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Retrieval-Augmented Generation with LangChain

Intermediate2 hr

Learn to build knowledge-grounded LLM applications that retrieve relevant information from structured and unstructured sources before generating responses.

Python1 hr - 3 hr3,500 XPStatement of accomplishment

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1

Retrieval-Augmented Generation

  • Structured Retrieval

    You will learn to build SQL-grounded RAG systems that convert natural language questions into valid SQL queries, validate them safely, execute them against databases, and synthesize results into accurate LLM responses — enabling you to unlock insights from relational data without requiring domain experts to write queries.

  • Semantic Retrieval

    You will learn to build semantic RAG systems that retrieve relevant information from unstructured documents using embeddings and vector databases — from preprocessing documents into searchable chunks to implementing real-time semantic search and response generation — enabling you to unlock insights from the majority of enterprise data that exists as documents and free-form text.

Retrieval-Augmented Generation with LangChain

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