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Building RAG Agents with LLMs (self-paced)

Building RAG Agents with LLMs is a self-paced NVIDIA course on deploying agent systems that retrieve from documents and use tools, built so they can scale to the demands of real users. You implement and evaluate a RAG agent without any fine-tuning.

Open at NVIDIA ↗Common questions

Who it suits

  • Developers who want to deploy LLM agents that retrieve information and manage dialogue.
  • Teams that need to scale a retrieval-based system to meet user demand.

What it covers

  • Composing an LLM system that interacts predictably, using internal and external reasoning components.
  • Designing dialogue management and document reasoning that keeps state and produces structured formats.
  • Using embedding models for similarity queries, content retrieval and dialogue guardrails.
  • Implementing, modularising and evaluating a RAG agent that answers questions about research papers in its dataset.

Common questions about Building RAG Agents with LLMs (self-paced)

Does it require fine-tuning?
No. NVIDIA says the RAG agent you build answers questions about its dataset without any fine-tuning.
Does it cost anything?
NVIDIA sells the self-paced course with Buy Now and Redeem Code options, and says online purchase is supported in select locations. Its page states the price, which changes, so check it.
Is there an instructor-led version?
NVIDIA also offers an instructor-led workshop on the same subject, listed separately.

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Where this comes from

Written from NVIDIA’s own pages, read on 2026-10-13. Content, prices and availability change, so the provider’s page is the source. We are not affiliated with NVIDIA and this is not an endorsement.