Context Engineering with DSPy - Comprehensive Hands-On Course for Building LLM Applications

Master Context Engineering through this comprehensive hands-on tutorial that demonstrates building powerful and reliable applications with Large Language Models using DSPy. Explore the art and science of structuring context to optimize LLM performance, starting with atomic prompts and progressing to complex systems including RAG, tool calling, and multi-agent architectures. Learn to programmatically construct sequential flows, conditional branching, parallel generation, and iterative refinement while monitoring DSPy programs with ML Flow and evaluating open-ended systems. Dive deep into Retrieval-Augmented Generation by comparing embedding-based retrieval with keyword-based retrieval like BM25, hybrid retrieval approaches, hypothetical document embeddings (HyDE), and multi-hop RAG search techniques. Discover memory systems and the Mem0 algorithm through practical implementation. The tutorial covers prompt engineering fundamentals, multi-agent prompt programs, comprehensive evaluation systems, tool calling mechanisms, and advanced RAG implementations across five detailed chapters spanning over an hour of in-depth instruction.