Beyond RAG: Building AI Agents That Think, Plan, and Act
Beyond RAG: Building AI Agents That Think, Plan, and Act
COM SCI 751.05
Agentic RAG expands traditional retrieval by enabling AI to reason, plan workflows, self‑correct, and take action, teaching participants to build autonomous, data‑grounded AI agents for real‑world tasks.
Duration
As few as 1 day
Units
0.0
Current Formats
Live Online
Cost
$0
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What You Can Learn.
What You Can Learn.
Design and Build Agentic RAG Systems: Learn how to build AI systems that don't just retrieve information but reason over it, plan multi-step research, use external tools, and self-correct when the first answer isn't good enough.
Build Multi-Agent AI Applications: Learn how to create systems where multiple AI agents work together to break down complex questions, research independently, and combine their findings into accurate, grounded answers.
Take Agentic AI from Prototype to Production: Learn how to evaluate agent quality, manage costs, add safety guardrails, and set up monitoring so your agentic systems are reliable and ready for real users.
Master Modern Retrieval Strategies: Learn how to go beyond basic search by combining multiple retrieval approaches and letting the AI decide which strategy to use based on the complexity of each question.
About This Course
This course explores the evolution from traditional retrieval‑augmented generation (RAG) to agentic RAG systems that can reason, plan multi‑step workflows, and take action. Participants will learn how to move beyond basic document retrieval to build autonomous AI agents capable of searching, analyzing, self‑correcting, and orchestrating tools, all grounded in real‑world data.
Spring 2026 Schedule
Date
Details
Format
Thursday 12:00PM - 1:00PM PT
REG#
409361
Live Online
UCLA X Open
Schedule
Type
Date
Time
Location
Discussion
Thu May 14, 2026
12:00PM PT - 1:00PM PT
UCLA X Open