Welcome to Few-Shot Academy
A free, open-source, chapter-wise curriculum for Generative AI, LLMs, Vector Databases, RAG, and Agents — from "what is a token?" to a working, evaluated agentic RAG system.
Why this exists
Generative AI is exploding, but most learning paths force a tradeoff: either shallow, video-only "for everyone" content with no hands-on practice, or hands-on labs that assume you already know how to code and are willing to pay for cloud credits. Few-Shot Academy is neither. It's:
- Truly beginner-friendly — Foundations assumes zero prior AI knowledge.
- Hands-on at every step — every lesson links to runnable code you execute on your own machine.
- Local-first and free — vector storage runs locally via ChromaDB, and every Foundations/Intermediate lab works with a free local Ollama model. No credit card required to finish the first two tracks. Prefer a hosted model? Bring your own OpenAI or Anthropic API key instead.
- One coherent arc — three tracks, each building on the last, ending with you having built and evaluated a real agentic RAG system.
How the curriculum is organized
- Foundations — start here if you're new to AI.
- Intermediate — chunking, retrieval quality, tool use, your first agent.
- Advanced — multi-agent systems, advanced RAG, guardrails, observability, shipping to production.
Every chapter follows the same shape: Concept → Diagram → Hands-on Lab → Checkpoint → What's Next. Each chapter links to that track's labs ZIP. Download it once, and you're set up for every lab in that track, no git required.
What you'll walk away with
Each track ends with something you actually built, not just read about:
- Foundations → a working Q&A bot that answers questions over your own documents, using retrieval-augmented generation you understand piece by piece.
- Intermediate → a tool-calling assistant, then a multi-tool agent that combines web search, a calculator, and RAG over your own documents, plus the ability to judge whether a RAG or agent system is actually working, not just build one.
- Advanced → a production-shaped agentic RAG system with evaluation, guardrails, and observability built in, packaged the way a real system would ship.
Whichever track you land on, you'll finish it having built something real, not just read about it.