Course Staff
Dawn Song
Professor, UC Berkeley
Xinyun Chen
Research Scientist, Google DeepMind
MOOC, Fall 2024
Professor, UC Berkeley
Research Scientist, Google DeepMind
Weekly lectures with flexible completion timelines and online access
From fundamentals to advanced topics in LLM agents and AI
Multiple tiers of completion certificates based on your engagement
Large language models (LLMs) have revolutionized a wide range of domains. In particular, LLMs have been developed as agents to interact with the world and handle various tasks. With the continuous advancement of LLM techniques, LLM agents are set to be the upcoming breakthrough in AI, and they are going to transform the future of our daily life with the support of intelligent task automation and personalization.
In this course, we will first discuss fundamental concepts that are essential for LLM agents, including the foundation of LLMs, essential LLM abilities required for task automation, as well as infrastructures for agent development. We will also cover representative agent applications, including code generation, robotics, web automation, medical applications, and scientific discovery. Meanwhile, we will discuss limitations and potential risks of current LLM agents, and share insights into directions for further improvement.
LLM Agent course completion certificates will be awarded to students based on the rules of the following tiers. All assignments are due December 12th, 2024 at 11:59PM PST. To receive your certificate please complete the Certificate Declaration Form by December 17th, 2024 at 11:59PM PST.
NOTE: completing the assignments associated with this course in order to earn a Completion Certificate is completely optional. You are more than welcome to just watch the lectures and audit the course!
| Date | Guest Lecture (3:00PM-5:00PM PST) | Supplemental Readings |
|---|---|---|
| Sept 9 |
LLM Reasoning Denny Zhou, Google DeepMind |
|
| Sept 16 |
LLM agents: brief history and overview Shunyu Yao, OpenAI |
|
| Sept 23 |
Agentic AI Frameworks & AutoGen Chi Wang, AutoGen-AI Building a Multimodal Knowledge Assistant Jerry Liu, LlamaIndex |
|
| Sept 30 |
Enterprise trends for generative AI, and key components of building successful agents/applications Burak Gokturk, Google |
|
| Oct 7 |
Compound AI Systems & the DSPy Framework Omar Khattab, Databricks |
|
| Oct 14 |
Agents for Software Development Graham Neubig, Carnegie Mellon University |
|
| Oct 21 |
AI Agents for Enterprise Workflows Nicolas Chapados, ServiceNow |
|
| Oct 28 |
Towards a unified framework of Neural and Symbolic Decision Making Yuandong Tian, Meta AI (FAIR) |
|
| Nov 4 |
Project GR00T: A Blueprint for Generalist Robotics Jim Fan, NVIDIA |
|
| Nov 11 | No Class - Veterans Day | |
| Nov 18 |
Open-Source and Science in the Era of Foundation Models Percy Liang, Stanford University |
|
| Nov 25 |
Measuring Agent capabilities and Anthropic's RSP Ben Mann, Anthropic |
|
| Dec 2 |
Towards Building Safe & Trustworthy AI Agents and A Path for Science‑ and Evidence‑based AI Policy Dawn Song, UC Berkeley |
|
All coursework will be released and submitted through the course website.
All quizzes are released in parallel with (or shortly after) the corresponding lecture. Please remember to complete the quiz each week. Although it's graded on completion, we encourage you to do your best. The questions are all multiple-choice and there are usually at most 5 per quiz. The quizzes will be posted in the Syllabus section.
Create a twitter post, linkedin post, or medium article to post on Twitter of roughly 500 words. Include the link to our MOOC website in the article and tweet.
The written article is an effort-based assignment that will be graded as pass or no pass (P/NP). Submit your written article assignment HERE.
There will be 3 lab assignments to give students some hands-on experience with building agents. Students must pass all 3 lab assignments. All labs are due December 12th, 2024 at 11:59pm PST. Please read the instructions carefully here. Please read the FAQs here before asking questions in Discord.
| Assignment | Submission Form |
|---|---|
| Lab 1 | Submission 1 |
| Lab 2 | Submission 2 |
| Lab 3 | Submission 3 |
Check out our hackathon website here.
Sign up for the hackathon here — every member of the team should signup individually.
Then, complete the team creation form here. There are no limits to team sizes.
For any questions, please visit our Hackathon FAQ here. You can also ask questions and find potential team members in our LLM Agents Discord.
Submit your final hackathon project here before December 17th, 2024 @11:59PM PST.