Building Production RAG & LLM Systems
Architect enterprise Retrieval Augmented Generation systems. Master tokenization, vector databases (ChromaDB, Pinecone), hybrid search, and autonomous agents.
Course Overview
Build What Companies Are Actively Hiring For
Generative AI is only as useful as the private enterprise data it can reliably access. In this hands-on course, you’ll construct full-stack RAG systems with verified citations, low latency, and zero hallucinations.
Key Competencies You'll Build
Course Curriculum
3 chapters • 7 total lessons & checkpoints
Learning Path & Prerequisite Graph
How this course connects to your end-to-end engineering career.
Dense Embeddings & Chunking
In ProgressContext windows, semantic chunking algorithms, and token budgeting.
Vector Indexing & HNSW
In ProgressPinecone, ChromaDB, hybrid BM25 + dense search, and reciprocal rank fusion.
Autonomous LLM Agents
In ProgressTool binding, plan-and-solve loops, structured outputs, and evaluation.
Applied Deep Learning & Fine-Tuning
Next UpLoRA, QLoRA, parameter-efficient fine-tuning, and DPO alignment.
Explore specializationFrontier AI Roadmap
Next UpExplore full artificial intelligence career competencies.
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