Computer Science

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Term
Time & Day Offered
Level
Credits
Course Duration

Analyzing Blockchain/Web3 as an open distributed database — CS4391.01

Instructor: Michael Corey
Days & Time: TH 3:40pm-5:30pm
Credits: 2

Following up on the fall course on web3, this course helps students learn to track transactions and actions across blockchains, which are large distributed censorship resistant databases. The course starts by exploring the fundamental nature of the blockchain: how data is stored, accessed, and traversed. It then introduces common patterns

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,

Computing and Data in Practice — CS4392.01

Instructor: Michael Corey
Days & Time: Tu 8:30AM-10:20AM
Credits: 2

For students doing work-study or internships, we will focus on three core areas of professionalization. First, each week will journal our work weeks, discussing and sharing our work experiences in a round-table. Second, we will build our professionalization skills, especially networking (in person and on LinkedIn), resume writing, and

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

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)

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

Robotics and STEM Education: A Workshop — EDU2107.01

Instructor: Hugh Crowl
Days & Time: FR 10:30am-12:20pm
Credits: 1

In this course, students will gain experience with using simple programmable robots and how they can be utilized in STEM education. The focus of this class will be on learning and designing lessons for K-12 students utilizing these robots. This class is accessible for students at all levels of computer programming experience (including none).