Syllabus TL;DR
Spring 2027
This syllabus is subject to change. The final syllabus will be posted on Canvas.
Time: Mondays, 3:00–6:00 PM
Location: In person, room TBD
Prerequisites: CS 343 (Artificial Intelligence) or CS 342/363M (Machine Learning)
Considering enrolling?
- The first homework will be posted on December 11 and is due on the first day of class, Monday, January 11.
- In-person attendance is mandatory. Students are expected to attend all lectures.
- This is not a low-workload elective. Preparation, attendance, quizzes, homework, and substantial research effort are expected.
Course Policies
In-person attendance is mandatory. Students are expected to attend all lectures, including the final UT AI Safety Symposium, to participate in class, and to complete all homework and the final project.
Sessions combine lecture, discussion, and in-class coding exercises. Read the assigned paper before class and bring a laptop.
Deadlines & Late Days
All assignments are due at 11:59 PM Central Time (Austin time) on the due date.
All students get 3 late days at the start of the course. Each late day grants a 24-hour extension on one assignment deadline. Late days cannot be used for the project submission or peer reviews.
AI Use Policy
We encourage you to use AI as a generative and agentic tool: for studying, exploring ideas, coding, and running experiments. However, we ask that you write your own thoughts in your reports, projects, and peer reviews.
Grading
The grading breakdown below is subject to change. The final grading policy will be posted on Canvas.