Spring 2026 Course Search

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

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.

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.

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.

This course covers the breadth of university calculus: differentiation, integration, infinite series, and ordinary differential equations. It focuses on concepts and interconnections. In order to cover this much material, computational techniques are de-emphasized. The approach is historically based and classical, following original texts where possible.

Multivariable calculus is one of the core parts of an undergraduate mathematics curriculum. Introductory calculus mostly concentrates on situations where there is one input and one output variable; multivariable extends differentiation, integration, and differential equations to cases where there are multiple input and output variables. In this way, multivariable calculus combines calculus and linear algebra; the subject can also be called vector and matrix calculus.

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.

In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis, and effective presentation of results.

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.

Throughout history, people have played games — games of chance and games of skill. Many of us grew up playing all kinds of different games, and most of those are infused with the core tenets of statistical reasoning and understanding: probability, risk assessment, expected value, and game theory. This course will look at statistics and probability through this lens. We will consider dice, cards, and several ‘classic’ board games. We will consider situations with both complete and hidden information and how to analyze those.

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). 

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.

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 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.