Generative AI course syllabus
Follow the lessons in order — each one builds on the last. Tick them off as you go.
- What Is Generative AI? A Beginner’s Guide What generative AI is, how it differs from traditional AI, real-world use cases, and the skills students need to work with GenAI. 4 min
- How Generative Models Work Autoregressive models, diffusion, GANs and VAEs explained simply — what each family generates and why LLMs and diffusion won. 4 min
- Diffusion Models Explained How image generators like Stable Diffusion turn noise into pictures: forward and reverse diffusion, latent space and text guidance. 4 min
- Multimodal AI: Text, Images & Audio How multimodal models understand images and audio alongside text, common use cases, and their current limitations. 4 min
- Build Your First Generative AI App in Python Call an LLM API from Python, write a solid system prompt, stream the answer, and handle errors — a complete beginner project. 4 min
- Generative AI Interview Questions Frequently asked generative AI interview questions — LLMs, diffusion, evaluation, cost and responsible AI — with answers. 4 min
Generative AI FAQ
Is this Generative AI tutorial free?
Yes. All 6 Generative AI lessons are free to read online with no sign-up. Each one includes working code examples you can copy and run.
Is Generative AI good for beginners?
Yes. The tutorial starts with "What Is Generative AI? A Beginner’s Guide" and builds up one concept at a time, so you don't need any prior Generative AI experience — just follow the lessons in order.
How long does it take to learn Generative AI?
Reading all 6 lessons takes about 1 hour. Most learners need a few weeks of hands-on practice alongside the lessons to feel confident using Generative AI on real projects.
What should I learn after Generative AI?
Good next topics are Artificial Intelligence, AI Agents, Deep Learning, LLM Fine-Tuning. The AI Engineer Roadmap shows the full order.