Spring 2026 Course Search

An herbarium is a museum of pressed plants, a record of flora following a system that dates back to the 16th century. Large herbaria at institutions like D.C.’s Smithsonian National Museum of Natural History, Chicago’s Field Museum, Cambridge’s Harvard University, and London’s Kew Gardens contain millions of specimens, collected from around the world. But, most herbaria are small herbaria, with less than 10,000 specimens.

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.

The cells in our bodies need to grow and divide in order to make new tissue, and to repair or replace damaged tissue.  The processes that govern cell growth and division are tightly regulated. When the cells that comprise the tissues of our bodies lose the ability to properly regulate their growth and proliferation, cancer is the result.  This introductory level course will provide an overview of the basic mechanisms and genetics underlying human cancers, as well as explore current diagnostic and therapeutic strategies.

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 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.

Why would a forest ecology course include an assignment to knit a wool hat? In this class we will explore the lasting impact of sheep on the Vermont landscape, from the earliest settler-colonizers through today’s small batch fiber mills and second growth forests studded with stone walls. Sheep, and especially a 19th century boom in merino sheep, radically altered Vermont’s forests and inspired early writing on conservation and sustainable land management.

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.