Identify keywords and understand the ad auction,Best practices when creating a Google Ad in Search,Introduction to display advertising,How to optimize a responsive display ad for your goals,Wrap-up,Course wrap-up |
Neural Networks and Deep Learning | 1. Introduction to Deep Learning
2. Neural Networks Basics
3. Shallow Neural Networks
4. Deep Neural Networks | Introduction to Deep Learning: Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.
Neural Networks Basics: Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.
Shallow Neural Networks: Build a neural network with one hidden layer, using forward propagation and backpropagation.
Deep Neural Networks: Analyze the key computations underlying deep learning, then use them to build and train deep neural networks for computer vision tasks. | Introduction to Deep Learning: Welcome,What is a Neural Network?,Supervised Learning with Neural Networks,Why is Deep Learning taking off?,About this Course,Geoffrey Hinton Interview
Neural Networks Basics: Binary Classification,Logistic Regression,Logistic Regression Cost Function,Gradient Descent,Derivatives,More Derivative Examples,Computation Graph,Derivatives with a Computation Graph,Logistic Regression Gradient Descent,Gradient Descent on m Examples,Vectorization,More Vectorization Examples,Vectorizing Logistic Regression,Vectorizing Logistic Regression's Gradient Output,Broadcasting in Python,A Note on Python/Numpy Vectors,Quick tour of Jupyter/iPython Notebooks,Explanation of Logistic Regression Cost Function (Optional),Pieter Abbeel Interview
Shallow Neural Networks: Neural Networks Overview,Neural Network Representation,Computing a Neural Network's Output,Vectorizing Across Multiple Examples,Explanation for Vectorized Implementation,Activation Functions,Why do you need Non-Linear Activation Functions?,Derivatives of Activation Functions,Gradient Descent for Neural Networks,Backpropagation Intuition (Optional),Random Initialization,Ian Goodfellow Interview
Deep Neural Networks: Deep L-layer Neural Network,Forward Propagation in a Deep Network,Getting your Matrix Dimensions Right,Why Deep Representations?,Building Blocks of Deep Neural Networks,Forward and Backward Propagation,Parameters vs Hyperparameters,What does this have to do with the brain? |
The Bits and Bytes of Computer Networking | 1. Introduction to Networking
2. The Network Layer
3. The Transport and Application Layers
4. Networking Services
5. Connecting to the Internet
6. Troubleshooting and the Future of Networking | Introduction to Networking: Welcome to the Networking course of the IT Support Professional Certificate! In the first module of this course, we will cover the basics of computer networking. We will learn about the TCP/IP and OSI networking models and how the network layers work together. We'll also cover the basics of networking devices such as cables, hubs and switches, routers, servers and clients. We'll also explore the physical layer and data link layer of our networking model in more detail. By the end of this module, you will know how all the different layers of the network model fit together to create a network.
The Network Layer: In the second module of this course, we'll explore the network layer in more depth. We'll learn about the IP addressing scheme and how subnetting works. We'll explore how encapsulation works and how protocols such as ARP allow different layers of the network to communicate. We'll also cover the basics of routing, routing protocols, and how the Internet works. By the end of this module, you'll be able to describe the IP addressing scheme, understand how subnetting works, perform binary math to describe subnets, and understand how the Internet works.
The Transport and Application Layers: In the third module of this course, we'll explore the transport and application layers. By the end of this module, you'll be able to describe TCP ports and sockets, identify the different components of a TCP header, show the difference between connection-oriented and connectionless protocols, and explain how TCP is used to ensure data integrity.
Networking Services: In the fourth module of this course, we'll explore networking services. We'll learn about why we need DNS and how it works. We'll also show you why DHCP makes network administration a simpler task. By the end of this module, you'll be able to do describe how DNS and DHCP work, how NAT technologies help keep networks secure, and how VPNs and proxies help users connect and stay secured.
Connecting to the Internet: In the fifth module of this course, we'll explore the history of the Internet, how it evolved, and how it works today. We'll understand the different ways to connect to the Internet through cables, wireless and cellar connections, and even fiber connections. By the end of this module, you'll be able to define the components of WANs and outline the basics of wireless and cellular networking.
Troubleshooting and the Future of Networking: Congratulations, you've made it to the final module in the course! In the last module of this course, we'll explore the future of computer networking. We'll also cover the practical aspects of troubleshooting a network using popular operating systems. By the end of this module, you'll be able to detect and fix a lot of common network connectivity problems using tools available in Microsoft Windows, MacOS, and Linux operating systems. | Introduction to Networking: Course Introduction,The TCP/IP Five-Layer Network Model,Alex: Why networking is important,Cables,Hubs and Switches,Routers,Servers and Clients,Sergio: Being a network engineer,Moving Bits Across the Wire,Twisted Pair Cabling and Duplexing,Network Ports and Patch Panels,Ethernet and MAC Addresses,Unicast, Multicast, and Broadcast,Dissecting an Ethernet Frame,Victor: Practical experience in IT
The Network Layer: Introduction to The Network Layer,The Network Layer,IPv4 Addresses,IPv4 Datagram and Encapsulation,IPv4 Address Classes,Address Resolution Protocol,Sergio: My career path,Subnetting,Subnet Masks,Basic Binary Math,CIDR,Stay motivated in the program,Basic Routing Concepts,Routing Tables,Interior Gateway Protocols,Exterior Gateways, Autonomous Systems, and the IANA,Non-Routable Address Space,Alex: My success story
The Transport and Application Layers: Introduction to the Transport and Application Layers,The Transport Layer,Dissection of a TCP Segment,TCP Control Flags and the Three-way Handshake,TCP Socket States,Connection-oriented and Connectionless Protocols,Firewalls,The Application Layer,The Application Layer and the OSI Model,All the Layers Working in Unison,Learner Story: Daniel
Networking Services: Introduction to Network Services,Why do we need DNS?,The Many Steps of Name Resolution,DNS and UDP,Sergio: A journey to the IT field,Resource Record Types,Anatomy of a Domain Name,DNS Zones,Overview of DHCP,DHCP in Action,Basics of NAT,NAT and the Transport Layer,Virtual Private Networks,Proxy Services
Connecting to the Internet: Introduction to Connecting to the Internet,Dial-up and Modems,What is broadband?,T-Carrier Technologies,Digital Subscriber Lines,Cable Broadband,Fiber Connections,Wide Area Network Technologies,Point-to-Point VPNs,Introduction to Wireless Networking Technologies,Wireless Network Configurations,Wireless Channels,Wireless Security,Cellular Networking,Mobile Device Networks
Troubleshooting and the Future of Networking: Introduction to Troubleshooting and the Future of Networking,Ping: Internet Control Message Protocol,Traceroute,Testing Port Connectivity,Name Resolution Tools,Public DNS Servers,DNS Registration and Expiration,Hosts Files,What is The Cloud?,Everything as a Service,Cloud Storage,IPv6 Addressing and Subnetting,IPv6 Headers,IPv6 and IPv4 Harmony,Interview Role Play: Networking,Course Wrap Up,Alex: My career path,Congratulations! |
Project Planning: Putting It All Together | 1. Beginning the planning phase
2. Building a project plan
3. Managing budgeting and procurement
4. Managing risks effectively
5. Organizing communication and documentation | Beginning the planning phase: You will learn how the course is structured, the benefits of planning and key components of the planning phase, the difference between tasks and milestones, and how to set milestones.
Building a project plan: You will learn why a project plan is necessary and what components it contains, how to create accurate time estimates and why they are important, and which tools and best practices to use to build a project plan.
Managing budgeting and procurement: You will learn what the components of a project budget are, how the budgeting process works, and how to manage a project budget. You will also explore how the procurement process works, what documentation is necessary, and how to obtain support and avoid ethical conflicts during the process.
Managing risks effectively: You will learn what risk management is and how it can help prevent project failure, what tools can help identify and manage risks, how to identify different types of risks and measure their impact on a project, and how to use a risk management plan to communicate and resolve risks.
Organizing communication and documentation: You will learn the elements of a simple communication plan and how to draft and manage one, why documentation helps create project team visibility and accountability, how to organize documents in one central place, and how to prepare for a job search by documenting experience and highlighting transferable skills. | Beginning the planning phase: Introduction to Course 3,The benefits of project planning,Launching the planning phase,Facilitating a project kick-off meeting,Understanding tasks and milestones,The importance of setting milestones,How to set milestones,Creating a work breakdown structure,Wrap-up,Clennita: How planning creates a sense of team
Building a project plan: Introduction: Building a project plan,Components of a project plan,Making realistic time estimates,Capacity planning and the critical path,Getting accurate time estimates from your team,Angel: The value of interpersonal skills in time estimation,Developing a project schedule,Project plan best practices,Wrap-up
Managing budgeting and procurement: Introduction: Managing budgeting and procurement,The importance of budget setting,Key components of a project budget,Creating a project budget,Maintaining a project budget,Understanding procurement,The procurement process,Common procurement documentation,Creating a Statement of Work,Obtaining procurement support,Ethics in the procurement process,Wrap-up
Managing risks effectively: Introduction: Managing risks effectively,The importance of risk management,Stanton: Managing my first project,Tools to help identify risks,Types of risk,Risk mitigation strategies,Building a risk management plan,Communicating risks to stakeholders,Aji: Risk management at Google,Wrap-up
Organizing communication and documentation: Introduction: Organizing communication and documentation,Why communication is critical,Starting a communication plan,Developing a communication plan,The value of project documentation,Organizing project documentation,Chris: Organizing artifacts for a job interview,Documenting experience in a resume,Dan: The importance of project documentation,Course wrap-up |
Introduction to Statistics | 1. Introduction and Descriptive Statistics for Exploring Data
2. Producing Data and Sampling
3. Probability
4. Normal Approximation and Binomial Distribution
5. Sampling Distributions and the Central Limit Theorem
6. Regression
7. Confidence Intervals
8. Tests of Significance
9. Resampling
10. Analysis of Categorical Data
11. One-Way Analysis of Variance (ANOVA)
12. Multiple Comparisons | Introduction and Descriptive Statistics for Exploring Data: This module provides an overview of the course and a review of the main tools used in descriptive statistics to visualize information.
Producing Data and Sampling: In this module, you will look at the main concepts for sampling and designing experiments. You will learn about curious pitfalls and how to evaluate the effectiveness of such experiments.
Probability: In this module, you will learn about the definition of probability and the essential rules of probability that you will need for solving both simple and complex challenges. You will also learn about examples of how simple rules of probability are used to create solutions for real-life complex situations.
Normal Approximation and Binomial Distribution: This module covers the empirical rule and normal approximation for data, a technique that is used in many statistical procedures. You will also learn about the binomial distribution and the basics of random variables.
Sampling Distributions and the Central Limit Theorem: In this module, you will learn about the Law of Large Numbers and the Central Limit Theorem. You will also learn how to differentiate between the different types of histograms present in statistical analysis.
Regression: This module covers regression, arguably the most important statistical technique based on its versatility to solve different types of statistical problems. You will learn about inference, regression, and how to do regression diagnostics.
Confidence Intervals: In this module, you will learn how to construct and interpret confidence intervals in standard situations.
Tests of Significance: In this module, you will look at the logic behind testing and learn how to perform the appropriate statistical tests for different samples and situations. You will also learn about common misunderstandings and pitfalls in testing.
Resampling: This module focuses on the two main methods used in computer-intensive statistical inference: The Monte Carlo method, and the Bootstrap method. You will learn about the theoretic principles behind these methods and how they are applied in different contexts, such as regression and constructing confidence intervals.
Analysis of Categorical Data: This module focuses on the three important statistical analysis for categorical data: Chi-Square Goodness of Fit test, Chi-Square test of Homogeneity, and Chi-Square test of Independence.
One-Way Analysis of Variance (ANOVA): This module covers the basics of ANOVA and how F-tests work on one-way ANOVA examples.
Multiple Comparisons: In this module, you will learn about very important issues that have surfaced in the era of big data: data snooping and the multiple testing fallacy. You will also explore the reasons behind challenges in data reproducibility and applicability, and how to prevent such issues in your own work. | Introduction and Descriptive Statistics for Exploring Data: Course Welcome,Meet Guenther Walther,Introduction,Pie Chart, Bar Graph, and Histograms,Box-and-Whisker Plot and Scatter Plot,Providing Context is Key for Statistical Analyses,Pitfalls when Visualizing Information,Mean and Median,Percentiles, the Five Number Summary, and Standard Deviation,[EXTRA] Industry Insight: Introduction to Andrew Radin
Producing Data and Sampling: Introduction,Simple Random Sampling and Stratified Random Sampling,Bias and Chance Error,Observation vs. Experiment, Confounding, and the Placebo Effect,The Logic of Randomized Controlled Experiments,[EXTRA] Industry Insights: Filing a Patent for twoXAR
Probability: The Interpretation of Probability,Complement, Equally Likely Outcomes, Addition, and Multiplication,Four Rules Example: How to Deal with "At Least One",Solving Problems by Total Enumeration,Bayes' Rule,Bayesian Analysis,Warner's Randomized Response Model,[EXTRA] Industry Insights: Drug Discovery at twoXAR
Normal Approximation and Binomial Distribution: The Normal Curve,The Empirical Rule,Standardizing Data and the Standard Normal Curve,Normal Approximation,Computing Percentiles with the Normal Approximation,The Binomial Setting and Binomial Coefficient,The Binomial Formula,Random Variables and Probability Histograms,Normal Approximation to the Binomial; Sampling Without Replacement,[EXTRA] Industry Insights: Opportunities in Life Sciences
Sampling Distributions and the Central Limit Theorem: Parameter and Statistic,Expected Value and Standard Error,EV and SE of Sum, Percentages, and When Simulating,The Square Root Law,The Sampling Distribution,Three Histograms,The Law of Large Numbers,The Central Limit Theorem,When does the Central Limit Theorem Apply?
Regression: Prediction is a Key Task of Statistics,The Correlation Coefficient,Correlation Measures Linear Association,Regression Line and the Method of Least Squares,Regression to the Mean, The Regression Fallacy,Predicting y from x and x from y,Normal Approximation Given x,Residual Plots, Heteroscedasticity, and Transformations,Outliers and Influential Points,[EXTRA] Industry Insights: Challenges to Using Data Science in Medicine
Confidence Intervals: Interpretation of a Confidence Interval,Using the Central Limit Theorem to Find a Confidence Interval,Estimating the Standard Error with the Bootstrap Principle,More About Confidence Intervals
Tests of Significance: The Idea Behind Testing Hypotheses,Setting Up a Test Statistic,p-values as Measures of Evidence,Distinguishing Coke and Pepsi by Taste,The t-test,Statistical Significance vs. Importance,The Two-Sample z-test,Matched Pairs,[EXTRA] Industry Insights: Hiring Data Science Talent
Resampling: Using Computer Simulations in Place of Calculations,Using the Law of Large Numbers to Approximate Quantities of Interest,Plug-in Principle,The Parametric Bootstrap and Bootstrap Confidence Intervals,Bootstrapping in Regression
Analysis of Categorical Data: Relationships Between Two Categorical Variables,The Color Proportions of M&Ms,The Chi-Square Test for Homogeneity and Independence
One-Way Analysis of Variance (ANOVA): Comparing Several Means,The Idea of Analysis of Variance,Using the F Distribution to Evaluate ANOVA,More on ANOVA,[EXTRA] Industry Insights: Starting Your Career in Data Science
Multiple Comparisons: Data Snooping and the Multiple Testing Fallacy, Reproducibility and Replicability,Bonferroni Correction, False Discovery Rate, and Data Splitting,Summary |
Introduction to Psychology | 1. Welcome to Introduction to Psychology
2. Foundations
3. Development and Language
4. Cognition
5. Self and others
6. Variation
7. The good life | Welcome to Introduction to Psychology: Meet Paul Bloom, your instructor.
Foundations: In this module, you will learn about foundational psychological theories and findings in psychology. We will start with the discovery that our mental lives have a physical basis, introducing the field of neuroscience. And then we will turn to two major psychological theories that have come to shape the world that we now live in—Freud’s psychodynamic theory and Skinner’s theory of behaviorism.
Development and Language: In this module, you will learn about foundational psychological research into development and language. Specifically, you will learn about methods for studying how infants and children think and the core discoveries that they have led to. Then you will learn about the structure of language, how language is learned, and end with a little bit on animal communication, language processing, and relationship between language and thought.
Cognition: In this module, you will learn about cognitive psychology. Specifically, you will learn about how we perceive the world, how attention works, and we store our experiences in memory.
Self and others: In this module, you will learn about psychology examining the self and others. Specifically, in the first half, you will learn about social and non-social emotions. In the second half, you will learn about how we deal with other people—social psychology.
Variation: In this module, you will learn human variation. The focus will focus on personality and intelligence, and the role of genes and environment in explaining individual differences. The second half will focus on clinical psychology by reviewing prominent mental illnesses and therapies.
The good life: In the final module, you will learn how psychologists measure happiness and what factors contribute to the good life | Welcome to Introduction to Psychology: How to take this course
Foundations: The astonishing hypothesis,Dualism,Neurons,Parts of the brain,Our two brains,A bit of humility,Sigmund Freud,The psychodynamic approach,Stages of development,Defense mechanisms,Scientific assessment of Freud,Taking Freud seriously,B.F. Skinner,Habituation,Classical conditioning,Instrumental conditioning,Scientific assessment of Skinner
Development and Language: Big questions about development,Piaget,Piaget's Developmental Stage Theory,Scientific evaluation of Piaget,Methods for studying infants,How are children different from adults?,Explanations for development,What is language?,Basic facts about language,Phonology,Morphology,Syntax,Language acquisition,Language and thought
Cognition: From the world to the mind,Problems of perception,Perception of brightness,Perception of objects,Perception of depth,Attention,Important memory distinctions,Memory storage,Learning,Remembering,Failures of memory,False memories
Self and others: Evolution of emotion,Why evolution matters,Facial expressions,Fear,Kinship,Attachment,Prisoner's dilemma,Irrationality and culture,Social animals,Self,Attribution,Liking,The psychology of groups,Social categories,Social categories II
Variation: How are we different?,Personality,Intelligence,Behavioral genetics,Major discoveries about genes and environment,Parenting,Mental illness,Schizophrenia,Mood disorders,Anxiety disorders,Dissassociation disorders,Personality disorders,Therapy
The good life: Positive psychology,What is happiness?,Happiness set point,Happiness is relative,Judgments about past events are skewed,Humility and Optimism,Now what? |
Personal Branding: Stand Out and Succeed | 1. Week 1: Introduction to Brands
2. Week 2: People as Brands
3. Week 3: You as a Brand
4. Week 4: Reinventing & Retuning | Week 1: Introduction to Brands: Your instructors, Cheri Alexander and Marcus Collins, introduce themselves and share with you an overview of the course. During this introductory week, you will be exposed to essential concepts related to branding. These include understanding the definition and historical context of brand, exploring brand effects, and gaining insights into the frameworks that can be employed for brand analysis. To fully comprehend personal branding, the instructors will initially build your knowledge around product branding to give you a baseline understanding of key branding concepts.
Week 2: People as Brands: In Week 2, Cheri and Marcus delve into how we can relate product brands to personal brands. To better understand how great brands have clear values and authenticity, you will explore a series of mini case studies of people who have left an impact on the world. You will then practice analyzing personal brands with the RED Framework, which you learned about at the end of Week 1 of the course. By going through the process of brand analysis, you will start identifying key traits that constitute a strong and authentic brand.
Week 3: You as a Brand: In Week 3, you will be guided through two reflection activities (a Core Values Sort and a Reflected Best Self analysis). In the Core Values Sort, you will discover which of your values are most important to you and incorporate those values into your own personal brand. In the Reflected Best Self analysis, you will reach out to those close to you and gain insights into how they perceive you when you are at your best. By hearing the perspectives of others, you will pinpoint characteristics that you have that are foundational to your authentic brand. Note that this module may take longer than a week to complete.
Week 4: Reinventing & Retuning: In Week 4, we will bring all of the concepts that you have learned throughout the course in two final activities: designing your brand logo and creating your brand story. Now that you have an understanding of your core values and characteristics from Week 3, you will be able to design a visual representation of your personal brand and craft a brand story about what makes you stand out from a crowd. | Week 1: Introduction to Brands: Welcome to the Course,Introduction to Week 1,Activity: Personal Goals,What is a Brand?,History of Brand,What are Brand Effects?,Activity: Breaking Down Your Favorite Brand,Debrief: Breaking Down Your Favorite Brand,Which Brand is Better?,Our Brand Pyramid Framework,Brand Ideology,Debrief: Using the Brand Pyramid,The RED Framework,Activity: Analyzing Your Favorite Brand,Debrief: Analyzing Your Favorite Brand,Week 1 Coffee Chat
Week 2: People as Brands: Introduction to Week 2,Activity: Role Model Reflection,People as Brands,Activity: Perceiving Others,Debrief: Perceiving Others,The Facets of a Personal Brand,Introduction to the Case Studies,Case Study: Beyonce,Case Study: Ghandi,Case Study: Steve Jobs,Case Study: Martin Luther King, Jr.,Case Study: Lionel Messi,Case Study: JFK,Case Study: Malala,Activity: Analyze Your Role Model with the RED Framework,Debrief: Analyze Your Role Model Using the RED Framework,Real Life Example of a Strong Brand: Zingerman's,Activity: Analyzing the Zingerman's Brand,Week 2 Coffee Chat
Week 3: You as a Brand: Introduction to Week 3,Values as the Foundation of Your Brand,Activity: Sanger Value Sort,Reflected Best Self,Activity: Examples of Your Best Self,Cheri's Best Self,Knowing Yourself,What is a Story?,Activity: What Makes You Distinctive?,Week 3 Coffee Chat
Week 4: Reinventing & Retuning: Introduction to Week 4,Cheri's Personal Brand Drawing,Marcus' Personal Brand Collage,Activity: Designing Your Brand Logo,Marcus' Personal Brand,Activity: Creating Your Brand Story,Living Your Brand,Week 4 Coffee Chat |
Workday Basics Series | 1. Workday Basics
2. Beyond Basics | Workday Basics: Workday Basics is your entry point to a rewarding career using Workday technology. In this course, you will learn why companies choose Workday. You will also gain an understanding of the foundational frameworks that allow Workday to uniquely support organizations and their goals.
Beyond Basics: Welcome to Workday Beyond Basics! Workday Basics served as your entry point to Workday. Beyond Basics is the next step in your journey. In this course, you will dive deeper into the Workday framework, review additional Workday products and features, and explore real world business cases that showcase Workday in action. | Workday Basics: Workday Basics,Workday Navigation Intro,Business Object Model Demo,Home Page and Search Demo,Performing Tasks Demo,Workday Foundation,Organizations & Worktags Intro,Supervisory Organization,Company,Cost Center,Pay Group,Location,Academic Unit,Worktags,Workday Basics Configurable Security,Business Process Framework,Reporting Options,Workday in Action,Create a Supervisory Org,Move Workers,Create Positions,Hire Employees,Workday Financial Management,Create a Cost Center,Assign Cost Center to Supervisory Organization,Edit Expense Report Business Process Definition,Submit an Expense Report,Workday Time Tracking,Review Time Entry Options,Enter Time for a Worker,Approve Time for a Worker,Workday Payroll,Run a Pay Calculation,View Payroll Results,View Payslip as a Worker,Workday Reporting & Analytics,Reports and Dashboards,Custom Reports
Beyond Basics: Reunite with Workday,Reunite with Workday University,Tenant Branding,Additional Workday Products,Workday Integration Systems,Workday Extend Technology,Workday Adaptive Planning Navigation,Workday Peakon Personal Dashboard,Organization Types,Create a Company,Create a Location,Add the Location to a Location Hierarchy,Additional Security Features,Create a Location Membership Security Group,Create an Organization Membership Security Group,Create a Job-Based Security Group,Business Process Features,Advanced Routing Restriction,Configure a Delegation,Additional Reporting Features,Share a Custom Report Definition,Schedule a Report,Export a Custom Report,Wrap Up |
Tools of the Trade: Linux and SQL | 1. Introduction to operating systems
2. The Linux operating system
3. Linux commands in the Bash shell
4. Databases and SQL | Introduction to operating systems: You will learn about the relationship between operating systems, hardware, and software, and become familiar with the primary functions of an operating system. You'll recognize common operating systems in use today and understand how the graphical user interface (GUI) and command-line interface (CLI) both allow users to interact with the operating system.
The Linux operating system: You will be introduced to the Linux operating system and learn how it is commonly used in cybersecurity. You’ll also learn about Linux architecture and common Linux distributions. In addition, you'll be introduced to the Linux shell and learn how it allows you to communicate with the operating system.
Linux commands in the Bash shell: You will be introduced to Linux commands as entered through the Bash shell. You'll use the Bash shell to navigate and manage the file system and to authorize and authenticate users. You'll also learn where to go for help when working with new Linux commands.
Databases and SQL: You will practice using SQL to communicate with databases. You'll learn how to query a database and filter the results. You’ll also learn how SQL can join multiple tables together in a query. | Introduction to operating systems: Introduction to Course 4,Welcome to module 1,Kim: My journey into computing,Introduction to operating systems,Inside the operating system,Resource allocation via the OS,GUI versus CLI,Ellen: My path into cybersecurity,Wrap-up
The Linux operating system: Welcome to module 2,Introduction to Linux,Phil: Learn and grow in the cybersecurity field,Linux architecture,Linux distributions,KALI LINUX ™,Introduction to the shell,Input and output in the shell,Wrap-up
Linux commands in the Bash shell: Welcome to module 3,Linux commands via the Bash shell,Core commands for navigation and reading files,Find what you need with Linux,Create and modify directories and files,File permissions and ownership,Change permissions,Add and delete users,Damar: My journey into Linux commands,The Linux community,Man pages within the shell,Wrap-up
Databases and SQL: Welcome to module 4,Introduction to databases,Query databases with SQL,Adedayo: SQL in cybersecurity,Basic queries,Basic filters on SQL queries,Filter dates and numbers,Filters with AND, OR, and NOT,Join tables in SQL,Types of joins,Wrap-up,Course wrap-up |
Agile Project Management | 1. The fundamentals of Agile
2. Scrum 101
3. Implementing Scrum
4. Applying Agile in the organization | The fundamentals of Agile: You will learn how the course is structured and explore the history, approach, and philosophy of Agile project management and Scrum theory. You will also learn why Agile is best suited to industries that are susceptible to change and how to differentiate and blend Agile approaches.
Scrum 101: You will learn the pillars of Scrum and how they support Scrum values. You will also compare essential Scrum Team roles and examine what makes them effective.
Implementing Scrum: You will learn how to build and manage a Product Backlog and develop user stories and epics. You will also explore how to set up the five important Scrum events and use tools to plan and visualize sprint workflows and progress.
Applying Agile in the organization: You will learn to implement Agile’s value-driven delivery strategies and how to define a value roadmap. You will learn strategies to effectively introduce an Agile or Scrum approach to an organization and coach an Agile team. You will also investigate how Agile frameworks have evolved and how to land opportunities in Agile roles. | The fundamentals of Agile: Introduction to Course 5,A brief history of Agile,Distinguishing Agile from Waterfall,The four values of the Agile Manifesto,The 12 principles of the Agile Manifesto,Adopting an Agile mindset,Applying Agile in a VUCA environment,Introduction to Scrum,Introduction to Kanban, XP, and Lean,Blending project management approaches,Wrap-up
Scrum 101: Introduction: Scrum 101,The three pillars of Scrum,The five values of Scrum,Essential Scrum roles,Traits of an effective Scrum Master,Pete: What makes an effective Scrum Master,Traits of an effective Product Owner,Traits of an effective Development Team,Wrap-up
Implementing Scrum: Introduction: Implementing Scrum,Building a Product Backlog,Writing user stories,Backlog refinement and effort estimation,Introduction to the Sprint,Sprint planning,The Daily Scrum and Sprint Review,Sarah: The benefits of a Daily Standup,The Sprint Retrospective,Velocity and burndown charts,Utilizing Kanban boards,Tools for transparency and collaboration,Wrap-up
Applying Agile in the organization: Introduction: Applying Agile in the organization,Maximizing value-driven delivery,Camron: How Agile can drive value,Components of a value roadmap,Creating an effective value roadmap,Facilitating organizational change,Coaching an Agile team,Agile team challenges,Common Agile coaching challenges,The evolution of Agile,Jez: My thoughts on Agile,Agile project management opportunities,Course wrap-up,Creating a job search plan |
Process Data from Dirty to Clean | 1. The importance of integrity
2. Clean data for more accurate insights
3. Data cleaning with SQL
4. Verify and report on cleaning results
5. Optional: Add data to your resume
6. Course wrap-up | The importance of integrity: Data integrity is critical to successful analysis. In this part of the course, you’ll explore methods and steps that analysts take to check their data for integrity. This includes knowing what to do when you don’t have enough data. You’ll also learn about random samples and understand how to avoid sampling bias. All of these methods will also help you ensure your analysis is successful.
Clean data for more accurate insights: Every data analyst wants to analyze clean data. In this part of the course, you’ll learn the difference between clean and dirty data. Then, you’ll practice cleaning data in spreadsheets and other tools.
Data cleaning with SQL: Knowing a variety of ways to clean data can make a data analyst’s job much easier. In this part of the course, you’ll use SQL to clean data from databases. In particular, you’ll explore how SQL queries and functions can be used to clean and transform your data before an analysis.
Verify and report on cleaning results: When you clean data, you make changes to the original dataset. It’s important to verify the changes you make are accurate and to let your teammates know about the changes. In this part of the course, you’ll learn to verify that data is clean and report your data cleaning results. With verified clean data, you’re ready to begin analyzing!
Optional: Add data to your resume: Creating an effective resume will help you in your data analytics career. In this part of the course, you’ll learn all about the job application process. Your focus will be on building a resume that highlights your strengths and relevant experience.
Course wrap-up: Review the course glossary and prepare for the next course in the Google Data Analytics Certificate program. | The importance of integrity: Introduction to data integrity,Why data integrity is important,Balance objectives with data integrity,Deal with insufficient data,The importance of sample size,Using statistical power,Determine the best sample size,Evaluate data reliability
Clean data for more accurate insights: Clean it up!,Why data cleaning is critical,Angie: I love cleaning data,Recognize and remedy dirty data,Data-cleaning tools and techniques,Clean data from multiple sources,Data-cleaning features in spreadsheets,Optimize the data-cleaning process,Different data perspectives,Even more data-cleaning techniques
Data cleaning with SQL: Use SQL to clean data,Sally: For the love of SQL,Understand SQL capabilities,Spreadsheets versus SQL,Widely used SQL queries,Evan: Having fun with SQL,Clean string variables using SQL,Advanced data-cleaning functions, part 1,Advanced data-cleaning functions, part 2
Verify and report on cleaning results: Verify and report results,Confirm data-cleaning meets business expectations,Verification of data cleaning,Capture cleaning changes,Why documentation is important,Feedback and cleaning
Optional: Add data to your resume: About the data-analyst hiring process,The data analyst job-application,Build a resume,Make your resume unique,Joseph: Black and African American inclusion in the data industry,Translate past work experience,Kate: My career path as a data analyst,Where does your interest lie?
Course wrap-up: Congratulations! Course wrap-up |
Business Analytics with Excel: Elementary to Advanced | 1. Introduction to Excel: Basics and Best Practices
2. What-If Analysis in Excel
3. Decision Analysis through Regression and NPV
4. Linear Programming
5. Transportation and Assignment Problems
6. Integer Programming and Nonlinear Programming | Introduction to Excel: Basics and Best Practices: The purpose of this course is to expose you to a variety of problems that can be solved using management science methods and modelled in Excel. In this course, we start from the basics of spreadsheet design and work our way up to broader mathematical optimization modelling. Many airlines, banks, and technology companies could not operate today as they do without the skills and techniques taught in this course. In this first module, we begin by introducing a relatively simple example of a mathematical model which we will use as our platform to build off of for more complicated applications later in the course.
Many problems used in the video lectures come from the text Business Analytics: Data Analysis & Decision Making by Albright & Winston (Cengage Learning, 2014), ISBN 1285965523
What-If Analysis in Excel: We are now ready to introduce more complexity to our spreadsheet models. Since everyone comes from different Excel backgrounds, we will review some basic functions and features as well as more advanced techniques. This module covers more of the modelling process and includes some of the less-well known, but particularly helpful, Excel functions and tools that are available. Remember though that this course's objective is not to be a "how-to" of Excel. Instead, the focus and intent is to use these features to provide insights into real business problems.
Decision Analysis through Regression and NPV: In this module the modeling concept of estimating relationships between variables by curve fitting, or regression analysis, is used to solve realistic business problems. Different regression curves are introduced and a mathematical analysis of which curve is best to help defend the model is presented. This allows not only an understanding of the techniques of modelling but also the rational behind which model to use.
Linear Programming: In this module we introduce spreadsheet optimization, one of the most powerful and flexible methods of quantitative analysis. The specific type of optimization presented here is linear programming (LP) which is used in all types of organizations to solve a wide variety of problems. As you will see through the examples presented in this course, LP is used in problems of labor scheduling, inventory management, advertising, finance, transportation, staffing, and many others. The goal of this module is to introduce you to the basic elements of LP, the types of problems it can solve, and how to model an LP problem in excel.
Transportation and Assignment Problems: This module provides even more examples of problems that can be modeling using linear programming (LP), in particular Transportation and Assignment problems. The basic transportation problem is concerned with finding the best (usually the least cost) way to distribute the good from sources such as factories, to final destinations such as retail outlets. The assignment problem involves finding the best (usually the least cost) way to assign individuals or pieces of equipment to projects or jobs on a one-to-one basis. Using Solver, we will take advantage of the special structure of these LP problems to find the best solutions to complex business problems in an efficient way.
Integer Programming and Nonlinear Programming: This module presents yet another subset of important mathematical linear programming models that arise when some of the basic assumptions of an LP model are made more or less restrictive. For example, restricting the decision variables to be whole numbers leads to the process of Integer Programming. Restricting the decision variables to be either 0 or 1 leads to binary programming. Lastly, we will see how the skills in this course can be used to solve more complex problems that involve nonlinear models. | Introduction to Excel: Basics and Best Practices: Warm-Up - Creating a Budget in Excel,NCAA T-Shirt Vendor,Woodworks Bookshelf Co.
What-If Analysis in Excel: Quality Sweater Company,B&N Bookstore
Decision Analysis through Regression and NPV: The 19th Hole,NPV Example: Gopher Drugs
Linear Programming: Campaign Marketing,PC Tech Company,Investment Allocation,Busing Problem
Transportation and Assignment Problems: Transportation Problem Excel Template,Alternative Excel Template,New Hire Assignments,MLB Umpire Assignment
Integer Programming and Nonlinear Programming: Princess Brides,Bolsa de Café,Binary Investment Decision,Portfolio Variance,Motorcross Snowmobiles |
Start the UX Design Process: Empathize, Define, and Ideate | 1. Empathizing with users and defining pain points
2. Creating user stories and user journey maps
3. Defining user problems
4. Ideating design solutions | Empathizing with users and defining pain points: Get ready to begin the design process for a new portfolio project: a mobile app! This part of the course will focus on empathizing with users, which is the first phase of the design process. You’ll think through the needs of your potential users to build empathy maps and create personas. These hands-on activities will help you understand user perspectives and pain points.
Creating user stories and user journey maps: In this part of the course, you'll continue to empathize with users of the mobile app you'll later design. You'll craft user stories and develop user journey maps. You’ll also learn about the importance of considering accessibility when empathizing with users.
Defining user problems: All of your work to empathize with users will help you define the problem that users are facing. In this part of the course, you'll move from the empathize phase into the define phase of the design process. To define the problem your designs will solve, you’ll build a problem statement, a hypothesis statement, and a value proposition. In addition, you’ll explore how psychology and human factors influence design.
Ideating design solutions: You're ready to move into the third phase of the design process: ideate. You'll consider everything you've learned about the users you're designing for and the problems they're facing in order to brainstorm ideas for design solutions. To help you come up with lots of ideas for design solutions, you’ll conduct a competitive audit and complete design activities, like How Might We and Crazy Eights. | Empathizing with users and defining pain points: Introduction to Course 2: Empathize, Define, and Ideate,Lisa - Create a UX design portfolio,Introduction to UX design portfolios,Introduction to website builders,Introduction to best practices for UX design portfolios,Empathize with users,Recruit interview participants,Prepare for user interviews,Interviewing users,Empathy Maps,Identify user pain points,Understand personas,Wrap-up: Empathizing with users and defining pain points
Creating user stories and user journey maps: Welcome to module 2,Craft user stories,Consider edge cases,Ayan - Real world example of edge cases,Create a user journey map,Consider accessibility when empathizing,Understand the curb cut effect,Wrap-up: Creating user stories and user journey maps
Defining user problems: Welcome to module 3,Create problem statements,Define hypothesis statements,Determine a value proposition,Understand human factors,Explore psychology principles that influence design,Wrap-up: Defining user problems
Ideating design solutions: Welcome to module 4,Understand design ideation,Explore lots of ideas,Recognize business needs during design ideation,Use research to inform ideation,Craig - Research informs ideation in the real world,Create goal statements,Scope the competition,Limits to competitive audits,Steps to conduct a competitive audit,Use insights from competitive audits to ideate,Vanessa - My journey to UX,Use How Might We to ideate,Use Rapid Sketching to ideate,Consider user journeys during ideation,Congratulations on completing Course 2: Empathize, Define, and Ideate |
Project Execution: Running the Project | 1. Introduction to project execution
2. Quality management and continuous improvement
3. Data-informed decision-making
4. Leadership and influencing skills
5. Effective project communication
6. Closing a project | Introduction to project execution: You will learn how the course is structured, what aspects of a project to track, and how to track them. You will also learn how to effectively manage changes, dependencies, and risks and how to communicate critical risks to stakeholders.
Quality management and continuous improvement: You will learn how to manage quality using various techniques. You will learn how to effectively communicate with customers and different ways to measure customer satisfaction. You will also explore continuous improvement and process improvement techniques and how to conduct a retrospective during the project to improve processes.
Data-informed decision-making: You will learn the value of gathering data, how to prioritize data to meet project needs, and how to use data to inform your decision-making. You will also learn how to explain your project data to stakeholders and team members using effective visuals and presentation techniques.
Leadership and influencing skills: You will learn the factors that influence team effectiveness, the stages of team development, and how to manage team dynamics. You will discover how to create an ethical and inclusive environment in which high-functioning teams work together to achieve project goals. You will also explore how to use different techniques and sources of power to influence others.
Effective project communication: You will learn what tools provide effective project team communication, how to organize and facilitate meetings to ensure project success, and how to effectively communicate project status updates to project stakeholders and team members.
Closing a project: You will learn how to determine when a project is finished and why closing a project is important. You will examine the steps of the closing process and how to create and share project closing documentation. | Introduction to project execution: Introduction to Course 4,The importance of tracking,Common items to track,Different tracking methods,Belinda: tracking and managing a budget,Pranjal: Managing multiple tracks,Why risks and changes occur,Identifying and tracking dependencies,Techniques to help manage risks,Escalating issues,Communicating changes to the team,Wrap-up
Quality management and continuous improvement: Introduction: Quality management and continuous improvement,Key quality management concepts,Fostering customer relationships with communication skills,Measuring customer satisfaction,Ensuring accessibility during feedback collection,Sue: The importance of understanding customer needs,Continuous improvement and process improvement,Data-driven improvement frameworks,Differentiating projects from programs,Jacob: Cultivating a continuous improvement mindset,The purpose of a retrospective,Conducting a retrospective,Gernot: Using retrospectives to get back on track,Wrap-up
Data-informed decision-making: Introduction: Data-informed decision-making,The value of data,Common types of project data,Discerning important data,Using data analysis to inform decisions,Presenting data to tell a project's story,Data visualization tools,Effective presentation techniques,Making presentations accessible,Wrap-up
Leadership and influencing skills: Introduction: Leadership and influencing skills,The necessity of project teamwork,The factors that impact team effectiveness,Leading high-functioning teams,Emilio: Learning to lead,Team development and managing team dynamics,Rowena: Delegating the details,Ethical and inclusive leadership,Steps to effective influencing,Using sources of power to influence,Chris: Influencing others by demonstrating project impact,Wrap-up
Effective project communication: Introduction: Effective project communication,Communicating in different ways,Common communication tools,How to organize effective meetings,Common types of project meetings,Wrap-up
Closing a project: Introduction: Closing a project,The importance of project closure,The closing process for clients and stakeholders,The closing process for the team,Sarah: Why I love retrospectives,The closing process for the project manager,Course wrap-up |
Writing in the Sciences | 1. 1
2. 2
3. 3
4. 4
5. 5
6. 6
7. 7
8. 8 | 1: Unit 1 introduces the course and reviews key principles of effective writing. In particular, you will practice cutting clutter from writing.
2: Unit 2 focuses on writing with strong, active verbs. Lessons include how to: write in the active voice; avoid turning verbs into nouns; choose strong verbs; and get to the main verb of a sentence quickly.
3: Unit 3 reviews how to vary sentence structure and write strong paragraphs. You will practice using the dash, colon, semi-colon, and parentheses, as well as writing well-organized and concise paragraphs.
4: Unit 4 reviews the writing process. I will give you tips for making the writing process easier, more efficient, and more organized.
5: Unit 5 reviews the sections of a scientific manuscript. You will learn how to format tables and figures, and how to write results, methods, introduction, and discussion sections.
6: Unit 6 discusses the peer review process, as well as ethical issues in scientific publishing. You will learn how to avoid plagiarism, determine authorship, submit a paper, write a peer review, and avoid predatory journals.
7: Unit 7 reviews types of writing beyond original research manuscripts. You will learn how to write review papers, grants, letters of recommendation, and personal essays.
8: Unit 8 reviews communication with broader audiences. You will learn how work with the media, be interviewed, conduct an interview, and write about science for general audiences. | 1: 1.1: Introduction; principles of effective writing,1.2: Examples of what not to do,1.3: Overview, principles of effective writing,1.4: Cut the clutter,1.5: Cut the clutter, more tricks,1.6: Practicing cutting clutter,Demo Edit 1 (Optional)
2: 2.1: Use the active voice,2.2: Is it really OK to use "We" and "I",2.3: Active voice practice,2.4: Write with verbs,2.5: Practice examples,2.6: A few grammar tips,Demo Edit 2 (Optional)
3: 3.1: Experiment with punctuation,3.2: Practice, colon and dash,3.3: Parallelism,3.4: Paragraphs,3.5: Paragraph Editing I,3.6: Paragraph Editing II,Module 3.7: A few more tips,Demo Edit 3 (Optional)
4: 4.1 More paragraph practice,4.2 Overview of the writing process,4.3 The pre-writing step,4.4 The writing step,4.5: Revision,4.6: Checklist for the final draft,Demo Edit 4 (Optional)
5: 5.1: Tables and Figures,5.2: Results,5.3: Practice writing results,5.4: Methods,5.5: Introduction,5.6: Introduction practice,5.7: Discussion,5.8: Abstract,Demo Edit 5 (Optional)
6: 6.1: Plagiarism,6.2: Authorship,6.3: The Submission Process,6.4: Interview with Dr. Bradley Efron,6.5: Interview with Dr. George Lundberg,6.6: Interview with Dr. Gary Friedman,6.7: Doing a peer review,6.8: Predatory journals,Demo Edit 6 (Optional)
7: 7.1: Writing a review article,7.2: Grants I,7.3: Grants II,7.4: Grants III,7.5 Writing letters of recommendation,7.6: Writing personal statements,Demo Edit 7 (Optional)
8: 8.1: Talking with the media,8.2: Panel Interview,8.3: Writing for general audiences,8.4: Writing a science news story,8.5: Interviewing a scientist,8.6: Social media,8.7: Concluding Remarks,Demo Edit 8 (Optional) |
Bookkeeping Basics | 1. Accounting Concepts and Measurement
2. The Accounting Cycle (Part 1)
3. The Accounting Cycle (Part 2)
4. Accounting Principles and Practices | Accounting Concepts and Measurement: In this module, you'll be introduced to the role of a bookkeeper and gain an understanding of how to use the accounting equation and double-entry accounting.
The Accounting Cycle (Part 1): In this module, you will learn about the accounting cycle and how bookkeepers use the general journal and general ledger to record and keep track of business transactions.
The Accounting Cycle (Part 2): In this module, you will learn how bookkeepers using accounting software to record transactions. You will also further your understanding of the accounting cycle by learning how to create trail balances and produce financial statemnets.
Accounting Principles and Practices: In this final module for Course 1, you will gain an understanding of key accounting assumptions and principles and learn about the different types of accounting methods bookkeepers use. | Accounting Concepts and Measurement: Welcome to Intuit's Bookkeeping Certification Program,Welcome to Course 1: Bookkeeping Basics,Meet Your Learning Guide,Introduction to Accounting,Our Schedule,Introduction to the Bookkeeper Role and Learning Objectives,How Does a Bookkeeper Contribute to Clients' success?,Commercial Break: Career Readiness Resource,Commercial Break: Expert Advice,Lesson Summary and Wrap-Up,Introduction and Learning Objectives,The Accounting Principle,Accounting Equation Summary,Next on Bookkeeper Rescue,Double Entry Accounting Introduction and Overview,Double Entry Accounting,Account Types,Recapping Journal Entries,A Pro's Perspective on Debits and Credits
The Accounting Cycle (Part 1): Introduction to Working with the General Journal and General Ledger (Part 1),Chart of Accounts,General Ledger Summary,Introduction to Working with the General Journal and General Ledger (Part 2),Overview of Accounting Software,Transaction Examples,Creating a Journal,Running Reports,Introducing the Accounting Cycle,Step 1 - Collect and Analyze Transactions,Step 2 - Posting Transactions to the General Ledger,Step 3 - Preparing an Unadjusted Trial Balance,Step 4 - Preparing Adjusting Entries at the End of a Period,Step 5: Preparing an Adjusted Trial Balance
The Accounting Cycle (Part 2): Introduction Learning Objectives,Sales Receipts,Sales Receipt vs Invoice,Lou Received a Check - Entering a Bank Deposit,Lou Writes a Check - Paying a Check to a Vendor,Lou Gives a Credit,Processing Transactions with QuickBooks Online Summary,Intro and Objectives,Expert Advice: Adjusting Entries,Creating an Adjusted Trial Balance,Financial Statements and Closing the Books,Expert Advice: Closing the Books,Introduction and Balance Sheet Overview,QuickBooks Online Demo: The Balance Sheet,How to Read a Balance Sheet,Income Statement Overview,QuickBooks Online Demo: The Profit and Loss Statement,Expert Advice: Explaining the Income Statement to a Client,Statement of Equity Overview,Cash Flow Statement Overview,How These Statements Work Together,Wrapping Up with Lou
Accounting Principles and Practices: You're Invited to Bianca's Bookkeeping Bootcamp!,Bootcamp Welcome,Introduction to Key Assumptions of Accounting and Reporting,Expert Advice on Key Assumptions,Job Readiness Commercial,Introduction to the Periodicity Assumption and Learning Objectives,Overview of the Periodicity Assumptions and Its Significance,Overview of the Revenue Recognition Principle and Example,Overview of the Matching Principle and Example,Lesson Summary and Wrap,Introduction and Objectives,Cash-Basis Accounting,Accrual Method of Accounting,Hybrid Accounting,Accounting Methods in QuickBooks Online,Lesson Summary and Wrap |
Linear Algebra for Machine Learning and Data Science | 1. Week 1: Systems of linear equations
2. Week 2: Solving systems of linear equations
3. Week 3: Vectors and Linear Transformations
4. Week 4: Determinants and Eigenvectors | Week 1: Systems of linear equations: Matrices are commonly used in machine learning and data science to represent data and its transformations. In this week, you will learn how matrices naturally arise from systems of equations and how certain matrix properties can be thought in terms of operations on system of equations.
Week 2: Solving systems of linear equations: In this week, you will learn how to solve a system of linear equations using the elimination method and the row echelon form. You will also learn about an important property of a matrix: the rank. The concept of the rank of a matrix is useful in computer vision for compressing images.
Week 3: Vectors and Linear Transformations: An individual instance (observation) of data is typically represented as a vector in machine learning. In this week, you will learn about properties and operations of vectors. You will also learn about linear transformations, matrix inverse, and one of the most important operations on matrices: the matrix multiplication. You will see how matrix multiplication naturally arises from composition of linear transformations. Finally, you will learn how to apply some of the properties of matrices and vectors that you have learned so far to neural networks.
Week 4: Determinants and Eigenvectors: In this final week, you will take a deeper look at determinants. You will learn how determinants can be geometrically interpreted as an area and how to calculate determinant of product and inverse of matrices. We conclude this course with eigenvalues and eigenvectors. Eigenvectors are used in dimensionality reduction in machine learning. You will see how eigenvectors naturally follow from the concept of eigenbases. | Week 1: Systems of linear equations: Specialization introduction,Course introduction,What to expect and how to succeed,A note on programming experience,Linear Algebra Applied I,Linear Algebra Applied II,System of sentences,System of equations,System of equations as lines and planes,A geometric notion of singularity,Singular vs non-singular matrices,Linear dependence and independence,The determinant,Conclusion
Week 2: Solving systems of linear equations: Solving non-singular system of linear equations,Solving singular system of linear equations,Solving system of equations with more variables,Matrix row-reduction,Row operations that preserve singularity,The rank of a matrix,The rank of a matrix in general,Row echelon form,Row echelon form in general,Reduced row echelon form,The Gaussian Elimination Algorithm,Conclusion
Week 3: Vectors and Linear Transformations: Machine Learning Motivation,Vectors and their properties,Vector operations,The dot product,Geometric Dot Product,Multiplying a matrix by a vector,Matrices as linear transformations,Linear transformations as matrices,Matrix multiplication,The identity matrix,Matrix inverse,Which matrices have an inverse?,Neural networks and matrices,Conclusion
Week 4: Determinants and Eigenvectors: Week 4 Introduction,Singularity and rank of linear transformations,Determinant as an area,Determinant of a product,Determinants of inverses,Bases in Linear Algebra,Span in Linear Algebra,Eigenbases,Eigenvalues and Eigenvectors,Calculating Eigenvalues and Eigenvectors,On the Number of Eigenvectors,Dimensionality Reduction and Projection,Motivating PCA,Variance and Covariance,Covariance Matrix,PCA - Overview,PCA - Why It Works,PCA - Mathematical Formulation,Discrete Dynamical Systems,Conclusion |
Python for Data Science, AI & Development | 1. Python Basics
2. Python Data Structures
3. Python Programming Fundamentals
4. Working with Data in Python
5. APIs and Data Collection | Python Basics: This module teaches the basics of Python and begins by exploring some of the different data types such as integers, real numbers, and strings. Continue with the module and learn how to use expressions in mathematical operations, store values in variables, and the many different ways to manipulate strings.
Python Data Structures: This module begins a journey into Python data structures by explaining the use of lists and tuples and how they are able to store collections of data in a single variable. Next learn about dictionaries and how they function by storing data in pairs of keys and values, and end with Python sets to learn how this type of collection can appear in any order and will only contain unique elements.
Python Programming Fundamentals: This module discusses Python fundamentals and begins with the concepts of conditions and branching. Continue through the module and learn how to implement loops to iterate over sequences, create functions to perform a specific task, perform exception handling to catch errors, and how classes are needed to create objects.
Working with Data in Python: This module explains the basics of working with data in Python and begins the path with learning how to read and write files. Continue the module and uncover the best Python libraries that will aid in data manipulation and mathematical operations.
APIs and Data Collection: This module delves into the unique ways to collect data by the use of APIs and web scraping. It further explores data collection by explaining how to read and collect data when dealing with different file formats. | Python Basics: Course Introduction,Introduction to Python,Getting Started with Jupyter,Types,Expressions and Variables,String Operations
Python Data Structures: Lists and Tuples,Dictionaries,Sets
Python Programming Fundamentals: Conditions and Branching,Loops,Functions,Exception Handling,Objects and Classes
Working with Data in Python: Reading Files with Open,Writing Files with Open,Pandas: Loading Data,Pandas: Working with and Saving Data,One Dimensional Numpy,Two Dimensional Numpy
APIs and Data Collection: Application Program Interface,REST APIs & HTTP Requests - Part 1,REST APIs & HTTP Requests - Part 2,(Optional) HTML for Web Scraping,(Optional) Web Scraping,Working with Different File Formats |
Analyze Data to Answer Questions | 1. Organize data for more effective analysis
2. Format and adjust data
3. Aggregate data for analysis
4. Perform data calculations | Organize data for more effective analysis: Organizing data makes the data easier to use in your analysis. In this part of the course, you’ll learn the importance of organizing your data through sorting and filtering. You’ll explore these processes in both spreadsheets and SQL as you continue to prepare your data.
Format and adjust data: As you move closer to analyzing your data, you’ll want to have it formatted and ready to go. In this part of the course, you’ll learn all about converting and formatting data, including how SQL queries can help you combine data. You’ll also find out the value of feedback and support from your colleagues and how it can lead to learnings that you can apply to your work.
Aggregate data for analysis: As part of your analysis, you’ll often have to combine data in order to gain insights and complete business objectives. In this part of the course, you’ll explore the functions, procedures, and syntax involved in combining, or aggregating, data. You’ll learn how to do this from multiple cells in spreadsheets and from multiple database tables using SQL queries.
Perform data calculations: Calculations are a common task for data analysts. In this part of the course, you’ll explore formulas, functions, and pivot tables in spreadsheets and queries in SQL, all of which will help with your calculations. You’ll also learn about the benefits of using SQL to manage temporary tables. | Organize data for more effective analysis: Introduction to getting organized,The analysis process,Ayanna: Sticking with it,Always a need to organize,Filter data with SQL,Sort data in spreadsheets,Use the SORT function in spreadsheets,Emma: Journey to a meaningful career,Sort data with SQL
Format and adjust data: Get started with data formatting,From one type to another,Data validation,Conditional formatting,Merge text strings to gain insights,Strings in spreadsheets,When you get stuck,Layla: All about the analyze stage,Running into challenges? Not to worry!,When to use which tool
Aggregate data for analysis: Aggregate data for analysis,Prepare for VLOOKUP,VLOOKUP in action,Identify and fix common VLOOKUP errors,Explore how JOINs work,Queries within queries,Use subqueries to aggregate data,Justin: Where data analysis takes you
Perform data calculations: Data calculations,Common calculation formulas,Functions and conditions,Composite functions,Start working with pivot tables,Pivot tables continued,Queries and calculations,Embed simple calculations with SQL,Calculations with other statements,Check and recheck,Temporary tables,Multiple table variations,Congratulations! Course wrap-up |
Assets, Threats, and Vulnerabilities | 1. Introduction to asset security
2. Protect organizational assets
3. Vulnerabilities in systems
4. Threats to asset security | Introduction to asset security: You will be introduced to how organizations determine what assets to protect. You'll learn about the connection between managing risk and classifying assets by exploring the unique challenge of securing physical and digital assets. You'll also be introduced to the National Institute of Standards and Technology (NIST) framework standards, guidelines and best practices to manage cybersecurity risk.
Protect organizational assets: You will focus on security controls that protect organizational assets. You'll explore how privacy impacts asset security and understand the role that encryption plays in maintaining the privacy of digital assets. You'll also explore how authentication and authorization systems help verify a user’s identity.
Vulnerabilities in systems: You will build an understanding of the vulnerability management process. You'll learn about common vulnerabilities and develop an attacker mindset by examining the ways vulnerabilities can become threats to asset security if they are exploited.
Threats to asset security: You will explore common types of threats to digital asset security. You'll also examine the tools and techniques used by cybercriminals to target assets. In addition, you'll be introduced to the threat modeling process and learn ways security professionals stay ahead of security breaches. | Introduction to asset security: Introduction to Course 5,Da'Queshia: My path to cybersecurity,Welcome to module 1,The what, why, and how of asset security,Tri: Life in asset security,Security starts with asset classification,Assets in a digital world,Elements of a security plan,The NIST Cybersecurity Framework,Wrap-up
Protect organizational assets: Welcome to module 2,Security controls,Heather: The importance of protecting PII,Fundamentals of cryptography,Public key infrastructure,Non-repudiation and hashing,Access controls and authentication systems,The mechanisms of authorization,Why we audit user activity,Tim: Finding purpose in protecting assets,Wrap-up
Vulnerabilities in systems: Welcome to module 3,Vulnerability management,Defense in depth strategy,Common vulnerabilities and exposures,Vulnerability assessments,Omad: My learning journey into cybersecurity,Protect all entry points,Niru: Adopt an attacker mindset,Pathways through defenses,Wrap-up
Threats to asset security: Welcome to module 4,The criminal art of persuasion,Phishing for information,Malicious software,The rise of cryptojacking,Cross-site scripting (XSS),Exploitable gaps in databases,A proactive approach to security,Chantelle: The value of diversity in cybersecurity,PASTA: The Process for Attack Simulation and Threat Analysis,Wrap-up,Course wrap-up |
Introduction to Healthcare | 1. Overview of Health Care Systems and Key Challenges They Face
2. Physicians, Physician Practices, and Physician Payment
3. Hospitals, Other Provider Organizations, and Related Payment Systems
4. Intermediaries, Health Insurance Plans, and Health Care Financing
5. Health Care Products and Prescription Drugs, and Quality Measurement and Improvement
6. Ethics
7. Course Wrap Up | Overview of Health Care Systems and Key Challenges They Face:
Physicians, Physician Practices, and Physician Payment:
Hospitals, Other Provider Organizations, and Related Payment Systems:
Intermediaries, Health Insurance Plans, and Health Care Financing:
Health Care Products and Prescription Drugs, and Quality Measurement and Improvement:
Ethics: Ethics in Healthcare System
Course Wrap Up: Course Summary and Final Assessment | Overview of Health Care Systems and Key Challenges They Face: Introduction,A Simple Interaction Between Providers and Patients,The Problem of Risk,Solving the Problem of Risk: Risk Pooling,Insurance and Intermediaries for Risk Pooling,Beyond Patients, Providers, and Intermediaries: Other Players in the Health Care System,Overview of the Types and Roles of Intermediaries,Overview of the Types and Roles of Providers,Providers and Levels of Care,The Challenge of Rising Health Care Costs,The Challenges of Quality and Access,Lessons for AI and Data
Physicians, Physician Practices, and Physician Payment: Characteristics of Physician Practices,Physicians, Intermediaries, and Networks,Fee for Service Payment,Procedure Codes and Diagnosis Codes,The Medicare Fee Schedule,Capitation Payment Systems: Overview and Structure,Capitation Payment Systems: Scope of Capitation,Episode-Based Payment Systems and Salary Systems,Risk Shifting in Physician Payment and Multi-Layered Physician Payment Arrangements,Incentives Created by Physician Payments,Lessons for AI and Data,Wrap Up
Hospitals, Other Provider Organizations, and Related Payment Systems: Basic Operations and Characteristics of Hospitals,How Hospitals Relate to Physicians and Intermediaries,Hospital Payment Methods: Charge Masters/FFS and Per Diem,Hospital Payment Methods: DRGs,Hospital Payment Methods: Global Budgets,Hospital Payment Topics: Payments for Inpatient vs Outpatient Services, Hospital vs Physician Payments; Charges and Payments,Risk and Incentives in Hospital Payment,Independent Facilities - Structure and Payment,Health Care Systems and Larger Provider Organizations,Pay for Performance,EMRs, EHRs, and PHRs,Providers, Provider Incentives, Data, and Tools,Wrap Up
Intermediaries, Health Insurance Plans, and Health Care Financing: Intermediaries and their Goals,Intermediaries and the Broad Challenges Facing Health Care Systems,Networks and Selective Contracting,Provider Payment Methods and Levels,Patient Cost Sharing,Utilization Review, Gatekeepes, and Other Methods of Directly Influencing Care,Coverage Decisions,Combinations and Tradeoffs,Three Stereotypical Plan Designs: "Traditional," HMO, and PPO,Some More Recent Trends in Plan Design,Public and Private Plans (and Employer-Provided Private Insurance in the U.S.),The U.S. Medicare Program,The U.S. Medicaid Program,Intermediaries: Lessons for Innovators,Wrap Up
Health Care Products and Prescription Drugs, and Quality Measurement and Improvement: Health care products, approvals, and prescription drugs,Prescription Drug Approval Processes,Patents, Branded Drugs, and Generic Drugs,Patients, Insurance, Formularies, and Prescription Drugs,Intermediaries, Pharmacy Benefit Managers, Drug Prices, and Rebates,Products and Prescription Drugs Wrap Up - Data and Opportunities for Innovation,Quality of Care Overview and Key Organizing Concepts,Overview, and Structural Quality Measures,Process Quality Measures,Outcome Quality Measures and Satisfaction Measures,Overview of Some Approaches to Improving Quality,Innovation and Data in Quality Improvement,Wrap Up
Ethics: Overview of AI applications in delivery of health care services and ethical issues,Ethical frameworks for health care and for AI,AI and incentives in health care delivery and payment structures,More examples of AI and incentives in health care delivery and payment structures
Course Wrap Up: Course Summary |
The Science of Well-Being | 1. Introduction
2. Misconceptions About Happiness
3. Why Our Expectations are so Bad
4. How Can We Overcome Our Biases
5. Stuff that Really Makes Us Happy
6. Putting Strategies into Practice
7. Start Your Final Rewirement Challenge
8. Continue Your Rewirement Challenge
9. Continue Your Rewirement Challenge
10. Submit Your Final Assignment | Introduction: Why take this course?
Misconceptions About Happiness: What do we think will make us happy?
Why Our Expectations are so Bad: Why do we mispredict what makes us happy?
How Can We Overcome Our Biases: How we counteract our annoying features of the mind?
Stuff that Really Makes Us Happy: What can we do to improve our happiness?
Putting Strategies into Practice: How can we intentionally put these strategies into practice and build healthier habits?
Start Your Final Rewirement Challenge: What rewirement will you commit to for the next 4 weeks?
Continue Your Rewirement Challenge: How can you rely on others to help you change your behaviors?
Continue Your Rewirement Challenge: How can you design your environment to help you change your behaviors?
Submit Your Final Assignment: What mindset can you have to appreciate your progress so far and continue your progress beyond the course? | Introduction: Start a New Journey!,Become Happier by Learning & Applying Psychological Science,Why This Course Exists,What is the G.I. Joe Fallacy?,Watch out for scams
Misconceptions About Happiness: Savoring,Gratitude,Part 1 - Good Job,Part 2 - Money,Part 3 - Awesome Stuff, True Love, Perfect Body & Good Grades,Annoying Features of the Mind,Question & Answer
Why Our Expectations are so Bad: Kindness,Social Connection,Annoying Feature #1,Annoying Feature #2,Annoying Feature #3,Annoying Feature #4,Annoying Features Summary,Question & Answer
How Can We Overcome Our Biases: Exercise,Sleep,Part 1 - Rethink "Awesome Stuff",Part 2 - Thwart Hedonic Adaptation,Part 3 - Reset Your Reference Points,Overcome Biases Summary,Question & Answer
Stuff that Really Makes Us Happy: Meditation,Good Job,Good Grades,Kindness,Interview with Elizabeth Dunn,Social Connection,Interview with Nicholas Epley,Time Affluence,Mind Control,Healthy Practices,Question & Answer
Putting Strategies into Practice: Part 1 - Situation Support,Part 2 - Goal Setting,Interview with Gabriele Oettingen,Question & Answer,Recap
Start Your Final Rewirement Challenge: Welcome to Your Final Rewirement Challenge
Continue Your Rewirement Challenge: Welcome to Week 2
Continue Your Rewirement Challenge: Welcome to Week 3
Submit Your Final Assignment: Welcome to Week 4,Congratulations on Completing Your Challenge!,Students Discuss Their Rewirement Challenges,Conclusion |
Capstone: Applying Project Management in the Real World | 1. Initiating a project
2. Building out a project plan
3. Maintaining quality
4. Effective stakeholder communication | Initiating a project: You will learn to analyze project documents and supporting materials to identify project requirements, evaluate stakeholders, and problem-solve. You’ll complete a project charter and use it as a tool to align project scope and goals among stakeholders. You will also add specificity to project goals to make them SMART and apply effective negotiation skills with stakeholders to prioritize project goals.
Building out a project plan: You will examine project documentation, conduct online research, and analyze key conversations to identify tasks and milestones and then document and prioritize them in a project plan. You will also demonstrate effective communication techniques for making accurate time estimates for project tasks.
Maintaining quality: You will learn to define and describe quality management standards and evaluate against those standards to ensure that the project is achieving the required level of quality. You will distinguish evaluation questions from survey questions and recognize how to effectively share qualitative data. You will also learn strategies to facilitate a productive retrospective by encouraging participation, accountability, and positivity.
Effective stakeholder communication: You will learn to communicate and escalate project problems to stakeholders and to demonstrate your impact through effective reporting strategies. Additionally, you will prepare for job interviews in the field by reflecting on past projects, developing an elevator pitch, and anticipating common questions. You’ll also learn AI skills that you can use as a project management professional. | Initiating a project: Introduction to Course 6,Project charters: Purpose and components,Project charters: Stakeholder alignment,Project charters: Drafting SMART goals,Project charters: Defining scope, benefits, and costs,Afsheen: Initiating a project effectively,Completing a stakeholder analysis,Finding mutually beneficial solutions,Stanton: Managing scope changes with stakeholders,Applying influence in negotiations,Wrap-up
Building out a project plan: Introduction: Building out a project plan,Identifying project tasks: Analyzing documentation,Identifying project tasks: Conducting online research,Identifying project tasks: Analyzing key conversations,Ordering tasks and identifying milestones,Time estimation: Asking the right questions,Time estimation: Three-point estimating,Time estimation: Applying confidence level ratings,Time estimation: Effective time estimate negotiation,Time estimation: Negotiating with empathy,Torie: Practicing empathy as a program manager,Wrap-up
Maintaining quality: Introduction: Maintaining quality,Key quality management concepts,Defining quality standards,Creating evaluation questions,Determining evaluation indicators,Developing a survey,Delivering an evaluation presentation,The value of retrospectives,Retrospectives: Encouraging participation,Retrospectives: Encouraging accountability,Retrospectives: Addressing negativity,Dana: Leading positive retrospectives,Wrap-up
Effective stakeholder communication: Introduction: Effective stakeholder communication,Communicating project problems,Chris: The art of problem-solving,Connecting project problems to goals,Writing emails to escalate a problem,Laura: Stakeholder communication best practices,Completing a closeout report,Project impact report,Wrap-up,Personal closing report,Acing an elevator pitch,The STAR method,Interviewing remotely,Interview tips from Googlers,Boost your project management skills with AI,Use AI to create a project charter,Identify potential project risks with gen AI,Use AI to improve project communications,Execute your meetings more efficiently with AI,Plan sprint retrospectives using AI,Introducing Google AI Essentials,Congratulations from your instructors,Exploring Professional Opportunities |
Stanford Introduction to Food and Health | 1. Background on Food & Nutrients
2. Contemporary Trends in Eating
3. Future Directions in Health - Part I
4. Future Directions in Health - Part 2
5. Cooking Workshop
6. Recommended Optional Resources | Background on Food & Nutrients: In this section we will examine the social and cultural shifts that have contributed to our modern epidemics of overweight and obesity. We will briefly review the nutrients found in foods, their different functions in the human body and how we can support our own health by choosing wisely from the foods within each category.
Contemporary Trends in Eating: In this section, we will explore the ways in which highly processed foods differ from real, whole food and the implications of food processing on our health. We’ll also look at how our consumption of sugar has changed in recent decades and explore sensible solutions for people who wish to start eating better. We will also meet Kevin, a middle-aged pre-diabetic man, and find out how a step-wise approach to behavior change helped him change for the better.
Future Directions in Health - Part I: This section focuses on sustainable solutions to the challenge of choosing healthier foods more frequently. Michael Pollan explains his mantra and how we can use it to make better food choices. We also begin to explore practical tips for preparing foods that will support our health and enjoyment.
Future Directions in Health - Part 2: In this section you will find more practical tips for grocery shopping, reading labels and assembling a balanced meal. We also learn more about the most important secret ingredient for success: moderation.
Cooking Workshop: A few years ago, a friend of mine started a healthy eating and fitness website called Grokker. She asked me to make some instructional cooking videos and generously agreed to share some of them with you. Thanks, Lorna! (If you like this section, you can find many more great videos on cooking and fitness at Grokker.com)
Recommended Optional Resources: Here is a list of recommended books and videos that can help deepen your understanding of the course material. Feel free to explore the recommendations on this list to learn more about food, health, eating behaviors, and more. | Background on Food & Nutrients: Introduction,A Sociocultural History of Obesity,Macronutrient Structure & Metabolism,Carbohydrate-rich Foods & the Glycemic Index,Animal & Plant-based Proteins,Dietary Fats & Their Effects on Human Health
Contemporary Trends in Eating: Why Are Highly Processed Foods Generally Less Healthy?,Trends in Sugar Consumption & Recommendations,The Case for Cooking,A Case Study: Middle-aged Pre-diabetic Man,A Step-wise Approach to Behavior Change
Future Directions in Health - Part I: Eat Food. Not Too Much. Mostly Plants.,Cooking: Fundamental Ingredients,Cooking: Increasing Vegetable Intake,Cooking: Sensible Substitutions
Future Directions in Health - Part 2: Constructing a Healthy Plate,Shopping in a Supermarket,Reading Nutrition Labels,The Importance of Moderation in Maintaining a Healthy Diet
Cooking Workshop: How to Make Gluten Free Crêpes,How to Make Lemon Herb Roasted Chicken,How to Make Asparagus Torta,How to Make Idlis - Indian Rice Cakes,How to Make Pad Thai,How to Make Lasagna,How to Make Ricotta Cake,How to Make Pancakes in a Blender,How to Make a Sweet Pea Salad,How to Make Egg Sandwiches
Recommended Optional Resources: List of Recommended Readings,List of Recommended Documentaries,List of Recommended Websites |
Operating Systems and You: Becoming a Power User | 1. Navigating the System
2. Users and Permissions
3. Package and Software Management
4. Filesystems
5. Process Management
6. Operating Systems in Practice | Navigating the System: Welcome to the Operating Systems course of the IT Support Professional Certificate! In the first module of this course, we will cover the basics of Windows and Linux operating systems (OS). We will learn about how directories and files work in Windows and Linux OS. You will also learn practical ways to manipulate files and directories in the Windows graphical user interface (GUI), Windows command line interface (CLI), and Linux shell. By the end of this module, you will interact with files and directories and perform basic text manipulation in Windows and Linux OS.
Users and Permissions: In the second module of this course, we'll learn about configuring users and permissions in Windows and Linux OS. As an IT Support Specialist, it's important to know how to grant the appropriate permissions to users and groups for both Windows and Linux OS. By the end of this module, you will know how to add, modify, and remove users for a computer and for specific files and folders by using the Windows GUI, Windows CLI, and Linux shell.
Package and Software Management: In the third module of this course, we'll learn about package and software management in Windows and Linux OS. It's important to know how package installs work and how devices and drivers are managed within these operating systems. We will also learn about different packaging and file compression methods. By the end of this module, you will know how to create, update, and remove software by using the Windows GUI, Windows CLI and Linux shell.
Filesystems: In the fourth module of this course, we'll learn about how filesystems work for Windows and Linux OS. We'll learn about filesystem types and why they're different for certain OS. We'll learn about disk partitioning and virtual memory and why these are so important for an IT Support Specialist's role. We'll also cover ways mount and unmount filesystems, read disk usage, and repair filesystems. By the end of this module, you will partition and format a disk drive yourself in both Windows and Linux.
Process Management: In the fifth module of this course, we'll explore process management. As an IT Support Specialist, it is important to use system tools to read and understand process statuses of machines. We will cover ways to start and terminate a process in Windows and Linux. We will also apply troubleshooting tools to solve problems with processes and resources. By the end of this module, you will use Windows and Linux commands to do practical process maintenance.
Operating Systems in Practice: Congratulations, you've made it to the final module in the course! In the last module of this course, we will cover some of the practical aspects of operating systems that you'll use all the time in IT Support. We will cover remote access and how to troubleshoot a computer from afar. We'll explore virtualization tools to manage and remove virtual instances, use logs for system monitoring, and show you a few different techniques for OS deployment. By the end of this module, you will apply all the skills from this course to debug some issues within Windows and Linux OS. Good luck! | Navigating the System: Course Introduction,Lesson Overview & Practice Tips,Windows: List Directories in a GUI,Windows: List Directories in CLI,Linux: List Directories,Windows: Changing Directories in the GUI,Windows: Changing Directories in the CLI,Linux: Changing Directories in Bash,Windows: Make Directories in the GUI & CLI,Linux: Make Directories in Bash,Windows: Command History,Linux: Command History,Windows: Copying Files & Directories,Linux: Copying Files and Directories,Windows: Moving and Renaming Files, Directories,Linux: Moving and Renaming Files, Directories,Windows: Removing Files & Directories,Linux: Removing Files & Directories,Chelsea: Their learner story,Cindy: Why OS is important,Windows: Display File Contents,Linux: Display File Contents,Windows: Modifying Text Files,Linux: Modifying Text Files,Windows Powershell,Windows: Searching within Files,Windows: Searching within Directories,Linux: Searching within Files,Windows: Input, Output, and the Pipeline,Linux: Input, Output and Pipeline,Windows and Linux Advanced Navigation,Ben: My first tech job
Users and Permissions: Users, Administrators, and Groups, Oh My!,Windows: View User and Group Information,Windows: View User and Group Information using CLI,Linux: Users, Superuser and Beyond,Windows: Passwords,Linux: Passwords,Windows: Adding and Removing Users,Linux: Adding and Removing Users,Mobile Users and Accounts,Ben: Life as a CIO,Windows: File Permissions,Linux: File Permissions,Windows: Modifying Permissions,Linux: Modifying Permissions,Windows: Special Permissions,Linux: SetUID, SetGID, Sticky Bit
Package and Software Management: Module Introduction,Windows: Software Packages,Linux: Software Packages,Mobile App Packages,Windows: Archives,Linux: Archives,Windows: Package Dependencies,Linux: Package Dependencies,Windows: Package Manager,Linux: Package Manager Apt,Windows: Underneath the Hood,Linux: Underneath the Hood,Windows: Devices and Drivers,Linux: Devices and Drivers,Windows: Operating System Updates,Linux: Operating System Updates
Filesystems: Module Introduction,Review of Filesystems,Disk Partitioning and File System Essentials,Windows: Disk Partitioning and Formatting a Filesystem,Windows: Mounting and Unmounting a Filesystem,Linux: Disk Partitioning and Formatting a Filesystem,Linux: Mounting and Unmounting a Filesystem,Windows: Swap,Linux: Swap,Windows: Files,Linux: Files,Windows: Disk Usage,Linux: Disk Usage,Windows: Filesystem Repair,Linux: Filesystem Repair,Ben: The power of computers
Process Management: Module Introduction,Programs vs Processes Revisited,Windows: Process Creation and Termination,Linux: Process Creation and Termination,Jess: From challenge to passion,Windows: Reading Process Information,Linux: Reading Process Information,Windows: Signals,Linux: Signals,Windows: Managing Processes,Linux: Managing Processes,Mobile App Management,Windows: Resource Monitoring,Linux: Resource Monitoring
Operating Systems in Practice: Introduction,Remote Connections on Windows,Remote Connection: File Transfer on Linux,Remote Connection: File Transfer on Windows,Virtual Machines,System Monitoring,The Windows Event Viewer,Linux Logs,Working with Logs,Imaging Software,Operating Systems Deployment Methods,Mobile Device Resetting and Imaging,Interview Role Play: Operating Systems,Course Wrap Up,Heather: Early career advice,Congratulations! |
Data Analysis with R Programming | 1. Programming and data analytics
2. Programming using RStudio
3. Working with data in R
4. More about visualizations, aesthetics, and annotations
5. Documentation and reports | Programming and data analytics: R is a programming language that can help you in your data analysis process. In this part of the course, you’ll learn about R and RStudio, the environment you’ll use to work in R. You’ll explore the benefits of using R and RStudio as well as the components of RStudio that will help you get started.
Programming using RStudio: Using R can help you complete your analysis efficiently and effectively. In this part of the course, you’ll explore the fundamental concepts associated with R. You’ll learn about functions and variables for calculations and other programming. In addition, you'll discover R packages, which are collections of R functions, code and sample data that you’ll use in RStudio.
Working with data in R: The R programming language was designed to work with data at all stages of the data analysis process. In this part of the course, you’ll examine how R can help you structure, organize, and clean your data using functions and other processes. You’ll learn about data frames and how to work with them in R. You’ll also revisit the issue of data bias and how R can help.
More about visualizations, aesthetics, and annotations: R is a tool well-suited for creating detailed visualizations. In this part of the course, you’ll learn how to use R to generate and troubleshoot visualizations. You’ll also explore the features of R and RStudio that will help you with the aesthetics of your visualizations and for annotating and saving them.
Documentation and reports: When you’re ready to save and present your analysis, R has different options to consider. In this part of the course, you’ll explore R Markdown, a file format for making dynamic documents with R. You’ll find out how to format and export R Markdown, including how to incorporate R code chunks in your documents. | Programming and data analytics: Introduction to the exciting world of programming,Fun with R,Carrie: Getting started with R,Programming languages,Introduction to R,Intro to RStudio
Programming using RStudio: Programming using RStudio,Programming fundamentals,Operators and calculations,The gift that keeps on giving,Welcome to the tidyverse,More on the tidyverse,Use pipes to nest code,Connor: Coding tips
Working with data in R: Data in R,R data frames,Working with data frames,Cleaning up with the basics,Organize your data,Transforming data,Same data, different outcome,The bias function
More about visualizations, aesthetics, and annotations: Visualizations in R,Visualization basics in R and tidyverse,Getting started with ggplot(),Joseph: Career path to people analytics,Enhancing visualizations in R,Doing more with ggplot,Aesthetics and facets,Annotation layer,Saving your visualizations
Documentation and reports: Documentation and reports,Overview of R Markdown,Using R Markdown in RStudio,Structure of markdown documents,Meg: Programming is empowering,Even more document elements,Code chunks,Exporting documentation |
Introduction to Data Engineering | 1. Introduction to Data Engineering
2. The Data Engineering Lifecycle and Undercurrents
3. Data Architecture
4. Translating Requirements to Architecture | Introduction to Data Engineering: Gain a high-level overview of the data engineering lifecycle and key undercurrents to understand how data engineers add business value to organizations. Start developing a mental framework for thinking like a data engineer, starting with gathering stakeholder needs and translating them into system requirements. Learn the basics of working on the cloud from an AWS expert.
The Data Engineering Lifecycle and Undercurrents: Dive deeper into the stages of the data engineering lifecycle and its key undercurrents. Build an end-to-end data pipeline on AWS that encompasses all the stages of the data engineering lifecycle.
Data Architecture: Define data architecture and how it fits within the larger enterprise architecture. Examine the principles of good data architecture and how these principles inform tools and technology choices. Evaluate and optimize the security, performance, reliability, cost-efficiency, and scalability of a web application hosted on AWS.
Translating Requirements to Architecture: Practice gathering stakeholder needs and translating them into system requirements. Choose the appropriate tools and technologies based on the system requirements, then build an end-to-end data system that includes a batch and a streaming component to train a product recommendation system and serves product recommendations to a sales platform. | Introduction to Data Engineering: Welcome to Data Engineering,Course 1 Overview,Data Engineering Defined,[Optional] A Brief History of Data Engineering,The Data Engineer Among Other Stakeholders,[Optional] Business Value,System Requirements,[Optional] Conversation with Sol Rashidi,[Optional] Conversation with Jordan Morrow,Requirements Gathering Conversation,Translate Stakeholder Needs into Specific Requirements,Thinking Like a Data Engineer,Data Engineering on the Cloud,Meet Morgan Willis,Intro to the AWS Cloud,Intro to AWS Core Services,Walkthrough of the AWS Management Console,Week 1 Summary
The Data Engineering Lifecycle and Undercurrents: Week 2 Overview,Data Generation in Source Systems,Ingestion,Storage,Queries, Modeling, and Transformation,Serving Data,Introduction to the Undercurrents,Security,Data Management,Data Architecture,DataOps,Orchestration,Software Engineering,Lesson Intro,The Data Engineering Lifecycle on AWS,The Undercurrents on AWS,Lab Walkthrough - Introduction to the Lab,Lab Walkthrough - Setting up the Lab,Lab Walkthrough - Preview of the Lab Content,Week 2 Summary
Data Architecture: Week 3 Overview,What is Data Architecture?,[Optional] Conway's Law,Principles of Good Data Architecture,Always Architecting,When your Systems Fail,Batch Architectures,Streaming Architectures,Architecting for Compliance,Choosing Tools and Technologies,Location,Monolith vs Modular Systems,Cost Optimization and Business Value,Build vs Buy,Server, Container, and Serverless Compute Options,How the Undercurrents Impact Your Decisions,Intro to the AWS Well-Architected Framework,The AWS Well-Architected Framework,Lab Walkthrough - Introduction to the Lab,Lab Walkthrough - Monitoring the Web App,Lab Walkthrough - Applying the Principles of Good Data Architecture,Week 3 Summary
Translating Requirements to Architecture: Week 4 Overview,Requirements,Conversation with Matt Housley,Conversation with the CTO,Conversation with Marketing,Breaking Down the Conversation with Marketing,Conversation with the Software Engineer,Documenting Nonfunctional Requirements,Requirements Gathering Summary,Requirements Gathering Exercise,Follow-up Conversation with the Data Scientist,AWS Services for Batch Pipelines,AWS Services for Streaming Pipelines,Lab Walkthrough - Implementing the Batch Pipeline,Lab walkthrough - Setting up the Vector Database,Lab walkthrough - Implementing the Streaming Pipeline,Course 1 Summary |
Unsupervised Learning, Recommenders, Reinforcement Learning | 1. Unsupervised learning
2. Recommender systems
3. Reinforcement learning | Unsupervised learning: This week, you will learn two key unsupervised learning algorithms: clustering and anomaly detection
Recommender systems:
Reinforcement learning: This week, you will learn about reinforcement learning, and build a deep Q-learning neural network in order to land a virtual lunar lander on Mars! | Unsupervised learning: Welcome!,What is clustering?,K-means intuition,K-means algorithm,Optimization objective,Initializing K-means,Choosing the number of clusters,Finding unusual events,Gaussian (normal) distribution,Anomaly detection algorithm,Developing and evaluating an anomaly detection system,Anomaly detection vs. supervised learning,Choosing what features to use
Recommender systems: Making recommendations,Using per-item features,Collaborative filtering algorithm,Binary labels: favs, likes and clicks,Mean normalization,TensorFlow implementation of collaborative filtering,Finding related items,Collaborative filtering vs Content-based filtering,Deep learning for content-based filtering,Recommending from a large catalogue,Ethical use of recommender systems,TensorFlow implementation of content-based filtering,Reducing the number of features (optional),PCA algorithm (optional),PCA in code (optional)
Reinforcement learning: What is Reinforcement Learning?,Mars rover example,The Return in reinforcement learning,Making decisions: Policies in reinforcement learning,Review of key concepts,State-action value function definition,State-action value function example,Bellman Equation,Random (stochastic) environment (Optional),Example of continuous state space applications,Lunar lander,Learning the state-value function,Algorithm refinement: Improved neural network architecture,Algorithm refinement: ϵ-greedy policy,Algorithm refinement: Mini-batch and soft updates (optional),The state of reinforcement learning,Summary and thank you,Andrew Ng and Chelsea Finn on AI and Robotics |
Crash Course on Python | 1. Hello Python!
2. Basic Python Syntax
3. Loops
4. Strings, Lists and Dictionaries
5. Final Project | Hello Python!: In this module we’ll introduce you to the Coursera platform and the course format. Then, we’ll dive into the basics of programming languages and syntax, as well as automation using scripting. We’ll also introduce you to the Python programming language and cover some basic functions and keywords of the language, along with some arithmetic operations. Lastly, we'll go over some code editors and IDEs that you can use to write Python code.
Basic Python Syntax: In this module you’ll learn about different data types in Python, how to identify them, and how to convert between them. You’ll also learn how to use variables to assign data and to reference variables. You’ll deep dive into functions: how to define them, pass them parameters, and have them return information. You’ll explore the concepts of code reuse, code style, and refactoring complex code, along with effectively using code comments. Finally, you’ll learn about comparing data using equality and logical operators, and leveraging these to build complex branching scripts using if statements.
Loops: In this module you'll explore the intricacies of loops in Python! You'll learn how to use while loops to continuously execute code, as well as how to identify infinite loop errors and how to fix them. You'll also learn to use for loops to iterate over data, and how to use the range() function with for loops. You'll also explore common errors when using for loops and how to fix them.
Strings, Lists and Dictionaries: In this module you'll dive into more advanced ways to manipulate strings using indexing, slicing, and advanced formatting. You'll also explore the more advanced data types: lists, tuples, and dictionaries. You'll learn to store, reference, and manipulate data in these structures, as well as combine them to store complex data structures.
Final Project: In this module, you'll learn how to apply a problem-solving framework to tackle a challenging project. You'll learn how to formulate a problem statement to understand a challenge, conduct some research to see what options are available, then begin planning how you to solve a problem. | Hello Python!: Specialization Introduction,Course Introduction,The Beginning of Your Programming Journey,What is programming?,What is automation?,Getting Computers to Work for You,What is Python?,Why is Python relevant to IT?,Other Languages,Hello, World!,Getting Information from the User,Python Can Be Your Calculator,Code editors and IDEs overview,Use the command-line,Use JupyterLab and Jupyter Notebooks,Use Colab,Use VS Code,First Steps Wrap Up,Meet Marga, the Curriculum Developer
Basic Python Syntax: Basic Python Syntax introduction,Data Types,Expressions, numbers, and type conversions,Defining Functions,Returning Values,The principles of code reuse,Code style,Comparing things,Branching with if Statements,else Statements,elif Statements,In Marga's Words: Why I Like Python,Basic Syntax Wrap Up
Loops: Introduction to Loops,What is a while loop?,More while loop examples,Why Initializing Variables Matters,Infinite Loops and How to Break Them,What is a for loop?,More for loop examples,Nested for Loops,Common Errors in for Loops,What is recursion? (Optional),Recursion in Action in the IT Context,Loops Wrap Up,In Marga's Words: How I Got Into Programming
Strings, Lists and Dictionaries: Basic Structures Introduction,What is a string?,The Parts of a String,Creating New Strings,More String Methods,Formatting Strings,What is a list?,Modifying the Contents of a List,Lists and Tuples,Iterating over Lists and Tuples,List Comprehensions,List comprehension vs for loops,What is a dictionary?,Iterating over the Contents of a Dictionary,Dictionaries vs. Lists,OOP Introduction (Optional),Instance Methods (Optional),Basic Structures Wrap Up,In Marga's Words: My Most Challenging Script
Final Project: Final Project Introduction,Problem Statement,Research,Planning,Writing the Script,Putting It All Together,Congratulations!,Sneak Peek of the Next Course |
Private Equity and Venture Capital | 1. An Introduction to Private Equity and Venture Capital
2. Discovering Private Equity Investors: Legal Issues and Taxation
3. The Management Of Private Equity And Venture Capital Funds
4. Company Valuation And Deal Making In Private Equity Settings
5. FINAL TEST | An Introduction to Private Equity and Venture Capital:
Discovering Private Equity Investors: Legal Issues and Taxation:
The Management Of Private Equity And Venture Capital Funds:
Company Valuation And Deal Making In Private Equity Settings:
FINAL TEST: In this section you can find the final graded quiz covering all topics seen so far. | An Introduction to Private Equity and Venture Capital: Course Introduction,1.1 What Is Private Equity and Venture Capital?,1.2 Why Companies Need Private Equity and Venture Capital,1.3 Private Equity Clusters: Through the Fund's Life Cycle,1.4 Seed, Startup, and Early Stage Financing,1.5 Expansion Financing,1.6 Replacement Financing,1.7 Vulture Financing,1.8 Private Equity and Venture Capital: Today and Tomorrow - Interview with Fabio Sattin
Discovering Private Equity Investors: Legal Issues and Taxation: 2.1 Private Equity Investors: The Map to Investigate,2.2 Closed-End Funds in Europe: An Overview,2.3 Closed-End Funds in Europe: Lifetime of a Fund,2.4 Management Fees and Carried Interest,2.5 Investment Firms and Banks in Europe,2.6 Limited Partnerships in the US,2.7 The SBIC Experience in the US,2.8 Funds and VCTs in the UK,2.9 Taxation around the World,2.10 New Solutions: SPACs, Private Debt Funds, Venture Philanthropy, and Crowd Funding,2.11 Calculating Returns
The Management Of Private Equity And Venture Capital Funds: 3.1 The Managerial Process for Equity Funds,3.2 Fundraising,3.3 Investing: The Decision Making Phase,3.4 Investing: The Deal Making Phase,3.5 Managing and Monitoring: Supporting the Company,3.6 Managing and Monitoring: Covenants Usage,3.7 Exiting,3.8 Private Equity Advice for Entrepreneurs - Interview with Fabio Sattin
Company Valuation And Deal Making In Private Equity Settings: 4.1 Company Valuation Fundamentals,4.2 Company Valuation: The Pillars of DCF,4.3 A Case of Company Valutation for PE Investment,4.4 Applying Company Valuation to PE Settings,4.5 Applying Company Valuation to VC Settings: The Venture Capital Method,4.6 Launch Your Own Startup: Suggestions,4.7 PE and M&A - Interview with Eugenio Morpurgo,4.8 PE and IPO - Interview with Luca Peyrano,4.9 PE, Turnaround, and Restructuring - Interview with Raffaele Legnani
FINAL TEST: Final Test |
From Likes to Leads: Interact with Customers Online | 1. Introduction to from likes to leads: interact with customers online
2. Social media strategy, planning, and publishing
3. Listening and engagement on social media
4. Social media analytics and reporting
5. Paid social media | Introduction to from likes to leads: interact with customers online: You will study the importance of social media marketing in promoting a business or product. Next, you’ll explore common social media platforms used in digital marketing and how to choose the best platform for a campaign. Then, you’ll discover the five core pillars of social media marketing: strategy, planning and publishing, listening and engagement, analytics and reporting, and paid social media.
Social media strategy, planning, and publishing: You will focus on the first two core pillars of social media marketing: strategy, and planning and publishing. You’ll also learn how to accomplish business goals with a social media marketing campaign and how to identify a target audience while building a brand identity on social media. Then, you’ll learn the differences between paid, owned, earned, and organic social media marketing. Then, you’ll determine how to publish content at the right time and with the right frequency.
Listening and engagement on social media: You will focus on the third core pillar of social media marketing: listening and engagement. You’ll learn the importance of social listening and how to use popular social listening tools. Then, you’ll explore ways to develop relationships with customers and build brand authority.
Social media analytics and reporting: You will focus on the fourth core pillar of social media marketing: analytics and reporting. You’ll explore the importance of social media analytics and describe different analytics segments. Next, you’ll learn about popular analytics tools and understand how to use the data gathered to make decisions and improvements. Then, you’ll examine the importance of social media reports and practice creating one.
Paid social media: You will focus on the fifth core pillar of social media marketing: paid social media. You’ll learn about the benefits of paid advertising on social media and how to choose the best platforms for your ads. You’ll also explore ad formats and content types for different social media platforms and measure the impact of an ad campaign on a social media platform. You’ll end the course by describing common types of social testing and how to run a social test. | Introduction to from likes to leads: interact with customers online: Introduction to Course 3,Welcome to module 1,The benefits of social media marketing,Cindy - A day in the life of a product marketing manager,The five core pillars of social media marketing,Earned, owned, and paid social media,The social media marketing funnel,Wrap-up
Social media strategy, planning, and publishing: Welcome to module 2,Define the goals of your social media strategy,Identify your social media target audience,Choose social media platforms for your campaign,Types of content on social media,Anna - Use earned, owned, and paid media in social media marketing campaigns,Determine the frequency and timing of posts,Use a social media calendar,Wrap-up
Listening and engagement on social media: Welcome to module 3,The importance of social listening,Social listening strategies,Social media engagement,How to use YouTube to grow your audience,Camille - Respond to social media comments,Increase your followers on Twitter,Write for social media,Develop your brand voice on social media,Repurpose content on social media,Catherine - Engage a social media audience through storytelling,Wrap-up
Social media analytics and reporting: Welcome to module 4,Understand social media analytics,Metrics to track with social media analytics,Use social media data to drive marketing strategy,Jon - How data and social media analytics informs decision-making and strategy,Understand social media reports,Present a social media report,Wrap-up
Paid social media: Welcome to module 5,Benefits of paid social media,Integrate paid social media into your strategy,Develop a paid social media strategy,Remarketing on social media,Components of a paid social media budget,The cost of advertising on social media,Sabrina - Conflict resolution and responding to criticism,Wrap-up,Course wrap-up |
Game Theory | 1. Week 1: Introduction and Overview
2. Week 2: Mixed-Strategy Nash Equilibrium
3. Week 3: Alternate Solution Concepts
4. Week 4: Extensive-Form Games
5. Week 5: Repeated Games
6. Week 6: Bayesian Games
7. Week 7: Coalitional Games
8. Week 8: Final Exam | Week 1: Introduction and Overview: Introduction, overview, uses of game theory, some applications and examples, and formal definitions of: the normal form, payoffs, strategies, pure strategy Nash equilibrium, dominant strategies
Week 2: Mixed-Strategy Nash Equilibrium: pure and mixed strategy Nash equilibria
Week 3: Alternate Solution Concepts: Iterative removal of strictly dominated strategies, minimax strategies and the minimax theorem for zero-sum game, correlated equilibria
Week 4: Extensive-Form Games: Perfect information games: trees, players assigned to nodes, payoffs, backward Induction, subgame perfect equilibrium, introduction to imperfect-information games, mixed versus behavioral strategies.
Week 5: Repeated Games: Repeated prisoners dilemma, finite and infinite repeated games, limited-average versus future-discounted reward, folk theorems, stochastic games and learning.
Week 6: Bayesian Games: General definitions, ex ante/interim Bayesian Nash equilibrium.
Week 7: Coalitional Games: Transferable utility cooperative games, Shapley value, Core, applications.
Week 8: Final Exam: The description goes here | Week 1: Introduction and Overview: Introductory Video,1-1 Game Theory Intro - TCP Backoff,1-2 Self-Interested Agents and Utility Theory,1-3 Defining Games,1-4 Examples of Games,1-5 Nash Equilibrium Intro,1-6 Strategic Reasoning,1-7 Best Response and Nash Equilibrium,1-8 Nash Equilibrium of Example Games,1-9 Dominant Strategies,1-10 Pareto Optimality
Week 2: Mixed-Strategy Nash Equilibrium: 2-1 Mixed Strategies and Nash Equilibrium (I),2-2 Mixed Strategies and Nash Equilibrium (II),2-3 Computing Mixed Nash Equilibrium,2-4 Hardness Beyond 2x2 Games - Basic,2-4 Hardness Beyond 2x2 Games - Advanced,2-5 Example: Mixed Strategy Nash,2-6 Data: Professional Sports and Mixed Strategies
Week 3: Alternate Solution Concepts: 3-1 Beyond the Nash Equilibrium,3-2 Strictly Dominated Strategies & Iterative Removal,3-3 Dominated Strategies & Iterative Removal: An Application,3-4 Maxmin Strategies,3-4 Maxmin Strategies - Advanced,3-5 Correlated Equilibrium: Intuition
Week 4: Extensive-Form Games: 4-1 Perfect Information Extensive Form: Taste,4-2 Formalizing Perfect Information Extensive Form Games,4-3 Perfect Information Extensive Form: Strategies, BR, NE,4-4 Subgame Perfection,4-5 Backward Induction,4-6 Subgame Perfect Application: Ultimatum Bargaining,4-7 Imperfect Information Extensive Form: Poker,4-8 Imperfect Information Extensive Form: Definition, Strategies,4-9 Mixed and Behavioral Strategies,4-10 Incomplete Information in the Extensive Form: Beyond Subgame Perfection
Week 5: Repeated Games: 5-1 Repeated Games,5-2 Infinitely Repeated Games: Utility,5-3 Stochastic Games,5-4 Learning in Repeated Games,5-5 Equilibria of Infinitely Repeated Games,5-6 Discounted Repeated Games,5-7 A Folk Theorem for Discounted Repeated Games
Week 6: Bayesian Games: 6-1 Bayesian Games: Taste,6-2 Bayesian Games: First Definition,6-2 Bayesian Games: First Defintion (yoav),6-3 Bayesian Games: Second Definition,6-4 Analyzing Bayesian Games,6-5 Analyzing Bayesian Games: Another Example
Week 7: Coalitional Games: 7-1 Coalitional Game Theory: Taste,7-2 Coalitional Game Theory: Definitions,7-3 The Shapley Value,7-4 The Core,7-5 Comparing the Core and Shapley value in an Example
Week 8: Final Exam: Final Exam |
Programming for Everybody (Getting Started with Python) | 1. Chapter One - Why we Program?
2. Installing Python
3. Chapter One: Why We Program (continued)
4. Chapter Two: Variables and Expressions
5. Chapter Three: Conditional Code
6. Chapter Four: Functions
7. Chapter Five: Loops and Iteration | Chapter One - Why we Program?: These are the course-wide materials as well as the first part of Chapter One where we explore what it means to write programs. We finished Chapter One and had the quiz and first assignment in the third week of the class. Throughout the course, you may want to come back and look at these materials. This section should not take you an entire week.
Installing Python: In this module you will set things up so you can write Python programs. Not all activities in this module are required for this class so please read the "Using Python in this Class" material for details.
Chapter One: Why We Program (continued): In the first chapter, we try to cover the "big picture" of programming so you get a "table of contents" of the rest of the book. Don't worry if not everything makes perfect sense the first time you hear it. This chapter is quite broad and you would benefit from reading the chapter in the book in addition to watching the lectures to help it all sink in. You might want to come back and re-watch these lectures after you have finished a few more chapters.
Chapter Two: Variables and Expressions: In this chapter we cover how a program uses the computer's memory to store, retrieve and calculate information.
Chapter Three: Conditional Code: In this section we move from sequential code that simply runs one line of code after another to conditional code where some steps are skipped. It is a very simple concept - but it is how computer software makes "choices".
Chapter Four: Functions: This is a relatively short chapter. We will learn about what functions are and how we can use them. The programs in the first chapters of the book are not large enough to require us to develop functions, but as the book moves into more and more complex programs, functions will be an essential way for us to make sense of our code.
Chapter Five: Loops and Iteration: Loops and iteration complete our four basic programming patterns. Loops are the way we tell Python to do something over and over. Loops are the way we build programs that stay with a problem until the problem is solved. | Chapter One - Why we Program?: Video: Welcome to Class - Dr. Chuck,Video: Welcome to Python - Guido van Rossum,1.1 - Why Program,1.2 - Hardware Overview,1.3 - Python as a Language,Fun: The Textbook Authors Meet @PyCon2015,Face to Face Office Hours - Bengaluru, India
Installing Python: Demonstration: Using the Python Playground,Windows 10: Installing Python and Writing A Program,Windows: Taking Screen Shots,Macintosh: Using Python and Writing A Program,Macintosh: Taking Screen Shots,Bonus: Eben Upton and the RaspBerry Pi
Chapter One: Why We Program (continued): 1.4 - Writing Paragraphs of Code,Demonstration: Doing the "Hello World" Assignment,Interview: Daphne Koller - Building Coursera,Face-to-Face Office Hours: Milan, Italy
Chapter Two: Variables and Expressions: 2.1 - Expressions,2.2 - Expressions Part 2,2.3 - Expressions - Part 3,Worked Exercise: 2.3,Interview: Pooja Sankar - Building Piazza,Office Hours: Mountain View, CA
Chapter Three: Conditional Code: 3.1 Conditional Statements,3.2 More Conditional Statements,Worked Exercise: 3.2,Interview: Massimo Banzi: The Arduino,Office Hours: Seoul Korea
Chapter Four: Functions: 4.1 - Using Functions,4.2 - Building Functions,Interview: Guido van Rossum: The Early Years of Python,Office Hours: Manila Philippines
Chapter Five: Loops and Iteration: 5.1 - Loops and Iteration,5.2 - Definite Loops,5.3 - Finding the Largest Value,5.4 - Loop Idioms,Worked Exercise: 5.1,What's Next - Dr.Chuck,Interview: Guido van Rossum - The Modern Era of Python,Office Hours: Paris, France |
Machine Learning in Production | 1. Week 1: Overview of the ML Lifecycle and Deployment
2. Week 2: Modeling Challenges and Strategies
3. Week 3: Data Definition and Baseline | Week 1: Overview of the ML Lifecycle and Deployment: This week covers a quick introduction to machine learning production systems focusing on their requirements and challenges. Next, the week focuses on deploying production systems and what is needed to do so robustly while facing constantly changing data.
Week 2: Modeling Challenges and Strategies: This week is about model strategies and key challenges in model development. It covers error analysis and strategies to work with different data types. It also addresses how to cope with class imbalance and highly skewed data sets.
Week 3: Data Definition and Baseline: This week is all about working with different data types and ensuring label consistency for classification problems. This leads to establishing a performance baseline for your model and discussing strategies to improve it given your time and resources constraints. This week also includes the final end-to-end project. | Week 1: Overview of the ML Lifecycle and Deployment: Welcome,Steps of an ML Project,Case study: speech recognition,Course outline,Key challenges,Deployment patterns,Monitoring,Pipeline monitoring
Week 2: Modeling Challenges and Strategies: Modeling overview,Key challenges,Why low average error isn't good enough,Establish a baseline,Tips for getting started,Error analysis example,Prioritizing what to work on,Skewed datasets,Performance auditing,Data-centric AI development,A useful picture of data augmentation,Data augmentation,Can adding data hurt?,Adding features,Experiment tracking,From big data to good data
Week 3: Data Definition and Baseline: Why is data definition hard?,More label ambiguity examples,Major types of data problems,Small data and label consistency,Improving label consistency,Human level performance (HLP),Raising HLP,Obtaining data,Data pipelines,Meta-data, data provenance and lineage,Balanced train/dev/test splits,What is scoping?,Scoping process,Diligence on feasibility and value,Diligence on value,Milestones and resourcing,Final project overview |
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization | 1. Practical Aspects of Deep Learning
2. Optimization Algorithms
3. Hyperparameter Tuning, Batch Normalization and Programming Frameworks | Practical Aspects of Deep Learning: Discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model.
Optimization Algorithms: Develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models.
Hyperparameter Tuning, Batch Normalization and Programming Frameworks: Explore TensorFlow, a deep learning framework that allows you to build neural networks quickly and easily, then train a neural network on a TensorFlow dataset. | Practical Aspects of Deep Learning: Train / Dev / Test sets,Bias / Variance,Basic Recipe for Machine Learning,Regularization,Why Regularization Reduces Overfitting?,Dropout Regularization,Understanding Dropout,Other Regularization Methods,Normalizing Inputs,Vanishing / Exploding Gradients,Weight Initialization for Deep Networks,Numerical Approximation of Gradients,Gradient Checking,Gradient Checking Implementation Notes,Yoshua Bengio Interview
Optimization Algorithms: Mini-batch Gradient Descent,Understanding Mini-batch Gradient Descent,Exponentially Weighted Averages,Understanding Exponentially Weighted Averages,Bias Correction in Exponentially Weighted Averages,Gradient Descent with Momentum,RMSprop,Adam Optimization Algorithm,Learning Rate Decay,The Problem of Local Optima,Yuanqing Lin Interview
Hyperparameter Tuning, Batch Normalization and Programming Frameworks: Tuning Process,Using an Appropriate Scale to pick Hyperparameters,Hyperparameters Tuning in Practice: Pandas vs. Caviar,Normalizing Activations in a Network,Fitting Batch Norm into a Neural Network,Why does Batch Norm work?,Batch Norm at Test Time,Softmax Regression,Training a Softmax Classifier,Deep Learning Frameworks,TensorFlow |
Psychological First Aid | 1. Introduction
2. Reflective Listening/Rapport
3. Assessment and Prioritization
4. Intervention and Disposition
5. Self-Care and Wrap-Up | Introduction: In this first week, we have some materials to get you oriented, a pre-course survey, two lectures on history and terms and concepts and a simulated look at PFA in action.
Reflective Listening/Rapport: This week, we'll be looking more closely at the R component of our RAPID model.
Assessment and Prioritization: This week, we'll be looking more closely at the A and P components of our RAPID model. A stands for Assessment, and P stands for Prioritization.
Intervention and Disposition: This week, we'll be looking more closely at the I and D components of our RAPID model in Lectures 7 and 8, respectively. I stands for Intervention, and D stands for Disposition.
Self-Care and Wrap-Up: Now that we've gone through the entire RAPID model, we'll turn our intention to you, the provider. | Introduction: Module 1 Introduction,Lecture 1: Terms and Concepts,Lecture 2: Historical Context,Full simulation video
Reflective Listening/Rapport: Module 2 Introduction,Lecture 3: Reflective Listening & Rapport,Lecture 4: How Reflective Listening Works,Reflective Listening & Rapport Vignette A,Reflective Listening & Rapport Vignette B
Assessment and Prioritization: Module 3 Introduction,Lecture 5: Assessment of Needs,Assessment Vignette A,Assessment Vignette B,Module 4 Introduction,Lecture 6: Prioritization,Beyond the Ashes,Prioritization Vignette A,Prioritization Vignette B
Intervention and Disposition: Module 5 Introduction,Lecture 7: Intervention,Intervention Vignette A,Intervention Vignette B,Module 6 Introduction,Lecture 8: Disposition,Disposition Vignette A,Disposition Vignette B,Follow-Up Vignette
Self-Care and Wrap-Up: Module 7 Introduction,Lecture 9: Self-Care,Lecture 10: Summary,Closing Remarks |
Share Data Through the Art of Visualization | 1. Visualize data
2. Create data visualizations with Tableau
3. Craft data stories
4. Develop presentations and slideshows | Visualize data: In this module, you’ll delve into the various types of data visualizations and explore what makes an effective visualization. You'll also learn about accessibility, design thinking, and other factors that will help you use data visualizations to effectively communicate data insights.
Create data visualizations with Tableau: Tableau is a business intelligence and analytics platform that helps people visualize, understand, and make decisions with data. In this part of the course, you’ll become well-versed in Tableau’s dynamic capabilities and learn to inject creativity and clarity into your visualizations, ensuring that your findings are easy to understand.
Craft data stories: Connecting your objective with your data through insights is essential to data storytelling. In this part of the course, you’ll get acquainted with the principles of data-driven storytelling and learn to craft compelling narratives using Tableau's dashboard and filtering capabilities, giving life to your data insights.
Develop presentations and slideshows: In this part of the course, you’ll discover how to give an effective presentation about your data analysis. This final module teaches you to construct insightful presentations that resonate with your audience. You'll learn to anticipate and address potential questions and to articulate the limitations of your data, ensuring a robust and credible narrative for your stakeholders. | Visualize data: Introduction to communicating data insights,Kevin: The power's in the data viz,Why data visualization matters,Connect images with data,A recipe for a powerful visualization,Dynamic visualizations,Elements of art,Data visualization impact,Design thinking and visualizations,Accessible visualizations,Andrew: Making data accessible
Create data visualizations with Tableau: Data visualizations with Tableau,Tableau Public and other online tools,Meet Tableau,Create a data visualization in Tableau,Optimize the color palette in data visualization,Get creative,Link multiple datasets in Tableau
Craft data stories: Craft stories with data,Bring ideas to life,Speak to your audience,Carolyn: Data journalism,Tableau dashboard basics,From filters to charts,Compelling presentation tips,Share a narrative,Sundas: How to manage imposter syndrome
Develop presentations and slideshows: Pull it all together,Present with a framework,Weave data into your presentation,Brittany: Presentation skills for new data analysts,Connor: Messy example of a data presentation,Connor: Good example of a data presentation,Proven presentation tips,Present like a pro,Anticipate the question,Handle objections,Q&A best practices,Connor: Becoming an expert data translator,Congratulations! Course wrap-up |
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