GenAI + RAG Agents (DS Lite)
DS-sequel lite GenAI: prompting + structured extraction, embeddings and vector retrieval, RAG architecture with citation-required evals, and a single-agent tool-calling loop. Caps in a live RAG chatbot with an eval set and cost/latency dashboard. LangGraph/multi-agent stays out of scope (track 95).
4 weeks
5 modules, 18 lessons
0
~4 hours
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Course Curriculum
M0 — Prompting + LLM APIsFREE PREVIEW
Structured extraction, grounding/refusal drills, OpenAI-compatible wrapper with OSS fallback and cost/latency logging.
M1 — Embeddings + RetrievalFREE PREVIEW
Embedding dims compared, 2x2 chunking benchmark with P@K/Recall/MRR, FAISS-local-first stores.
M2 — RAG Architecture + EvalsFREE PREVIEW
RAG vs fine-tune trade-offs, citation/faithfulness evals with judge-bias guards, eval-set authoring.
M3 — Tool-Calling Lite + CapstoneFREE PREVIEW
Single-agent function-call loop, 20Q agent golden suite, live RAG demo with eval report + cost dashboard.
Capstone: RAG Chatbot Brief — Messy Business Corpus (Plan 96 Sec 4)FREE PREVIEW
Lesson home for the unpublished RAG chatbot brief; course stays unpublished.
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