Schedule

Proposal Stage

T Mar 31
(slides)
Class meeting. Introductions! Everyone gets one slide.
Th Apr 2
Optional class meeting. Course staff will be present. Form teams and discuss project ideas!

deadline Report #0 (ungraded) due at 11:59 pm: Team name, list of members. Submit as an Ed post with the title “Team [team name]: [team member 1], [team member 2], [team member 3]”. This is preliminary; teams can still change until Report #1 is submitted (on Tuesday April 7).
T Apr 7
Class meeting. Form teams and discuss project ideas with your classmates.

deadline Report #1 is due at 11:59 pm: Team name, list of members, top three project ideas you’re excited about, minimal viable action plan for each with stretch goals. Submit as an Ed post with the title “Report #1: [team member 1], [team member 2], [team member 3]”, and enter the link to the Ed post on Gradescope.
Th Apr 9
Optional class meeting. Course staff will be present. Continue discussing project ideas.

deadline Report #2 is due at 10:00 am: For each of the three project ideas, establish pros and cons (consider especially whether you have the resources to succeed, how excited you are about the project, and whether a successful result would be useful to the world); identify and describe likely codebases/platforms; briefly describe two related papers (so six papers total for three ideas). Submit as an Ed post with a linked or attached pdf, 2-3 pages long, and enter on Gradescope.
T Apr 14
(slides)
Class meeting. Mini-lecture on technical writing.

deadline Report #3 is due at 11:59 pm: Project proposal. Choose one project idea. Clearly state your minimal viable action plan, stretch goals, motivation, related work (literature survey), project objectives, proposed methodologies, available resources, and the evaluation plan. Submit as an Ed post with a linked or attached pdf, 2-3 pages long (not including references), and enter on Gradescope.

Execution Stage

Th Apr 16
In-class office hours and working time.
T Apr 21
Class meeting.

presentation First updates. Each team has 5 minutes and should not use more than 5 slides.

deadline Report #4 is due at 10:00 am. You should complete at least one strawman/baseline approach, run experiments, and set up the evaluation framework. Submit as an Ed post with a linked or attached pdf, 2-3 pages long, and enter on Gradescope.
Th Apr 23
In-class office hours and working time.

deadline Report #5 is due at 10:00 am. You will individually report on your team’s effectiveness, including a summary of your own, and each team member’s contributions so far. These reports will only be seen by course staff. Submit through Gradescope as a 1-page pdf.
T Apr 28
Class meeting. In-class working time and cross-discussions with course staff.
Th Apr 30
In-class office hours and working time.

deadline Report #6 is due at 10:00 am. You should have completed multiple strawman/baseline approaches, recorded their performance, and performed error analysis; you should report on your first advanced solution attempt. What did you try? Are there any exciting results? Any confusing results? What are the failure modes? What will you try next? Submit as an Ed post with a linked or attached pdf, 2-3 pages long, and enter on Gradescope.
T May 5
Class meeting.

presentation Second updates. Each team has 5 minutes and should not use more than 5 slides.
Th May 7
In-class office hours and working time.

deadline Report #7 is due at 10:00 am. You should continue your advanced solution attempt, run more experiments, do more error analysis, and sketch out the next action plan. Submit as an Ed post with a linked or attached pdf, 2-3 pages long, and enter on Gradescope.
T May 12
Guest lectures on current AI research.
Th May 14
In-class office hours and working time.

deadline Report #8 is due at 10:00 am. You should report on your second/continued advanced solution attempts. Submit as an Ed post with a linked or attached pdf, 2-3 pages long, and enter on Gradescope.
T May 19
Class meeting.

presentation Third updates. Each team has 5 minutes and should not use more than 5 slides.
Th May 21
In-class office hours and working time.

deadline Report #9 is due at 10:00 am. You will individually report on your team’s effectiveness, including a summary of your own, and each team member’s contributions so far. These reports will only be seen by course staff. Submit through Gradescope as a 1-page pdf.
T May 26
Class meeting. In-class working time and cross-discussions with course staff.
Th May 28
In-class office hours and working time.
T Jun 2
No class. Use the time to finalize your report.

deadline Final project report (#10) is due on Tuesday, Jun 2 at 11:59 pm. This should be a 7-9 page pdf, not including references, and structured like a research paper; follow the ICLR style template. At the end of the paper (not counted towards the page limit), include an author contributions section with one short paragraph per team member. Submit as an Ed post with a linked or attached pdf, and enter on Gradescope.
Th Jun 4
presentation Final project presentations (5 minutes per team, during normal class time).

deadline The link to the Youtube video of your final presentation is due before class. Each team should post the link on Ed together with the abstract of your project (which you may copy from the final project report). Note that you will still give the presentation live during class.

deadline Report #11 is due at 10:00 am. Individually write your reflections on the course project. What did you think went especially well? What could have been improved? What would you have done differently next time, both as a team and individually? These reports will only be seen by course staff. Submit through Gradescope as a 2-page pdf.
Note
We will not use any final exam slot.

Machine Learning Capstone, CSE 481M, Spring 2026. University of Washington. Course materials are based on the NLP capstone (CSE481N) taught by Noah Smith. This site was built using Kevin Lin's package Just the Class, which is built on Just the Docs.