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Generative AI For Beginners

18 Lessons 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

Generative AI for Beginners (Version 2) - A Course

Learn the fundamentals of building Generative AI applications with our 18-lesson comprehensive course by Microsoft Cloud Advocates.

🌱 Getting Started

This course is 18 lessons. Each lesson covers its own topic so start wherever you would like!

Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both Python and TypeScript when possible.

Each lesson also includes a "Keep Learning" section with additional learning tools.

What You Need

We have created a Course Setup lesson to help you with setting up your developement environment.

Don't forget to star star (🌟) this repo to find it easier later.

🧠 Ready to Deploy?

If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both Python and TypeScript.

πŸ—£οΈ Meet Other Learners, Get Support

Join our official AI Discord server to meet and network with other learners taking this course and get support.

πŸš€ Building a Startup?

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?

Find spelling errors, code errors or have a suggestion? Raise an issue or Create a pull request

πŸ“‚ Each lesson includes:

  • A short video introduction to the topic
  • A written lesson located in the README
  • Python and TypeScript Code Samples supporting Azure OpenAI and OpenAI API
  • Links to extra resources to continue your learning

πŸ—ƒοΈ Lessons

Lesson Link Description Additional Learning
00 Course Setup Learn: How to Setup Your Development Environment Learn More
01 Introduction to Generative AI and LLMs Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work. Learn More
02 Exploring and comparing different LLMs Learn: How to select the right model for your use case Learn More
03 Using Generative AI Responsibly Learn: How to build Generative AI Applications responsibly Learn More
04 Understanding Prompt Engineering Fundamentals Learn: Hands-on Prompt Engineering Best Practices Learn More
05 Creating Advanced Prompts Learn: How to apply prompt engineering techniques that improve the outcome of your prompts. Learn More
06 Building Text Generation Applications Build: A text generation app using Azure OpenAI Learn More
07 Building Chat Applications Build: Techniques for efficiently building and integrating chat applications. Learn More
08 Building Search Apps Vector Databases Build: A search application that uses Embeddings to search for data. Learn More
09 Building Image Generation Applications Build: A image generation application Learn More
10 Building Low Code AI Applications Build: A Generative AI application using Low Code tools Learn More
11 Integrating External Applications with Function Calling Build: What is function calling and its use cases for applications Learn More
12 Designing UX for AI Applications Learn: How to apply UX design principles when developing Generative AI Applications Learn More
13 Securing Your Generative AI Applications Learn: The threats and risks to AI systems and methods to secure these systems. Learn More
14 The Generative AI Application Lifecycle Learn: The tools and metrics to manage the LLM Lifecycle and LLMOps Learn More
15 Retrieval Augmented Generation (RAG) and Vector Databases Build: An application using a RAG Framework to retrieve embeddings from a Vector Databases Learn More
16 Open Source Models and Hugging Face Build: An application using open source models available on Hugging Face Learn More
17 AI Agents Build: An application using an AI Agent Framework Learn More
18 Fine-Tuning LLMs Learn: The what, why and how of fine-tuning LLMs Learn More

🌟 Special thanks

Special thanks to John Aziz for creating all of the GitHub Actions and workflows

πŸŽ’ Other Courses

Our team produces other courses! Check out:

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  • Jupyter Notebook 85.0%
  • Python 11.2%
  • TypeScript 2.1%
  • Other 1.7%