A young woman working at a computer 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.
—Nicholas Horton

Our Courses

Three photos of a computer classroom, a woman looking through a telescope and a computer science classroom 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!


    Political Science

    Computer Science


    Introductory Courses

    Data Science In the News

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

    Computer Science For… 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:

    A photo of Scott Alfeld

    Scott Alfeld

    Computer Science
    Visit Prof. Alfeld's Page

    A photo of Brittney Bailey

    Brittney Bailey

    Visit Prof. Bailey's Page

    A photo of Katharine Correia

    Katharine Correia

    Visit Prof. Correia's Page

    A photo of Kevin Donges

    Kevin Donges

    Visit Prof. Donges' Page

    A photo of Nicholas Horton

    Nicholas Horton

    Visit Prof. Horton's Page

    A photo of Tanya Leise

    Tanya Leise

    Visit Prof. Leise's Page

    A photo of Shu-Min Liao

    Shu-Min Liao

    Visit Prof. Liao's Page

    A photo of Matteo Riondato

    Matteo Riondato

    Computer Science
    Visit Prof. Riondato's Page

    A photo of Lee Spector

    Lee Spector

    Computer Science
    Visit Prof. Spector's Page

    A photo of Amy Wagaman

    Amy Wagaman

    Visit Prof. Wagaman's Page

    A photo of Kate Follette

    Kate Follette

    Physics & Astronomy
    Visit Prof. Follette's Page

    A photo of Nicholas Holschuh

    Nick Holschuh

    Visit Prof. Holschuh's Page

    A photo of Josef Trapani

    Josef Trapani

    Biology and Neuroscience
    Visit Prof. Trapani's Page

    A photo of Eleonora Mattiacci

    Eleonora Mattiacci

    Political Science
    Visit Prof. Mattiacci's Page

    A photo of Kerry Ratigan

    Kerry Ratigan

    Political Science
    Visit Prof. Ratigan's Page

    A photo of Matthew Schulkind

    Matthew Schulkind

    Visit Prof. Schulkind's Page