RAG Pipelines Mastery Path

A free, structured, module-wise training program on Retrieval-Augmented Generation (RAG) — entry level to master level, with runnable Python code in every module and a hands-on project at the end of each level. Taught from first principles in plain Python: sentence-transformers for local embeddings, chromadb for the vector store, and the Anthropic API for the generation step (any chat-completions API works the same way).

Live site: https://sigilipelli.github.io/rag-mastery-path/

Contents

• Level 1 · Entry — what RAG is, embeddings, chunking, vector stores, retrieval, grounded generation, a full end-to-end pipeline, evaluation, failure modes, and a docs Q&A bot project
• Level 2 · Intermediate — BM25 & hybrid search, reranking, query rewriting, structured/table RAG, multi-format ingestion, LangChain & LlamaIndex
• Level 3 · Advanced — agentic RAG, multi-hop retrieval, GraphRAG, production vector databases, evaluation at scale, observability
• Level 4 · Master — enterprise architecture, multi-tenant systems, cost/latency optimization, RAG security, governance

Local development

python3 -m venv .venv
.venv/bin/pip install mkdocs-material
.venv/bin/python -m mkdocs serve

Related

Sister tracks in the same wave:

• AI/ML Mastery Path
• LLM Development Mastery Path

The full Mastery Path series:

• Python Mastery Path
• Java Mastery Path
• JavaScript Mastery Path
• Shell Mastery Path
• C Mastery Path
• C++ Mastery Path
• Go Mastery Path
• SQL Mastery Path
• Rust Mastery Path
• TypeScript Mastery Path
• Ruby Mastery Path
• PHP Mastery Path
• Swift Mastery Path
• Kotlin Mastery Path
• Scala Mastery Path
• Dart Mastery Path
• PowerShell Mastery Path
• R Mastery Path
• AWS Mastery Path
• Azure Mastery Path
• GCP Mastery Path
• IBM Cloud Mastery Path
• Adobe Creative Cloud Mastery Path