Build generative AI apps using RAG and LangChain to enhance LLM capabilities and retrieve relevant information effectively.
Overview
This hands-on project teaches you to develop robust generative AI applications by implementing Retrieval Augmented Generation (RAG) with the LangChain framework. You'll learn to integrate large language models (LLMs) with external data sources, retrieve contextually relevant information, and synthesize enhanced outputs. The course covers the complete lifecycle of building a RAG-based application, from data ingestion to user interaction. Ideal for developers and data scientists comfortable with Python programming and basic AI/ML concepts.
Instructor
IBM Skills Network
Learning Outcomes
Implement Retrieval Augmented Generation (RAG) using LangChain.
Develop generative AI applications that leverage LLMs with external data.
Integrate large language models with diverse data sources using LangChain.
Enhance LLM outputs by providing contextually relevant information through RAG.