Spring 2023
COMPSCI 294 182 - LEC 182
Special Topics
Theoretical Foundations of Learning, Decisions, and Games
Michael Jordan, Nika Haghtalab
Class #:31337
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
-26
Enrolled: 26
Waitlisted: 0
Capacity: 0
Waitlist Max: 125
No Reserved Seats
Hours & Workload
1 to 3 hours of instructor presentation of course materials per week, and 2 to 11 hours of outside work hours per week.
Other classes by Michael Jordan
+ 1 Independent Study
Course Catalog Description
Topics will vary from semester to semester. See Computer Science Division announcements.
Class Notes
* Course enrollment will be capped and faculty will be
focusing on students with a strong background in the material outlined in the course prerequisites and
a particularly clear alignment between students' research interests and the course material. They will
make enrollment decis.. show more
focusing on students with a strong background in the material outlined in the course prerequisites and
a particularly clear alignment between students' research interests and the course material. They will
make enrollment decis.. show more
* Course enrollment will be capped and faculty will be
focusing on students with a strong background in the material outlined in the course prerequisites and
a particularly clear alignment between students' research interests and the course material. They will
make enrollment decisions on a rolling basis.
*Please fill out this form to be considered for enrollment: https://docs.google.com/forms/d/e/1FAIpQLSfbCLh2AH_JCOzrYBCoAdbHER40HTQqIWDegfKMJ5lcxnwdpQ/viewform?usp=sf_link
* Prerequisites: Graduate level mathematical maturity, including proof-based graduate-level courses in at least two, but recommended three, of the following categories: Statistics and Probability, e.g., STAT205, STAT210 Economics, e.g., ECON207 Algorithms, e.g., CS270 Optimization, e.g., EE 227 Control theory, e.g., EE 221A Machine Learning, e.g., CS281A
* No undergraduates will be allowed in this class.
* Time conflicts NOT allowed show less
focusing on students with a strong background in the material outlined in the course prerequisites and
a particularly clear alignment between students' research interests and the course material. They will
make enrollment decisions on a rolling basis.
*Please fill out this form to be considered for enrollment: https://docs.google.com/forms/d/e/1FAIpQLSfbCLh2AH_JCOzrYBCoAdbHER40HTQqIWDegfKMJ5lcxnwdpQ/viewform?usp=sf_link
* Prerequisites: Graduate level mathematical maturity, including proof-based graduate-level courses in at least two, but recommended three, of the following categories: Statistics and Probability, e.g., STAT205, STAT210 Economics, e.g., ECON207 Algorithms, e.g., CS270 Optimization, e.g., EE 227 Control theory, e.g., EE 221A Machine Learning, e.g., CS281A
* No undergraduates will be allowed in this class.
* Time conflicts NOT allowed show less
Rules & Requirements
Requisites
- Students not in the Master of Engineering Program
Repeat Rules
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials
Associated Sections
None