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DeepLearning.AI

Building Agentic RAG with LlamaIndex

  • up to 1 hour
  • Beginner

Learn how to build an agent that can reason over your documents and answer complex questions. This course will teach you to design and debug agents capable of intelligent navigation, summarization, and comparison of information across multiple documents.

  • Agentic RAG
  • Router agent design
  • Tool calling
  • Research assistant agent
  • Multi-document handling

Overview

Join our new short course and learn from Jerry Liu, co-founder and CEO at LlamaIndex, to start using agentic RAG, a framework designed to build research agents skilled in tool use, reasoning, and decision-making with your data. You will build various types of agents, including a router agent for Q&A and summarization tasks, and a research assistant agent capable of handling multiple documents. This course will enhance your ability to engage with and analyze your data comprehensively.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Python Enthusiasts

Anyone who has basic Python knowledge and wants to learn how to quickly build agents that can reason over their own documents.

AI Developers

Developers interested in building intelligent agents capable of reasoning, decision-making, and tool use with data.

Data Scientists

Data scientists looking to enhance their ability to engage with and analyze data comprehensively using agentic AI.

This course will teach you to build intelligent agents capable of reasoning over documents and answering complex questions. Ideal for Python enthusiasts, AI developers, and data scientists, it will enhance your ability to engage with and analyze data comprehensively.

Pre-Requisites

1 / 3

  • Basic Python knowledge

  • Interest in AI and machine learning

  • Familiarity with data analysis concepts

What will you learn?

Introduction to Agentic RAG
Learn the basics of agentic RAG and its applications in building intelligent agents.
Building a Router Agent
Create a simple router agent that can handle Q&A and summarization tasks over a single document.
Adding Tool Calling
Enhance your router agent by adding tool calling capabilities to execute functions with inferred arguments.
Designing a Research Assistant Agent
Develop a research assistant agent capable of reasoning over tools in multiple steps.
Handling Multiple Documents
Extend your research assistant agent to handle and analyze multiple documents.
Debugging Agents
Learn various techniques to debug and control the actions of your agents effectively.

Meet your instructor

  • Jerry Liu

    Co-founder/CEO, LlamaIndex

    Jerry Liu is the co-founder and CEO of LlamaIndex. He is passionate about making AI more accessible and democratized.

Upcoming cohorts

  • Dates

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Free