Spring 2026 Course Search

Artificial Intelligence — CS4105.01

Instructor: Darcy Otto
Days & Time: TU,FR 2:10pm-4:00pm
Credits: 4

How can we create machines that think, learn, and solve problems? This course explores the fascinating field of artificial intelligence (AI), introducing the fundamental concepts, techniques, and ethical considerations that drive this rapidly evolving discipline.

Building upon your programming knowledge, you will explore key AI paradigms including search algorithms, evolutionary algorithms, swarm intelligence, and machine learning.  You will implement AI solutions to real-world problems, and gain an understanding of how to think about contemporary AI development.

Metric Spaces and Geometry — MAT4162.01

Instructor: Andrew McIntyre
Days & Time: TU,FR 8:30am-10:20am
Credits: 4

Everything is geometry! This class is about two things: first, about how mathematicians have extended the concept of "geometry" beyond triangles and circles, into higher-dimensional spaces, curved spaces, spaces of functions, discrete spaces, and more. Second, about how this extension of "geometry" can allow us to apply our powerful geometric intuition to a wide range of problems that might not initially seem geometric, both within mathematics, and in physics, computer science, and elsewhere.

Discrete Mathematics — MAT4107.01

Instructor: Katie Montovan
Days & Time: MO,TH 10:00am-11:50am
Credits: 4

Discrete mathematics studies problems that can be broken up into distinct pieces. Some examples of these sorts of systems are letters or numbers in a password, pixels on a computer screen, the connections between friends on Facebook, and driving directions (along established roads) between two cities. In this course we will develop the tools needed to solve relevant, real-world problems. Topics will include: combinatorics (clever ways of counting things), number theory and graph theory. Possible applications include probability, social networks, optimization, and cryptography.

Introduction to Computer Science 2: Algorithms and Application — CS4384.01

Instructor: Darcy Otto
Days & Time: TU,FR 10:30am-12:20pm
Credits: 4

Introduction to Computer Science 2 continues the design-recipe approach started in Introduction to Computer Science 1. We extend our toolkit from structural recursion into generative recursion, abstraction, and algorithmic problem-solving. Students move beyond simple data definitions to work with more sophisticated structures (trees, graphs, sets, maps) while beginning to reason about program efficiency and resource use.

After Superflat Directed Project: Nuclear War — VA4407.01

Instructor: Yoko Inoue
Days & Time: MO,TH 10:00am-11:50am
Credits: 4

Conducted through research focusing on the development of Japanese subcultures in the Post World War II period, this course poses various critical inquiries about the effects of the nuclear bombings of Hiroshima and Nagasaki on contemporary global consumer society, visual culture and the production of art.

Food and Politics: A Food Citizens Methodology Workshop — APA4160.01

Instructor: Yoko Inoue
Days & Time: WE 10:00am-11:50am & WE 2:10pm-4:00pm
Credits: 4

This class will investigate various pedagogical approaches to food studies by examining curriculums, topics and discourses being taught at some academic institutions. More importantly, we will put focus on researching art collectives, contemporary civic engagement practices, and other non-institutional models developed by creative practitioners and activists, which engage with food as a conduit to undertake social, political and cultural identity issues and to enhance their community cohesion.