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Generative AI For Beginners

A 12 Lesson course teaching everything you need to know to start building Generative AI applications

GitHub license GitHub contributors GitHub issues GitHub pull-requests PRs Welcome

GitHub watchers GitHub forks GitHub stars

Open in GitHub Codespaces

Generative AI for Beginners - A Course

Learn the fundamentals of building Generative AI applications with our 12-lesson comprehensive course by Microsoft Cloud Advocates. Each lesson covers a key aspect of Generative AI principles and application development. Throughout this course, you will be building your own Generative AI startup so you can get an understanding of what it takes to launch your ideas.

🌟 Special thanks

To our Microsoft Student Ambassadors and community authors, reviewers, and content contributors including:

John Aziz - For creating all of the GitHub Actions and workflows

🌱 Getting Started

To get started, fork this entire repo to your own GitHub account to be able to change any code and complete the challenges. You can also star (🌟) this repo to find it easier later.

Below are the links to each lesson. Feel free to explore and start at any lesson that interests you the most!

Head to the Course Setup Page to find the setup guide that works best for you.

πŸ—£οΈ Meet Other Learners, Get Support

One of the best ways to learn is learning with others! Join our official AI Discord server to meet and network with other learners taking this course and get support. Who knows? You might find your next co-founder there!

🧠 Want to learn more?

After completing this course, check out our Generative AI Learning collection to continue levelling up your Generative AI knowledge!

πŸš€ Are you a startup or got an idea you want to launch?

Sign up for Microsoft for Startups Founders Hub to receive free OpenAI credits and up to $150k towards Azure credits to access OpenAI models through Azure OpenAI Services.

πŸ™ Want to help?

Here are ways you can contribute to this course:

  • Find spelling errors or code errors, Raise an issue or Create a pull request
  • Send us your ideas, maybe your ideas for new lessons or exercises, and let us know how we can improve.

πŸ“‚ Each lesson includes:

  • a short video introduction to the topic
  • a written lesson located in the README
  • a Jupyter Notebook with code examples (for project-based lessons)
  • a challenge or assignment to apply your learning
  • links to extra resources to continue your learning

πŸ—ƒοΈ Lessons

Lesson Link Concepts Taught Learning Goal
00 Course Introduction - How to Take This Course Tech setup and course structure Setting you up for success while learning in this course
01 Introduction to Generative AI and LLMs Concept: Generative AI and the current technology landscape Understanding what Generative AI is and how Large Language Models (LLMs) work.
02 Exploring and comparing different LLMs Concept: Testing, iterating, and comparing different Large Language Models Select the right model for your use case
03 Using Generative AI Responsibly Concept: Understanding the limitations of foundation models and the risks behind AI Learn how to build Generative AI Applications responsibly
04 Understanding Prompt Engineering Fundamentals Code/Concept: Hands-on application of Prompt Engineering Best Practices Understand prompt structure & usage
05 Creating Advanced Prompts Code/Concept: Extend your knowledge of prompt engineering by applying different techniques to your prompts Apply prompt engineering techniques that improve the outcome of your prompts.
06 Building Text Generation Applications Code: Build a text generation app using Azure OpenAI Understand how to efficiently use tokens and temperature to vary the model's output
07 Building Chat Applications Code: Techniques for efficiently building and integrating chat applications. Identify key metrics and considerations to effectively monitor and maintain the quality of AI-powered chat applications
08 Building Search Apps Vector Databases Code: Semantic vs Keyword search. Learn about text embeddings and how they apply to search Create an application that uses Embeddings to search for data.
09 Building Image Generation Applications Code: Image generation and why it's useful in building applications Build an image generation application
10 Building Low Code AI Applications Low Code: Introduction to Generative AI in Power Platform Build a Student Assignment Tracker App for our education startup with Low Code
11 Integrating External Applications with Function Calling Code: What is function calling and its use cases for applications Setup a function call to retrieve data from an external API
12 Designing UX for AI Applications Concept: Designing AI Applications for Trust and Transparency Apply UX design principles when developing Generative AI Applications
xx Continue Your Learning Links to continue your learning from each lesson! Mastering your Generative AI skills

πŸŽ’ Other Courses

Our team produces other courses! Check out:

About

12 Lessons, Get Started Building with Generative AI πŸ”— https://microsoft.github.io/generative-ai-for-beginners/

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  • Jupyter Notebook 77.1%
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  • JavaScript 2.2%
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