RAG from Zero is a hands-on two-module course that teaches you to build production Retrieval-Augmented Generation pipelines in Rust by walking two real tools you can use the same day. Module 1 walks the encode-chunk-index-fuse-retrieve pipeline one stage at a time using the published aprender-rag crate — RecursiveChunker(512, 50) with overlap, MockEmbedder(384) for deterministic teaching with candle for production, reciprocal-rank fusion at k=60, and a closing aprender_film_search demo against a 50-row Sakila fixture that asserts four runtime contracts. Module 2 walks pmat query, a production code-search RAG that ranks by semantic intent plus pagerank plus structural signals — --churn (90-day git volatility), --duplicates (MinHash + Locality-Sensitive Hashing clones), --entropy (pattern diversity), --faults, and -G git-history fusion. The course closes with cross-project search across a sibling-repo workspace via --include-project and --include-source so you can navigate a multi-crate codebase as one indexed corpus. No toy fixtures, no aspirational APIs — aprender-rag is on crates.io today, pmat ships from paiml/pmat, and the companion paiml/rag-from-zero repo runs end-to-end with cargo run and zero infrastructure.