This course provides an introductory survey of concepts and techniques in artificial intelligence. We will cover methods for search, classification, reasoning, and machine learning. We will also look at applications including core AI (games, planning), robotics, computer vision, and natural language understanding.
This course assumes that you have taken data structures (CS 225) and therefore, by transitivity, Discrete Structures and Calculus I. A probability and/or statistics course (e.g. CS 361) is strongly recommended. It is intended to be a first course in AI. If you have already taken a specialized AI course (e.g. CS 446), be prepared for a repeat of some familiar material.
The lectures will be pre-recorded. However, there will be some synchronous activities at our scheduled time (MWF 9-9:50).
Except for the quizzes, these are all optional.
MPs will be due alternate Wednesdays, starting week 3. So each Wednesday (starting week 3), you will either have a quiz or an MP due.
Starting week 2, there will also be staff office hours at other times of the week. See the staff page. Many of these will be online but there may also be some in-person ones if/when it becomes safe to hold them.
If you attend in-person activites (e.g. office hours), you are expected to follow campus guidance on whether to wear a mask.
The textbook is Russell and Norvig, Artificial Intelligence: A Modern Approach, fourth edition. The bookstore has the hardbound (aka US) edition. Used copies, third edition, paperback (aka international) and electronic editions are also fine. It is officially optional; everything critical should be in the posted notes.
You will also need a reference for Python, which we will use to write the MPs. A good place to start is the the Python Tutorial. You should install version 3.8 or 3.9. However, since most recent changes don't affect basic features, the hardcopy version 3.6 tutorial should also be ok for getting started.
Other supplementary readings will be posted, typically from textbooks and other resources available online.
As long as we have enough seats, it's ok for non-registered students to sit in on lectures. You can (obviously) also do MPs on your own. However, non-registered students may not take the quizzes.
We will not let students add the class after add date (10 day of classes).
See the top menu for links to piazza, gradescope, and moodle.
If you registered at least a week before the start of classes, you should find that you are enrolled in the class on all three sites. The rest of you might or might not be on these sites yet. You can add yourself to the course on piazza and moodle if you aren't already there. Email the instructor to get added to the roster on gradescope.
If you would prefer not to use your U. Illinois email on gradescope or piazza, contact the instructor to be added under an alternate email address.
The course will have about 7 MPs, 6 quizzes, and a short final exam.
Grading Formula (3sh)
Students taking the course for 4sh will also do two short literature review papers. The grading formula will be adapted as follows:
The translation into letter grades will be at least as generous as the standard high school scale (e.g. 70% is a C-, 80% is a B-, 90% is an A-). Any necessary curving may be done differently for the 3sh and 4sh students.
Makeups for each quiz will be held on the Monday after the regular sitting. You do not need special permission or documentation to take the Monday makeup. Ad-hoc makeup times will be arranged only in rare cases (e.g. extended illness).
Exam/quiz regrade requests should be posted to the regrade folder on piazza.
The procedures for MP regrades will be posted on the MP page
Regrade requests must be submitted within a week after the grade and feedback comments have been released. The course staff reserves the right to regrade not only the items questioned by the student, but also the other parts of the assignment or test.
You are encouraged to discuss assignments with other students, to share high-level understanding of the design (e.g. how is a perceptron supposed to work?) or basic utilities (e.g. how do I open a file in Python?). It is ok to conduct this discussion online, e.g. on piazza. However, extended fragments of code should be shown only to course staff. Programming and writing of reports/papers must be done individually.
Do not post work (e.g. MP code) or discuss details (e.g. quiz solutions) until you are sure that everyone else is done. In particular, wait until after the end of the MP grace period and after the makeup for a quiz. If you aren't sure, ask the instructor.
You may look at external sources for tips and copy small fragments of code, e.g. examples of how to invoke some standard utility. Anything non-trivial copied from external sources must be properly acknowledged, e.g. using comments in your code. Be aware that these MPs are intended to be built largely from scratch, so your grade will be reduced if these external aides make the assignment significantly easier.
It is an academic integrity offense to deliberately or negligently copy from other students, assist other students in copying from you, or use external sources without acknowledgement. It is also an academic integrity offense if a written report significantly misrepresents what your code actually does. Copying with proper acknowledgement is not an academic integrity offence but may lead to a lowered grade if too little of the submitted work is your own. See the college statement and the student code for other types of actions that would be considered violations.
The standard penalty for an academic integrity violation is the larger of a 10% penalty or a zero on the assignment or quiz/exam involved. (This assumes a misdeed of some significance rather than a minor technical mistake or misunderstanding.) A second offense will typically cause you to fail the entire course.
If you need disability accommodations, please send a copy of your DRES letter to the instructor. Usually it's fairly easy to work out something appropriate. Similarly please tell the instructor if you need privacy protections beyond what we normally provide. (See here for the college's official statements.)
We expect that you can arrange your work so that minor problems (e.g. a short virus, planned travel) do not stop you from meeting the deadlines. In particular, you are expected to submit preliminary versions of MPs ahead of the deadline, so that last-minute problems will not have catastrophic consequences.
We will make special arrangements for the usual range of official excuses (e.g. illness, religious holidays), serious extenuating circumstances, and situations that you could not reasonably have avoided by good preparation (e.g. illness on the day of an exam/quiz). However, you must inform the instructor and respond to rescheduling emails in a timely manner. The meaning of "timely" depends on the circumstances. For example, planned travel or religious holidays should be reported in advance. On the other hand, there might be unavoidable delays informing us about a serious illness or injury.
For major and extended problems, we expect you to be in contact with the Dean of Students office. Or, for graduate students, your department's advising office. These offices can help document the problem, help you stay in contact with instructors, and determine if you need accommodations such as incompletes.
Occasionally there are problems affecting a large number of people, e.g. network outages, snowstorms, TA strikes. In that case, we'll make appropriate adjustments. Watch for announcements (e.g. piazza). Do not make unsafe choices, e.g. driving into campus when the roads are dangerous.