The interdisciplinary Data Science Program at the George Washington University prepares students for data-related careers in the physical and social sciences such as astrophysics, geographic information systems and computational biology. Developed through a collaborative effort among the GW Departments of Statistics, Physics, Economics, Mathematics, Geography and Political Science, the program teaches students to make sense of data and contribute informed observations that change the way we live, work and communicate.
What Is Data Science?
Data Science is an emerging field that aims to extract actionable insights from vast arrays of information, and the Data Science Program at GW is constantly evolving to adapt to the information sharing landscape. Drawing on techniques and theories from statistics, computer science and mathematics, the program focuses on the effective analysis and use of big data in the natural and social sciences. Through a structured curriculum that provides foundational knowledge as well as applicable skills, our students learn how to confront some of the most complex problems facing government and private industry.
- Interdisciplinary curriculum across a half-dozen specialties
- Internships and collaboration with major organizations and agencies in the Washington, D.C., metropolitan area
- One-on-one mentoring with advisors and faculty members
- Practical application of problem solving, communication and teamwork skills
- Capstone projects that provide real-world experience
- Dedicated Data Science Career Coach offering one-on-one sessions
News Updates for Alumni
Sent exclusively to alumni, the Data Science Program newsletter features alumni and program updates as well as event information. If you are one of our alumni, update your contact information with the GW Office of Alumni Relations to start receiving this and other exclusive benefits.
"I chose this program because it was a short and robust program. It only has 30 credits and all the classes were aligned with what I was passionate about in my learning process."
Pierre Basseriba Bamba
MS '20, Data Science