Spring 2026 Course Search

Chemistry 2: Organic Structure and Bonding (with Lab) — CHE4212.01

Instructor: Fortune Ononiwu
Days & Time: T/F 10:30AM-12:20PM, W 2:10PM-5:50PM (Lab)
Credits: 5

Building on structural and reactivity insights developed in Chemistry 1, this course delves into molecular structure and modern theories of bonding, especially as they relate to the reaction patterns of functional groups. We will focus on the mechanisms of reaction pathways and develop an understanding for how those mechanisms are experimentally explored. There will be numerous readings from the primary literature, including some classic papers that describe seminal experiments.

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 doing practice interviews. Finally, we will work on writing 5-year plans, to help us figure out where we’d like to be a few years after graduation. More specifically

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 and software used for blockchain analytics.

Special Projects in Spanish — SPA4812.01

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

In lieu of more conventional advanced Spanish classes, paralleling a series of often disparate tutorials, with tutees working in relative isolation, the proposal is to allow students free reign over an idea for a final, term-long project, while concurrently offering them an educated, exoteric audience to assist in fleshing out their work.

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.

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). 

Spanish Through Film — SPA4222.01

Instructor: Jonathan Pitcher
Days & Time: MO,WE,TH 8:30am-9:50am
Credits: 4

Students with burgeoning linguistic skills will learn the language through an immersion in Latin American and Spanish film in the second half of this full-year introduction to the Spanish-speaking world. While there will be some discussion of more common tactics such as stylistic nuances, script-writing, acting, dubbing, and directors’ biographies, it is expected that we will continue to develop sufficient linguistic ability to focus on cinematographic and social movements, thus treating the films as ideologemes, representations of political import.

Inner Travel — SPA4604.01

Instructor: Jonathan Pitcher
Days & Time: MO,TH 1:40pm-3:30pm
Credits: 4

Beyond Columbus’ errant journey into the abyss and the ensuing quest for El Dorado, or Darwin’s Voyage of the Beagle, Latin America’s interior has often enticed its own learned population. Their travels, in space, time and thought, do not merely present a physical confrontation with alterity, with the continent’s supposed heart of darkness, but an intellectual clearing, an origin, from which a more equitable politics may begin.

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.