CS 175: Project in Artificial Intelligence

Winter 2025

Schedule

(Week) Dates Wednesday Friday
(1) Jan 8Introduction: 
 Recording: 
(2) Jan 15Reinforcement learning in a nutshell: 
 Recording: 
(3) Jan 22, 24Exercise 1: Project proposal: 
(6) Feb 14Exercise 2: 
(7) Feb 21Progress report: 
(10) Mar 14Project report (extended to 3/17): 
(11) Mar 19Project presentations

Note: the planned schedule is subject to change. Course materials will occasionally be added above.

Course logistics

  • When: Wednesdays at 5pm–7:50, only in weeks 1 and 2.
  • Where: SE2 1304.
  • Format:
    • Lectures during the first couple of weeks will introduce reinforcement learning, suggested project platforms, and the course expectations and evaluation criteria.
      • These lectures will be in-person but recorded / online resources will also be available; please keep up to date with the schedule above.
      • Lecture attendance is optional but an exact online replica of the in-person materials cannot be guaranteed.
    • After the introductory lectures, project teams will meet separately at times they will schedule.
    • Each team will meet periodically with the instructor and/or TA.
      • In-person and virtual meeting slots will be posted throughout the quarter.
      • The minimum requirement is to meet the course staff once by week 5 and once more by week 9; however, this is way too little, and more frequent meetings are strongly encouraged.
    • To get you started, 2 exercises will be due on weeks 3 and 4.
    • Project proposals and reports will be due on weeks 3, 7, and 10.
    • During week 11, the class will meet again for teams to present their projects.
    • There will be no discussion section meetings.
  • Ed Discussion:
    • Please use the forum for course-related discussions.
    • Important course announcements will be posted there as well (not on Canvas).
    • Please use the forum (not email) to privately message course staff about course-related matters.
    • Please note that the identity of anonymous posters is visible to the course staff.
  • Canvas:
    • Instructions for exercises, proposals, and reports will be posted on this page and should be submitted on Canvas.
    • Canvas will also be used to manage teams and report grades.
  • Instructor: Prof. Roy Fox
  • Teaching assistant: JB Lanier

Grading policy

  • Exercises: 10% (individual)
    • Late submission: 3 grace days total, for both assignments, per person
  • Project proposal: 10% (team)
  • Progress report: 20% (team)
  • Final report: 40% (team + individual component)
    • Late submission: 5 grace days total, for all project submissions, per team
  • Project presentation: 15% (team)
  • Participation (meetings, forum, evaluations): 5% (individual)
  • No exams

Resources

Compute Resources
Past projects
RL tutorials
RL libraries
Courses
Books