RAG
This guided path takes learners on a hands-on journey through the world of Retrieval-Augmented Generation (RAG), from foundational concepts to building and evaluating real-world RAG systems. Students will explore key components like document chunking, embeddings, vector databases, and end-to-end pipeline construction using LangChain or LlamaIndex. By the end, they'll be equipped to build, optimize, and troubleshoot production-ready RAG applications with advanced retrieval techniques and robust evaluation strategies.
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