Microsoft Releases a 21-Lesson Course for Generative AI

There are plenty of people who make and sell AI courses these days. You don’t have to pay a penny to get some education in this field. Microsoft has released a 21-lesson course that covers everything you need to learn about open source models, AI agents, LLM fine-tuning, and SLM and Meta models. Here is what’s covered:

1. Introduction to Generative AI and LLMs Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work.
2. Exploring and comparing different LLMs Learn: How to select the right model for your use case
3. Using Generative AI Responsibly Learn: How to build Generative AI Applications responsibly
4. Understanding Prompt Engineering Fundamentals Learn: Hands-on Prompt Engineering Best Practices
5. Creating Advanced Prompts Learn: How to apply prompt engineering techniques that improve the outcome of your prompts
6. Building Text Generation Applications Build: A text generation app using Azure OpenAI / OpenAI API
7. Building Chat Applications Build: Techniques for efficiently building and integrating chat applications. 
8. Building Search Apps Vector Databases Build: A search application that uses Embeddings to search for data. 
9. Building Image Generation Applications Build: An image generation application
10. Building Low Code AI Applications Build: A Generative AI application using Low Code tools
11. Integrating External Applications with Function Calling Build: What is function calling and its use cases for applications
12. Designing UX for AI Applications Learn: How to apply UX design principles when developing Generative AI Applications
13. Securing Your Generative AI Applications Learn: The threats and risks to AI systems and methods to secure these systems
14. The Generative AI Application Lifecycle Learn: The tools and metrics to manage the LLM Lifecycle and LLMOps 
15. Retrieval Augmented Generation (RAG) and Vector Databases Build: An application using a RAG Framework to retrieve embeddings from a Vector Databases
16. Open Source Models and Hugging Face Build: An application using open source models available on Hugging Face
17. AI Agents Build: An application using an AI Agent Framework
18. Fine-Tuning LLMs Learn: The what, why and how of fine-tuning LLMs
19. Building with SLMs Learn: The benefits of building with Small Language Models
20. Building with Mistral Models Learn: The features and differences of the Mistral Family Models
21. Building with Meta Models – The features and differences of the Meta Family Models

The course comes with learn and build lessons, with Python and TypeScript code examples.

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