Course Timetable

Section	Day	Time	Exam Date
2024 Fall 2025 Winter
CS 809 - Interactive Entertainment SW
This course surveys current research on the design and implementation of interactive entertainment software, including computer games. Topics include: interactivity, principles of interactive entertainment, hardware platforms, current software development tools and languages, game loop, design of virtual worlds and virtual characters, real-time requirements, incorporating multimedia resources, aesthetics.
001	MWF	11:30am - 12:20pm	16-DEC-24
CS 811 - Theory of Computing
Study of fundamental concepts of computer science from the theoretical point of view; basic concepts of computational complexity theory, algorithm analysis and their relation to the set of problems which can be programmed; "good" algorithm design. Prior to registering in this course, students should have a background in introductory compiler design, or algorithm analysis comparable to the senior undergraduate level.
001	T	7:00pm - 9:45pm	10-DEC-24
CS 820 - Artificial Intelligence
Logics; natural language processing; knowledge representation; uncertainty reasoning; machine learning; expert systems; neutral networks. Prior to registering for this course, students should have a background in artificial intelligence comparable to the senior undergraduate level.
001	MW	1:00pm - 2:15pm	18-DEC-24
CS 855 - Mobile Computing
Mobile Computing focuses on conducting research in the design, development, and evaluation of software in a networked mobile environment. The primary topics to be covered in the course include network computing, graphics programming, human-computer interaction, and evaluation methods, all focused on the challenges and opportunities afforded by modern mobile computing devices.
001	MW	1:00pm - 2:15pm	18-DEC-24
CS 890CB - Research Methods in CS
Review of the major consideration and tasks involved in conducting scientific research, with emphasis on Computer Science. Research Methodology. Technical writing.
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CS 890EC - Computational Learning Theory
Selected topics in computational learning theory and applications, e.g., models of interactive machine learning, privacy-preserving learning, statistical learning, recursion-theoretic models of learning, complexity analysis of learning algorithms. Reading materials include 2 book chapters and 10-15 research articles. A term project is required.
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CS 890EN - Topics in Machine Learning
This course provides an intensive study of one or more topics related to Machine Learning. Potential topics include inductive inference; concept learning; statistical learning; learning from time series; grammatical inference; knowledge acquisition.
001		-
CS 900 - Computer Science Graduate Seminar
CS Graduate students must complete two semesters of CS 900, with the exception of MSc Course Route students, who must complete one semester of CS 900. When enrolled in CS 900, a student must make one presentation and attend all presentations. In the first semester of CS 900, the student will choose a Computer Science topic within their research area. In the second semester of CS 900 (if required), the student will choose a topic within their own research.
001	MWF	3:30pm - 4:20pm
CS 901 - Research
Thesis research.
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CS 902 - Project Research
A supervisor approved project requiring an in-depth student investigation of a CS problem.
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