This course will cover a variety of topics in the general area of
Artificial Intelligence, with topic areas selected cooperatively
in the first week of class.
Prepare and deliver a lecture. One week beforehand, you need to
go over your lecture notes with me (at some mutually acceptable time).
You will be expected to deliver approximately an hour and 45 minutes
of class time in such a way that your classmates can learn
the material!
Provide homework problems. Specifically, two short problems that
are fairly cut-and-dried (i.e. with one answer) and two more
open-ended (but still not too time-consuming) problems. These should
be submitted on the day of your lecture or before, along with
solutions within two weeks. The assignment must be given to me
electronically (by email), either as .html or .pdf, to be linked from
the schedule page.
Provide a programming project. This should be a fairly
significant piece of work that ideally uses real-world data within the
context of your topic area. Data sources should be provided or linked
to but need not necessarily be cleaned up. The writeup should have
sufficient detail to allow the other students to solve it without
further input from you. Again, this should be sent as .html or .pdf
via email.
As learner:
Assess the lectures given by your classmates. A Clipboard survey
will be posted for each lecture, please fill it out promptly - these
are anonymous* and all feedback will be given to the lecturer.
(* I will also collect names for grading purposes only.)
Solve homework problems. You must answer homework problems in
half of the topic areas. For each topic area you choose, you must
answer one short problem and one open-ended problem. Homework must be
submitted no more than 2 weeks after the relevant lecture. (Deadlines
may be shorter for topics presented at the end of the quarter.) You
may hand in additional homeworks if you choose and your lowest grades
will be dropped.
Complete two programming projects (not in the topic area that you
lectured on). These will be due three weeks after the relevant
lecture, again modified at the end of the quarter. At least one
project must be on a topic from weeks 1-5.
Take a final exam. I will come up with the questions for this
but will use homework problems as jumping-off points.
Grading policy:
One third of the class grade will be based on the "lecturer"
portion (primarily the lecture itself) and two thirds on the
"learner" portion (split about evenly between homework, projects
and final exam). Details: