TL;DR: Generative AI for Beginners is Microsoft's free 21-lesson course on GitHub — learn to build generative AI applications from scratch with hands-on Python labs, covering everything from prompt engineering to RAG and AI agents.
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The AI Skills Gap
A 2025 LinkedIn report found that "AI skills" are the most in-demand skills globally, with a 3x increase in AI-related job postings year over year. Yet 65% of professionals report they lack confidence in building AI applications. Microsoft's free course directly addresses this gap with a structured, practical curriculum that takes you from zero to building functional AI apps.
What is Generative AI for Beginners?
Generative AI for Beginners is an open-source course created by Microsoft's Cloud Advocacy team, hosted on GitHub. It consists of 21 lessons covering the fundamentals of building generative AI applications using Python, Azure OpenAI, and the OpenAI API. Each lesson includes written content, video explanations, and hands-on coding exercises. The course has been starred by 70,000+ developers on GitHub.
Getting Started
Step 1: Access the Course
- Visit Generative AI for Beginners on GitHub
- Star the repo and clone it locally for the best experience
- No enrollment or payment needed — start immediately
Step 2: Follow the Curriculum
- Work through lessons sequentially — each builds on the previous
- Run the Python labs in VS Code or GitHub Codespaces
- Complete the challenges at the end of each lesson
Core Features
Curriculum Overview
| Module | Topics | Lessons |
|---|---|---|
| Foundations | GenAI concepts, LLM basics, responsible AI | 1-3 |
| Prompt Engineering | Prompt design, few-shot, chain-of-thought | 4-6 |
| Building Apps | Text generation, chat, search applications | 7-11 |
| Image & Code | Image generation, code generation with AI | 12-14 |
| Advanced | RAG, fine-tuning, AI agents, function calling | 15-19 |
| Deployment | Securing, deploying, and monitoring AI apps | 20-21 |
Learning Resources per Lesson
- Written lesson with concepts and examples
- Short video walkthrough (5-15 minutes)
- Hands-on Python lab notebook
- Challenge exercise with solution
- Additional reading and references
Real-World Use Cases
Career Changer: Breaking into AI
A web developer transitions into AI engineering by completing the course over 4 weeks, building a portfolio of AI projects including a RAG chatbot and an AI-powered content generator.
University Professor: Course Material
A CS professor adopts the course as supplementary material for their AI class, having students complete the labs as homework assignments.
Tips for Best Results
- Prerequisites: basic Python and familiarity with APIs. No ML background needed
- Use GitHub Codespaces for zero-setup — runs everything in the browser
- Do every lab exercise, not just read the theory
- Join the GitHub Discussions for help with exercises and to connect with other learners
- Budget 2-3 hours per lesson for thorough understanding
Pricing
The course is completely free and open-source under MIT license. You only need an OpenAI API key (free tier available) or Azure OpenAI access for the hands-on labs.
Try Generative AI for Beginners
Ready to learn generative AI development? Visit Generative AI for Beginners to start the course, or explore Generative AI for Beginners details, alternatives & reviews for ratings and alternatives.
FAQs
Do I need ML experience?
No. The course is designed for beginners with basic Python skills. It teaches generative AI application development, not ML research — you learn to use APIs and build apps, not train models from scratch.
How long does the course take?
At 2-3 hours per lesson, the 21 lessons can be completed in 4-6 weeks of part-time study. Many learners finish in 2-3 weeks at a more intensive pace.
Is there a certificate?
The GitHub course itself does not issue certificates. However, Microsoft Learn offers a related learning path that includes a completion certificate.
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Last updated: February 2026
