Retrieval-Augmented Generation with LangChain

Course Overview

The Retrieval-Augmented Generation with LangChain course covers the core pipeline for augmenting Large Language Models with domain-specific knowledge. You will learn to load documents, generate vector embeddings, store them in vector databases, construct custom prompt templates, and perform context-aware document retrieval in Python.

Who Is This Course For?

Intermediate developers, AI practitioners, and data scientists seeking to build knowledge-grounded LLM applications using the LangChain framework.

Key Takeaways

• Connect external knowledge bases to Large Language Models using LangChain.
• Load, chunk, and embed unstructured text documents for vector search.
• Store and query high-dimensional embeddings using vector databases.
• Design customized prompt templates and retrieval chains for accurate responses.