Hands-On Agentic AI: Building AI Agents with LlamaIndex

AI agents are quickly becoming popular for their ability to make decisions autonomously and then act upon them. In this hands-on interactive course for AI and ML engineers, instructor Kumaran Ponnambalam helps you get up to speed with agentic AI capabilities in LlamaIndex, the popular framework that provides several building blocks to quickly create and deploy AI agents with ease. Along the way, explore a variety of different agentic AI use cases with LlamaIndex to understand popular patterns in agentic AI and how to implement them successfully with LlamaIndex.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out “Using GitHub Codespaces" with this course to learn how to get started.

Learning objectives

• Explain the concepts and building blocks for agentic AI in LlamaIndex.
• Create an AI agent for reflection, routing, and tool use.
• Add query capabilities with retrieval-augmented generation (RAG) using LlamaIndex.
• Perform operations on external systems autonomously.
• Build multiagent systems with LlamaIndex.