Production RAG with LangChain: Beginner to Advanced

About this course

Welcome to Production RAG with LangChain: Beginner to Advanced, your step-by-step masterclass for building high-performance, real-world AI applications powered by Retrieval-Augmented Generation (RAG).

LLMs are powerful, but they often struggle with hallucination, context limits, and accessing private data. This course equips you with the tools to solve these challenges using LangChain—the industry-standard framework for building context-aware AI systems.

What You Will LearnRAG Fundamentals: Understand what RAG is, why it is critical for enterprise LLM apps, and how the core architecture components interact.

Document Processing & Chunking Strategies: Solve the "context window" and "lost in the middle" problems using document loaders, custom text splitters, and optimal chunking strategies.

Vector Databases & Vector Search: Master vector embeddings, vector databases, and the underlying mechanics of vector search algorithms.

Advanced Retrieval Techniques: Move beyond basic keyword searches with similarity-based retrievers, threshold-based retrievers, and custom advanced retrieval workflows.

Re-Ranking for Accuracy: Implement advanced re-ranking strategies to ensure your model always gets the most relevant context.

Full-Stack End-to-End Hands-On Project: Build a complete RAG system from scratch—from document loading, chunking, and vector database initialization, to setting up advanced retrieval, context preparation, and constructing a frontend UI.What You'll Learn (Key Takeaways)Build end-to-end production-ready RAG applications using LangChain.

Implement document loading, text splitting, and custom chunking strategies.

Generate vector embeddings and manage vector database stores.

Read the full description on Udemy on Udemy (opens in a new tab)

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.