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NVIDIA

nvidia.com
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coursesFreeintermediate2hAi Agents Workflow Automation
DevelopersAI EngineersData Scientists
Learn to build Retrieval-Augmented Generation (RAG) agents with LLMs using LangChain and LlamaIndex for domain-specific knowledge.

Overview

This NVIDIA DLI course teaches how to construct powerful Retrieval-Augmented Generation (RAG) agents, enabling Large Language Models (LLMs) to access and utilize domain-specific information. Students will gain practical skills using popular frameworks like LangChain and LlamaIndex to build agents capable of interacting with various tools, parsing diverse data types, and delivering accurate, context-aware responses. The course covers core RAG components, advanced agent architectures, and multi-step reasoning. Ideal for developers and data scientists with Python, LLM, and basic machine learning knowledge.

Instructor

Rishabh Singh

Senior Developer Evangelist at NVIDIA

Rishabh Singh is a Senior Developer Evangelist at NVIDIA, specializing in educating developers on AI and machine learning technologies. He focuses on bridging the gap between complex research and practical application.

Learning Outcomes

  • Understand core RAG components like embedding models and vector databases.
  • Build RAG agents effectively using LangChain and LlamaIndex frameworks.
  • Integrate external tools to enhance agent capabilities and interactions.
  • Develop agents with multi-step reasoning for complex query resolution.
  • Apply RAG techniques to provide accurate, domain-specific responses.
  • Design scalable RAG solutions for real-world LLM applications.