RAG learning path

RAG roadmap — from concepts to working pipeline

For developers and students who read about vector RAG, hybrid search, or fine-tuning but want to build something reliable. This path links our free guides to live mentorship when implementation gets hard.

  1. Phase 1: Foundations

    • What RAG is and when to use it
    • Python + basic ML intuition
    • Prompting vs retrieval
    RAG for beginners →Python prerequisites →

  2. Phase 2: Build a first pipeline

    • Ingest documents
    • Chunk and embed
    • Simple Q&A over your files
    Weekend RAG project guide →End-to-end RAG flow →

  3. Phase 3: Improve retrieval

    • Vector vs keyword search
    • Hybrid search & RRF
    • Re-ranking basics
    Hybrid search guide →

  4. Phase 4: Production habits

    • Evaluation and failure modes
    • Citations and safety
    • Agents & tool use (optional)
    RAG practice questions →Advanced AI mentorship →

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