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CSE 415: Introduction to Artificial Intelligence
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The University of Washington, Seattle, Winter 2024
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Regular Meetings: Mondays, Wednesdays, and Fridays,
2:30-3:20 in
CSE2 G01.
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Announcements:
Registering for the course: If you have not been able to
register for the course, but you believe you are qualified, please
come to class on Day 1 and the rest of the first week.
Assuming places open up, and you have the appropriate background,
we will try to give priority to students who were there since Day 1.
For additional information, click
here.
Worksheets: Worksheets are due by 11:59 PM the day after
they are administered in class. This will provide extra time, in case not
all aspects of a worksheet can be covered in class, and in case students
don't have enough free time to finish them the same day.
Students who register after a worksheet or assignment deadline as passed
will be allowed to submit work late, up to three days after joining.
Class Format:
Lectures and some office hours will normally be in-person.
Other office hours or special sessions may be on Zoom.
Lectures are scheduled to be recorded using the Panopto system.
Turn-in Deadline Extension Requests:
Requests should be posted as private messages to the staff in the Requests
topic within ED. See the Policies web page for additional information.
Final Examination: All students registered in CSE 415 must take the final
examination at the scheduled time and place (Tuesday, March 12, 2024, from 2:30 PM to 4:20 PM
in CSE2 Room G01), unless an official accommodation is being
made through the Disabled Student Services office. If you expect to be traveling
out of town at the time of the final examination, you should take CSE 415 in some
future quarter rather than during Winter 2024 and/or sign up for a different course instead.
Final Examination Topics:
The final exam covers the whole quarter but with more emphasis on material since the midterm.
See this additional info.
Midterm Exam Topics:
The exam covers the topics of the course through Bayes nets and counting free parameters
in Bayes nets. Here is a
detailed list
of the topics.
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