Instructor: Prof. George Ferguson <firstname.lastname@example.org>
Office: Wegmans Hall 2103 (see instructor website for office hours)
Lectures: Tue & Thu 1525-1640 in Wegmans Hall 1400
Patrick Conway <email@example.com>
Yutong He <firstname.lastname@example.org>
Michaela Houk <email@example.com>
Chris Janidlo <firstname.lastname@example.org>
Adam Kaplan <email@example.com>
Ben King <firstname.lastname@example.org>
Yujie Liu <email@example.com>
Ryan Wong <firstname.lastname@example.org>
TA Study Sessions: Tuesdays and Thursday 1940-2055 in Lattimore 210
This course introduces fundamental principles and techniques from Artificial Intelligence, including heuristic search, automated reasoning, handling uncertainty, and machine learning. An important goal of the course is to prepare students for advanced AI courses. Complete details are available in the Course Calendar.
CSC172 is required. CSC173 is strongly recommended (and may be required in future years).
Artificial Intelligence: A Modern Approach, Russell & Norvig, 3rd ed.
This book is excellent and will be a worthwhile addition to your Computer Science bookshelf.
Additional readings and resources will be posted as necessary.
There is homework for every class. Homework will NOT be graded. We may go over homework in class, and it can be discussed with the TAs in study sessions.
We do not have official CETL workshops, but the TAs hold regular study sessions. Many students find these VERY HELPFUL. Time and place are listed above.
There is a project for every unit. The projects are designed to deepen your understanding of the material in preparation for the unit exam. You are encouraged to start (and finish) projects EARLY. There is no point in doing them at the last minute.
There are FOUR (4) exams, one for each unit of the class. These will take place during class time.
There is a final exam during the final exam period, as scheduled by the Registrar. The final exam will consist of four sections, one for each unit.
This course does NOT permit additional work for extra credit under any circumstances.
Each unit will be equally weighted in the final grade.
Letter grades will follow the Official University of Rochester Grading Scheme. Note that the University scheme puts
average somewhere between C and B. The following table is an estimate of how the numeric grades will map onto the letter grades (subject to change):
|B: Above Average||>=80%|
|C: Minimum Satisfactory Grade||>=70%|
|D: Minimum Passing Grade||>=60%|
All appeals of exam or project grades must be made within ONE WEEK of the grade being posted.
We hope that you will want to attend class (lecture), but attendance is NOT required other than for exams. If you chose not to attend, you may miss important announcements or information about the course.
Computer crashes, malfunctions, and catastrophic loss of files are NOT valid excuses for not submitting work on time. You are all Computer Scientists—you should know how to deal with this by now. Backup your files regularly to at least one external drive and/or cloud storage. You can always complete your assignments using IT Center computers.
Network connectivity problems are also NOT an excuse for not submitting work to BlackBoard on time. CSC242 students are all familiar with BlackBoard, for better or worse. Upload early just in case.
Students with an appropriate excuse for missing any exam or project deadline must make arrangements IN ADVANCE.
Students with an accommodation for any aspect of the course must make arrangements through the Center for Excellence in Teaching and Learning (CETL) IN ADVANCE. Then, as instructed by CETL, contact the instructor to confirm your arrangements. Do not leave this until the last minute either.
Students who are unable to attend or complete any part of the course due to illness should contact the instructor AS SOON AS POSSIBLE. Please note that the University Health Service (UHS) does not provide retroactive excuses for missed classes. Students who are seen at UHS for an illness or injury can ask for documentation that verifies the date of their visit(s) to UHS without mention of the reason for the visit. Students with extended or severe illness should contact the College Center for Advising Services (CCAS) for advice and assistance.
All assignments and activities associated with this course must be performed in accordance with the University of Rochester's Academic Honesty Policy. More information is available at: www.rochester.edu/college/honesty
You will learn the most if you do all the work in this course ON YOUR OWN.
Collaboration on projects is permitted, subject to the following requirements:
Electronics (laptops, phones, etc.) are NOT permitted in class.Research shows that students who take notes using pen and paper retain significantly more of the information. Typing your handwritten notes into the computer after class improves understanding and retentions even more.
If you have a CETL-approved accomodation that requires the use of a laptop or other electronic device in class, you MUST make arrangements with the instructor.
Please note Section V.7 of the College's Academic Honesty policy regarding
Unauthorized Recording, Distribution or Publication of Course-Related Materials.