CSC242: Introduction to Artificial Intelligence
Spring 2022

Course Information

Introduces fundamental principles and techniques from Artificial Intelligence, including heuristic search, automated reasoning, handling uncertainty, and machine learning, to prepare students for advanced AI courses.

Credit hours: 4.0

Prerequisites: CSC172, MTH150 (no exceptions); CSC173 STRONGLY RECOMMENDED.

Class: Tue-Thu 0940-1055 Dewey 1-101

Web: BlackBoard and

Students may NOT add this course after the end of the two-week online Drop/Add period.

If changes to this syllabus are necessary, they will be announced on BlackBoard.

Instructor Information

Prof. George Ferguson <>

Office: Wegmans Hall 2103 (see instructor website for office hours)

Teaching Assistants:

Study Sessions: TBA (watch BlackBoard for announcements)

Course Goals

This course introduces fundamental principles and techniques from Artificial Intelligence, including:

The course is divided into four units, one for each topic listed above. You will not learn everything there is to know about AI from this course. But you will be prepared to learn more in advanced AI courses.

Course Mechanics

Textbook: Russell & Norvig, Artificial Intelligence: A Modern Approach, 4th ed. (2020). This book is excellent and will be a worthwhile addition to your Computer Science bookshelf.

Another good book is Poole & Mackworth, Artificial Intelligence: Foundations of Computational Agents, 2nd ed. (2017). Its approach is very similar to AIMA, especially for the material covered in this course.

Additional readings and resources will be assigned as needed and posted to BlackBoard.

Course calendar (including readings, assignments, and exam dates):

Grading: Each unit will be equally weighted in the final grade:

In other words, each unit is worth 1/4 (25%) of the final grade: 12.5% for the unit exam and 12.5% for the project.

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):

A: Excellent ≥90%
B: Above Average ≥80%
C: Minimum Satisfactory Grade ≥70%
D: Minimum Passing Grade ≥60%
E: Fail <60%

All appeals of grades must be made within ONE WEEK of the grade being posted.

Assessment and Student Support

Learning Outcomes

Students who complete this course shall be able to:

Academic Support Services


Academic Honesty

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:

You will learn the most if you do all the work in this course ON YOUR OWN.

That said, collaboration on projects is permitted, subject to the following requirements:

Avoid sites like GitHub and StackExchange for the duration of this course.

Note also that posting homework and project solutions to public repositories on sites like GitHub is a violation of the College’s Academic Honesty Policy, Section V.B.2 “Giving Unauthorized Aid.”

Disability Resources

The University of Rochester respects and welcomes students of all backgrounds and abilities. In the event you encounter any barrier(s) to full participation in this course due to the impact of disability, please contact the Office of Disability Resources. The access coordinators in the Office of Disability Resources can meet with you to discuss the barriers you are experiencing and explain the eligibility process for establishing academic accommodations. You can reach the Office of Disability Resources at:; (585) 276-5075; Taylor Hall.

Students with an accommodation for any aspect of the course must make arrangements IN ADVANCE through the Disability Resources office. Then, as instructed by the office, contact the instructor to confirm your arrangements. Do not leave this until the last minute.


We hope that you will want to attend class (lecture), but attendance is NOT required. However if you choose not to attend, you may miss important announcements or information about the course.

Credit Hours

This course follows the College credit hour policy for four-credit courses, including lectures and study sessions.

Students are expected to do significant work outside of class time. This supplementary work on homework, projects, and exam preparation may require up to twice again as many hours of effort per week.


This course follows the University policy regarding incompletes: “Incompletes may be given only when there are circumstances beyond the student’s control, such as illness or personal emergency, that prevented the student from finishing the course work on time.”


Computer crashes, malfunctions, and catastrophic loss of files are NOT valid excuses for not submitting work on time. CSC242 students are 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.

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 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.

Students with an appropriate excuse for missing any exam or project deadline must make arrangements IN ADVANCE.

Other Policies

Please also note Section V.7 of the College’s Academic Honesty policy regarding “Unauthorized Recording, Distribution or Publication of Course-Related Materials.”