Search by keyword, and use the left hand toolbar to filter your results further
Select Filters and then click Apply to load new results
Select Filters and then click Apply to load new results
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.
This course is for students who are doing advanced work in Sustainable Agriculture or community engagement work. Students will create an individual project developing project management skills that include planning, research, development, and implementation. The students will have the opportunity to collaborate with a community partner and will present their completed project at the end of term. A small project budget will be provided supported by The Bennington Fair Food Initiative grant.
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.
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.
How do we transition to a low-carbon economy in a manner that doesn’t reinscribe the social and environmental injustices that have plagued our fossil-fueled economy? On one hand, the continued burning of fossil fuels is producing environmental crises that threaten to destabilize the very foundations of collective life, with poor and historically marginalized communities bearing the brunt of the suffering. On the other hand, renewable energy technologies are far from environmentally and socially benign.
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.