Science and Mathematics

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Term
Time & Day Offered
Level
Credits
Course Duration

Climate Change, Ecology, and Seasons (with Lab) — BIO4439.01

Instructor: Carly Rudzinski
Credits: 4
Human activities have rapidly altered the climate at a global scale. Writer Lynda Mapes notes, “the climate is changing and with it, our seasons.” Ecosystems and the organisms they support are facing warmer and earlier springs, shifts in precipitation patterns, and altered growing seasons. The timing of seasonal activities of animals and plants are known to ecologists as

Climate Change: Past, Present, and Future — ES2103.01

Instructor: Andrew McIntyre
Credits: 4
Climate change is inarguably the most pressing current environmental issue. While human-caused climate change may be unprecedented, climate change itself is not. Indeed, the average temperature of our planet has fluctuated substantially over many millennia due to natural variability in Earth’s orbit and surface conditions. In this course, we will examine the physical basis for

Climate Science and Policy — ENV4109.01

Instructor: Tim Schroeder
Credits: 2
This course will seek to understand the relationship between climate change science and policy, allowing students to study the scientific basis behind policies to address one of our most pressing issues. We will examine major climate policies and proposals – like the Paris Agreement, Intergovernmental Panel on Climate Change reports, and the Inflation Reduction Act – with an

Code Crafting — CS2236.01

Instructor: Ursula Wolz
Credits: 4
This course is based on the national Computer Science Principles curriculum, but uses textile production as a vehicle for teaching software design and programming. The course addresses the history of computing and raises questions about the relationship between the Industrial Revolution and the Digital Age. The first half of the course uses a blocks language called Snap!

Coding Workshop — CS4379.01

Instructor: Jim Mahoney
Credits: 2
An opportunity to improve your programming skills, the Coding Workshop is a place to first work on some practice problems, then embark on a group project such as Google's "Tron Robot Challenge", and end with a final project of your choice. The specific languages and topics will depend in part on the participants, but may include Python, Javascript, web development, functional

Collaborative Software Engineering — CS4132.01

Instructor: justinvasselli@bennington.edu
Credits: 4
Software is rarely built by one person. It takes a team of people, technical and not, to make a piece of code become a product. This class will present ideas and techniques for designing and developing software from conception to deployment.  This class will provide experience working with version control, testing, debugging, refactoring, and programming with exceptions.

Collecting and Vetting Public Data for Research — CS4137.01

Instructor: Michael Corey
Credits: 4
In this course we will go over major methods for collecting and vetting public data to be used in research or computing settings. The course will start by learning about publicly available data sets, then progress through using APIs to call data providers, web-scraping public data, and finally capturing streaming data and converting it into usable datasets. This course will be

Comparative Animal Physiology (with lab) — BIO4201.01

Instructor: Betsy Sherman
Credits: 4
A rigorous course in which physiological processes of vertebrates and invertebrates are studied at the cellular, organ, organ system, and whole animal levels of organization. The unifying themes of the course are the phenomenon of homeostasis (whereby an animal maintains its organization in the face of environmental perturbations) and the relationship between structure and

Comparative Animal Physiology (with lab) — BIO4201.01

Instructor: Elizabeth Sherman
Credits: 4
A rigorous course in which physiological processes of vertebrates and invertebrates are studied at the cellular, organ, organ system, and whole animal levels of organization. The unifying themes of the course are the phenomenon of homeostasis (whereby an animal maintains its organization in the face of environmental perturbations) and the relationship between structure and

Comparative Animal Physiology (with lab) — BIO4201.01

Instructor: Betsy Sherman
Credits: 4
A rigorous course in which physiological processes of vertebrates and invertebrates are studied at the cellular, organ, organ system, and whole animal levels of organization. The unifying themes of the course are the phenomenon of homeostasis (whereby an animal maintains its organization in the face of environmental perturbations) and the relationship between structure and

Comparative Animal Physiology (with lab) — BIO4201.01

Instructor: Betsy Sherman
Credits: 4
A rigorous course in which physiological processes of vertebrates and invertebrates are studied at the cellular, organ, organ system, and whole animal levels of organization. The unifying themes of the course is the phenomenon of homeostasis (whereby an animal maintains its organization in the face of environmental perturbations).Topics include digestion and nutrition,

Computability and Logic — CS4383.01

Instructor: Darcy Otto
Days & Time: WE 8:30am-12:10pm
Credits: 4

In 1936, Alan Turing wrote a paper that invented computer science. Not a piece of computer science, not a contribution to it. The whole thing. “On Computable Numbers, with an Application to the Entscheidungsproblem” asked a question that nobody had thought to formalize: what does it mean to compute something? And in answering it, Turing proved

Computability and Logic — CS4383.01

Instructor: Darcy Otto
Credits: 4
This is not your typical class in computer science, or in formal logic; but you will learn a lot about both by taking it. Our subject will be one of the most important and influential papers that has ever been written—"On Computable Numbers, with an Application to the Entscheidungsproblem," by Alan Turing. This is the paper that birthed computer science as a discipline.

Computational Linguistics — CS4122.01

Instructor: Justin Vasselli
Credits: 4
In this class, students will learn various techniques and algorithms for processing human languages. Topics we will cover include data structures and algorithms for text processing, tokenization, and part-of-speech tagging among other topics. Students will learn techniques for working with large amounts of data, and gain familiarity with common resources such as the Penn

Computer Science Principles — CS2131.01

Instructor: Meltem Ballan
Credits: 4
This course is designed for all students. Computer Science Principles is an introductory course that introduces students to the breadth of the field of computer science. Students will learn to design and evaluate solutions and to apply computer science to solve problems through the development of algorithms and programs. Students will be provided real world  insights,

Computer Systems — CS4312.02

Instructor: acencini@bennington.edu
Credits: 4
A close look at how the unix operating system runs processes. Topics include machine-level data representation, C code and its compiled x86 assembly, virtual memory, process swapping, stack overflows, forking, the system heap, how compiling and linking are implemented, and inter-process communication. This material is a standard intermediate level part of undergrad computing

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

Computing and Data in Practice — CS4389.01

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

Confidently Unsure: Interpreting Statistical Tests Wisely — MAT2248.01

Instructor: Andrew McIntyre
Credits: 2
No matter our focus, data and information are relied upon in making decisions, building hypotheses, or in trying to show the connection of one idea or thought to another. In order to better understand (or argue against) a claim, we need to make sure we understand what the data is telling us and how it can be interpreted. This course will build towards understanding the basic

Conjecture and Proof in Discrete Mathematics — MAT4131.01

Instructor: Steven Morics
Credits: 4
Using concepts from combinatorial mathematics and computer science, this course is an introduction to the nature and process of doing mathematics; playing around with patterns, making conjectures, and then stating and proving theorems. The course revolves around a large collection of open-ended problems, concerning topics from graph theory, game theory, set theory,

Conservation Biology — BIO2129.01

Instructor: Carly Rudzinski
Credits: 4
This course introduces the unifying concepts of the diverse and interdisciplinary field of conservation biology, as well as highlighting the history of conservation in practice and current issues and methods. We will discuss conservation issues that span and integrate across disciplines and levels of organization, including: biodiversity and

Conservation Biology (with Lab) — BIO4133.01

Instructor: Carly Rudzinski
Credits: 4
This course introduces the unifying concepts of the diverse and interdisciplinary field of conservation biology, as well as highlighting the history of conservation in practice and current issues and methods. We will discuss conservation issues that span and integrate across disciplines and levels of organization, including: biodiversity and ecological functions,

Conservation Paleobiology — BIO4190.01

Instructor: Carly Rudzinski
Credits: 2
Most conservation biology studies are fairly short-term: years to decades. But, many of the threats to biodiversity, including environmental change, unfold over longer timelines, and dynamic ecological responses to disturbances may not be fully captured in short studies. Paleobiology — the study of fossil organisms — can extend our understanding of population and community

Creation of Statistics — MAT2247.01

Instructor: Josef Mundt
Credits: 4
The amount of data in the world is vast and is increasing exponentially. It is easy to become overwhelmed and lose sight of the goal of data: to answer questions we have about the world in a specific, concise manner. The goal of this course is to help craft answerable questions—and then answer them. In order to do this, we will be using a programming language (“R”) to help us

Creation of Statistics — MAT2247.01

Instructor: Josef Mundt
Credits: 4
The amount of data in the world is vast and is increasing exponentially. It is easy to become overwhelmed and lose sight of the goal of data: to answer questions we have about the world in a specific, concise manner. The goal of this course is to help craft answerable questions---and then answer them. In order to do this, we will be using a programming language ("R") to help us