An AI agents and automation bootcamp using LangChain and RAG teaches developers to build autonomous AI systems capable of completing multi-step tasks, using the LangChain framework to structure application logic and RAG techniques to connect AI models to real, external data sources.

Yes. Building with LangChain and implementing RAG pipelines requires an existing programming background, typically in Python. These are code-based frameworks intended for developers rather than non-technical learners.

RAG is a technique that connects an AI language model to external data sources, allowing it to retrieve relevant, current information and use it to generate accurate responses grounded in real data, rather than relying solely on the model's original training knowledge.

Building AI agents with LangChain involves writing code to structure application logic, manage memory, and orchestrate multi-step processes, offering more flexibility and control than no-code automation tools, which use visual interfaces rather than programming.

Software developers, machine learning engineers, and technical consultants specialising in applied AI development benefit most from these skills, as demand for developers who can build and deploy production-ready AI agent systems continues to significantly outpace supply.