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Program Overview

Data Science

Unlock valuable insights and knowledge.

Detail of "Dialectic Triangulation: A Visual Philosophy," Agnes Denes. Allen Memorial Art Museum, Oberlin College.
Photo credit: ©Agnes Denes

Explore the World of Data from Start to Finish

The growth and use of data is increasingly vital for many disciplines, from the natural sciences to the social sciences, and from business to the humanities. Data science equips students with principled, scientific methods for collecting, managing, analyzing, and decision-making using data. It synergizes and builds upon the computational problem solving of computer science, the analytical skills of statistics and mathematics, and the designed data collection and experimentation of the natural and social sciences to unlock insights and knowledge from large- and small-scale data in diverse mediums.

Evidence-Based Solutions

Data science offers critical skills for the 21st-century workforce and academy. Students at Oberlin work closely with faculty on real-world data sets including public health information, census tract records, GPS tracking data, social media posts, biometric observations, and more. Students in the data science concentration work toward evidence-based solutions to challenges such as climate change, public health, and the spread of misinformation.

More than 20 years of data on energy use collected via Oberlin’s Environmental Dashboard program
Learn more about Environmental Dashboard

Pathways in Computer Science

Oberlin Computer Science provides a background in fundamentals of data science, logic, theory and programming, but we go beyond just coding. With an Oberlin CS degree, you will learn how the computer revolution is changing society and our lives, and how you can help shape its impact.

A student at a shiny computer.
672 drop-in programming lab tutoring hours per year, including weekly safe space hours for women & transgender students and students of color

STEM in Color

Oberlin’s STRONG program (Science and Technology Research Opportunities for a New Generation) represents the college’s ongoing commitment to increasing the diversity of the STEM workforce.

Students of color participating in a discussion.

Featured Courses

CSCI 144

Introduction to Data Science

The growth and use of data is increasingly vital for many disciplines, from the natural sciences to the social sciences, and from business to the humanities. This course introduces students to data science and informatics that study how to collect, manage, process, analyze, and visualize data from a computational perspective. Topics include computational thinking, understanding different types of data, database techniques, and a variety of data analysis approaches. Focus will be on gaining a breadth of knowledge and the exploration of applications of data science and informatics.

Taught by
Adam Eck
STAT 205

Statistics and Modeling

An introduction to statistics and, in particular, linear models for students with some background in statistics and a good background in mathematics. Topics covered include exploratory data analysis, probability, sampling, estimation, statistical inference, multiple regression, one-factor and multi-factor analysis of variance, and analysis of categorical data via logistic regression. Statistical software is used heavily.

Taught by
Jeffrey (Jeff) Witmer
ECON 255

Introduction to Econometrics

This is an introduction to the application of statistical methods to the estimation of economic models and the testing of economic hypotheses using non-experimental data. The central statistical tool is multivariate regression analysis. Topics covered include: the Gauss-Markov theorem, testing hypotheses, and correcting for heteroskedasticity, autocorrelation and simultaneous equation bias. In the weekly computer lab sessions econometric software is used to analyze real-world data.

Taught by
Maggie Brehm
PSYC 311

Advanced Methods in Diversity Science

This course introduces students to theoretical and methodological considerations for conducting research with diverse populations (e.g., ethnic and racial minorities). Content areas may include (but are not limited to) cultural socialization, interracial relationships, and mental health. Students will gain further experience with various stages of the research process (e.g., conceptualization, literature review, study design, data analysis, report-writing).

Taught by
Christine S. Wu

Student Profiles

The Frontier of Economic Science

Mark Walker, a junior majoring in Russian studies, economics, and mathematics, has recently been awarded the prestigious Beinecke Scholarship, which he plans to put toward a graduate program in economics.

Mark discusses a book with a professor.

Studying the Effects of Covid-19

Alexa Myles ’21 and Devin Williams ’21 t joined a team of students who assisted Professor of Psychology and Environmental Studies Cindy Frantz in a project that would lead to the study of COVID-19 on psychological factors.

Alexa Myles

From Oberlin to Google

Four Oberlin computer science majors have accepted jobs from the tech giant while still in their senior year. Sage Vouse ’19 is one of them.

Sage Vouse

Next Steps

Get in touch; we would love to chat.

The science center at dusk
Photo credit: Mike Crupi