21 Lessons teaching everything you need to know to start building Generative AI applications 🌐 Multi-Language Support Supported via GitHub Action (Automated & Always Up-to-Date) Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | Chinese (Traditional, Taiwan) | Croatian | Czech | Danish | Dutch | Estonian | Finnish | French | German | Greek | Hebrew | Hindi | Hungarian | Indonesian | Italian | Japanese | Korean | Lithuanian | Malay | Marathi | Nepali | Norwegian | Persian (Farsi) | Polish | Portuguese (Brazil) | Portuguese (Portugal) | Punjabi (Gurmukhi) | Romanian | Russian | Serbian (Cyrillic) | Slovak | Slovenian | Spanish | Swahili | Swedish | Tagalog (Filipino) | Tamil | Thai | Turkish | Ukrainian | Urdu | Vietnamese Generative AI for Beginners (Version 3) - A Course Learn the fundamentals of building Generative AI applications with our 21-lesson comprehensive course by Microsoft Cloud Advocates. 🌱 Getting Started This course has 21 lessons. Each lesson covers its own topic so start wherever you 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. For .NET Developers checkout Generative AI for Beginners (.NET Edition)! Each lesson also includes a "Keep Learning" section with additional learning tools. What You Need To run the code of this course, you can use either: Azure OpenAI Service - Lessons: "aoai-assignment" GitHub Marketplace Model Catalog - Lessons: "githubmodels" OpenAI API - Lessons: "oai-assignment" Basic knowledge of Python or TypeScript is helpful - *For absolute beginners check out these TypeScript courses A GitHub account to fork this entire repo to your own GitHub account We have created a Course Setup lesson to help you with setting up your development environment. Don't forget to 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. 🗣️ Meet Other Learners, Get Support Join our official Azure AI Foundry Discord server to meet and network with other learners taking this course and get support. Ask questions or share product feedback in our Azure AI Foundry Developer Forum on Github. 🚀 Building a Startup? Visit Microsoft for Startups to find out how to get started building with Azure credits today. 🙏 Want to help? Do you have suggestions or found spelling or code errors? Create a pull request 📂 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 🗃️ Lessons # Lesson Link Description Video Extra Learning 00 Course Setup Learn: How to Setup Your Development Environment Video Coming Soon Learn More 01 Introduction to Generative AI and LLMs Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work. Video Learn More 02 Exploring and comparing different LLMs Learn: How to select the right model for your use case Video Learn More 03 Using Generative AI Responsibly Learn: How to build Generative AI Applications responsibly Video Learn More 04 Understanding Prompt Engineering Fundamentals Learn: Hands-on Prompt Engineering Best Practices Video Learn More 05 Creating Advanced Prompts Learn: How to apply prompt engineering techniques that improve the outcome of your prompts. Video Learn More 06 Building Text Generation Applications Build: A text generation app using Azure OpenAI / OpenAI API Video Learn More 07 Building Chat Applications Build: Techniques for efficiently building and integrating chat applications. Video Learn More 08 Building Search Apps Vector Databases Build: A search application that uses Embeddings to search for data. Video Learn More 09 Building Image Generation Applications Build: An image generation application Video Learn More 10 Building Low Code AI Applications Build: A Generative AI application using Low Code tools Video Learn More 11 Integrating External Applications with Function Calling Build: What is function calling and its use cases for applications Video Learn More 12 Designing UX for AI Applications Learn: How to apply UX design principles when developing Generative AI Applications Video Learn More 13 Securing Your Generative AI Applications Learn: The threats and risks to AI systems and methods to secure these systems. Video Learn More 14 The Generative AI Application Lifecycle Learn: The tools and metrics to manage the LLM Lifecycle and LLMOps Video Learn More 15 Retrieval Augmented Generation (RAG) and Vector Databases Build: An application using a RAG Framework to retrieve embeddings from a Vector Databases Video Learn More 16 Open Source Models and Hugging Face Build: An application using open source models available on Hugging Face Video Learn More 17 AI Agents Build: An application using an AI Agent Framework Video Learn More 18 Fine-Tuning LLMs Learn: The what, why and how of fine-tuning LLMs Video Learn More 19 Building with SLMs Learn: The benefits of building with Small Language Models Video Coming Soon Learn More 20 Building with Mistral Models Learn: The features and differences of the Mistral Family Models Video Coming Soon Learn More 21 Building with Meta Models Learn: The features and differences of the Meta Family Models Video Coming Soon Learn More 🌟 Special thanks Special thanks to John Aziz for creating all of the GitHub Actions and workflows Bernhard Merkle for making key contributions to each lesson to improve the learner and code experience. 🎒 Other Courses Our team produces other courses! Check out: Azure / Edge / MCP / Agents Generative AI Series Core Learning Copilot Series Getting Help If you get stuck or have any questions about building AI apps. Join fellow learners and experienced developers in discussions about MCP. It's a supportive community where questions are welcome and knowledge is shared freely. If you have product feedback or errors while building visit: