Microsoft Generative AI for Beginners Project Details

Project Overview

Microsoft Generative AI for Beginners is a comprehensive 21-lesson course created by Microsoft Cloud Advocates. This open-source project aims to help beginners master the fundamentals of building generative AI applications.

Project Features

Course Structure

• 21 Complete Lessons: Each lesson covers an independent topic, allowing learners to start anywhere.
• Course Type Classification:
  • "Learn" Lessons: Explain generative AI concepts.
  • "Build" Lessons: Combine conceptual explanations with code examples.

Programming Language Support

• Python: Primary programming language.
• TypeScript: Corresponding code examples are provided.
• Multi-Platform Support:
  • Universal Version (Python/TypeScript)
  • .NET Version (Specifically designed for .NET developers)
  • JavaScript Version

Technology Platform Integration

The course supports various AI service platforms:

• Azure OpenAI Service: Microsoft Azure's OpenAI service.
• GitHub Marketplace Model Catalog: GitHub model catalog.
• OpenAI API: OpenAI official API.

Complete Course Outline

Lesson Number	Lesson Name	Lesson Description	Video Resource
00	Course Setup	Setting up the course environment	✓
01	Introduction to Generative AI and LLMs	Introduction to Generative AI and Large Language Models	✓
02	Exploring and comparing different LLMs	Exploring and comparing different Large Language Models	✓
03	Using Generative AI Responsibly	Using Generative AI Responsibly	✓
04	Understanding Prompt Engineering Fundamentals	Understanding Prompt Engineering Fundamentals	✓
05	Creating Advanced Prompts	Creating Advanced Prompts	✓
06	Building Text Generation Applications	Building Text Generation Applications	✓
07	Building Chat Applications	Building Chat Applications	✓
08	Building Search Apps Vector Databases	Building Search Apps and Vector Databases	✓
09	Building Image Generation Applications	Building Image Generation Applications	✓
10	Building Low Code AI Applications	Building Low Code AI Applications	✓
11	Integrating External Applications with Function Calling	Integrating External Applications with Function Calling	✓
12	Designing UX for AI Applications	Designing UX for AI Applications	✓
13	Securing Your Generative AI Applications	Securing Your Generative AI Applications	✓
14	The Generative AI Application Lifecycle	The Generative AI Application Lifecycle	✓
15	Retrieval Augmented Generation (RAG) and Vector Databases	Retrieval Augmented Generation (RAG) and Vector Databases	✓
16	Open Source Models and Hugging Face	Open Source Models and Hugging Face	✓
17	AI Agents	AI Agents	✓
18	Fine-Tuning LLMs	Fine-Tuning LLMs	✓
19	Building with SLMs	Building with Small Language Models	-
20	Building with Mistral Models	Building with Mistral Models	-
21	Building with Meta Models	Building with Meta Models	-

Learning Resources

Each Lesson Includes

• Video Introduction: A short video introduction to the topic.
• Text Tutorial: A detailed written lesson in the README.
• Code Examples: Python and TypeScript code samples supporting Azure OpenAI and OpenAI API.
• Further Learning: Links to additional resources for continued learning.

Prerequisites

• Programming Fundamentals: Basic knowledge of Python or TypeScript is helpful.
• GitHub Account: Required to fork the entire repository to your own GitHub account.
• Development Environment: Course setup guides are provided to help configure the development environment.

Support Resources

• Official Discord Server: Communicate with other learners and get support.
• GitHub Discussions: Ask questions and provide suggestions.
• Free Resources: Microsoft for Startups Founders Hub provides free OpenAI credits and Azure credits.

Target Audience

• Beginners interested in generative AI.
• Developers who want to learn how to build AI applications.
• Technical personnel who want to understand different AI models and platforms.
• Product managers interested in AI product design and user experience.

Project Advantages

1. Authoritative: Created and maintained by the official Microsoft team.
2. Practical: Combines theory and practice, with each lesson including practical code examples.
3. Comprehensive: Covers a complete learning path from basic concepts to advanced applications.
4. Open Source: Completely open source, free to use and contribute.
5. Multi-Platform: Supports multiple programming languages and AI service platforms.
6. Continuously Updated: Actively maintained and updated by the community.

Related Course Series

Microsoft also offers other related learning resources:

• AI Agents for Beginners
• ML for Beginners
• Data Science for Beginners
• AI for Beginners
• Cybersecurity for Beginners