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We live in a world awash with data. The rise of connected devices, sophisticated sensor networks, social media, and interconnected databases has led to an unprecedented flood of information. Making sense of the data that surround us is inherently a liberal art.

Large and complex datasets can be used to address societal challenges (e.g., climate change, energy and transportation, health, inclusion and systematic racism and inequality). Potential downsides exist as well in terms of loss of privacy, algorithmic bias, and broader ethical concerns.

To best meet these challenges, we need an integrated humanistic and scientific approach to understanding our data-infused world. Data science-related majors at Amherst include computer science and statistics, though many other majors facilitate the application of data science, including (but not limited to) anthropology, astronomy, biology, chemistry, economics, English, mathematics, neuroscience, physics, political science, psychology, and sociology.

Making sense of the data that surround us is inherently a liberal art.鈥 
鈥擭icholas Horton

Our Courses

Courses at all levels in data science, broadly defined, are available across the curriculum, including the following disciplines and courses. Introductory level courses below may satisfy prerequisite requirements for some of these courses, and provide some glimpses into data science.

Be sure you check prerequisites for courses you are interested in, as some may have higher-level requirements!

Astronomy

Political Science

Computer Science

Statistics

Introductory Courses


Data Science In the News

A professor sitting down looking at a student drawing a diagram on a whiteboard

Computer Science For鈥 Science

September 8, 2020

Read about how Assistant Professor of Computer Science Matteo Riondato uses data science to figure out how to extract the most accurate information from enormous data sets.

Read the Article

Want more information?

Reach Out to Our Faculty

Students interested in data science are advised to consult with the following faculty:

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Scott Alfeld

Scott Alfeld

Computer Science    
Visit Prof. Alfeld's Page

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Brittney Bailey

Brittney Bailey

Statistics    
Visit Prof. Bailey's Page

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Katharine Correia

Katharine Correia

Statistics    
Visit Prof. Correia's Page

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Kevin Donges

Kevin Donges

Statistics    
Visit Prof. Donges' Page

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Nicholas Horton

Nicholas Horton

Statistics    
Visit Prof. Horton's Page

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Shu-Min Liao

Shu-Min Liao

Statistics    
Visit Prof. Liao's Page

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Matteo Riondato

Matteo Riondato

Computer Science    
Visit Prof. Riondato's Page

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Lee Spector

Lee Spector

Computer Science    
Visit Prof. Spector's Page

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Amy Wagaman

Amy Wagaman

Statistics    
Visit Prof. Wagaman's Page

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Kate Follette

Kate Follette

Physics & Astronomy    
Visit Prof. Follette's Page

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Nick Holschuh

Nick Holschuh

Geology    
Visit Prof. Holschuh's Page

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Josef Trapani

Josef Trapani

Biology and Neuroscience    
Visit Prof. Trapani's Page

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Eleonora Mattiacci

Eleonora Mattiacci

Political Science    
Visit Prof. Mattiacci's Page

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Kate Moore

Katherine Moore

Mathematics and Statistics 
Visit Prof. Moore's Page

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Kerry Ratigan

Kerry Ratigan

Political Science 
Visit Prof. Ratigan's Page

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Matthew Schulkind

Matthew Schulkind

Psychology    
Visit Prof. Schulkind's Page