Unit 2 of the Build AI Agents with Python course — an introduction to LlamaIndex. This short overview sets up the next arc of the series: what LlamaIndex is, the key parts you’ll use (documents, indexes, query engines and agents), and what makes it different from the tools we used in Unit 1.
If you’ve finished Unit 1, this tells you exactly what’s coming next and how LlamaIndex fits into building RAG-powered AI agents.
WHAT YOU’LL COVER
• What LlamaIndex is: a toolkit for LLM apps over your data
• RAG agents and query engines explained
• Key parts: documents, indexes, query engines, agents
• What makes LlamaIndex special: structured agentic workflows
• What’s next in Unit 2
FULL COURSE (playlist)
Code
https://github.com/KNehe/ai_agents
OpenAI Billing
https://platform.openai.com/settings/organization/billing/overview
LLM hardware requirements
https://runthisllm.com/
source