Public MOOC website: agenticai-learning.org/f25
Course website: rdi.berkeley.edu/agentic-ai/f25
Link to playlist on YouTube
(Note that lecture 04 on Agent Evaluation & Project Overview is not part of this playlist, link to the lecture recording can be found on the notes of the lecture)
| Lecture | Title | Speaker |
|---|---|---|
| 01 | LLM Agents Overview | Yann Dubois |
| 02 | Evolution of System Designs from an AI Engineer’s Perspective | Yangqing Jia |
| 03 | Post-Training Verifiable Agents | Jiantao Jiao |
| 04 | Agent Evaluation & Project Overview | Course TAs |
| 05 | Some Challenges and Lessons from Training Agentic Models | Weizhu Chen |
| 06 | Multi-Agent AI | Noam Brown |
| 07 | Predictable Noise in LLM Benchmarks | Sida Wang |
| 08 | AI Agents for Accelerating Scientific Discoveries | James Zou |
| 09 | Practical Lessons from Deploying Real-World AI Agents | Clay Bavor |
| 10 | AlphaStar Revisited: Multi-Agent Systems in the Era of LLMs | Oriol Vinyals |
| 11 | Autonomous Agents: Embodiment, Interaction, and Learning | Peter Stone |
| 12 | Towards Building Safe & Secure Agentic AI | Dawn Song |