Big Data, Big Opportunities

Students in our Data Science Program are mastering tomorrow’s technology and stepping into today’s workplace. Read more.


Developed through a collaborative effort between the Departments of Statistics, Mathematics, Physics, Economics, Geography and Political Science, our Data Science Program teaches students to understand data and contribute important insights that will change the way we live, work and communicate. As a result, we prepare students for successful and exciting careers in data science.


Our curricula for both the master's degree and graduate certificate feature a combination of courses that address:

  • Methods: Data management and data analytics; develop deep expertise in the programing languages essential for data science, including Python, JavaScript and R
  • Applications: Elective courses in data science applied to a specific knowledge domain, such as astrophysics, political science and geography (GIS)
  • Skills: Teamwork, project management and communication skills
  • Technology: Hands-on exposure to data analysis and visualization software tools and languages; gain experience applying data science principles to real world applications

Master of Science in Data Science Curriculum

The Master of Science in Data Science requires 10 three-credit graduate courses. In addition to the mandatory Data Science Capstone course, students are recommended to choose at least seven Data Science (DATS) courses and no more than two application area courses from departments such as Economics (ECON), Geography (GEOG), and Political Science (PSC).

You will have an academic advisor who will work with you to create a plan of study. Elective courses will be chosen in consultation with your advisor to ensure that you have taken pre-requisite courses and to help you with any permissions needed to register for a class. Please note: GW cannot guarantee that a course will be offered in a given semester.

Certificate in Data Science Curriculum

The Certificate in Data Science requires four data science courses, at least two of which are core courses. Please reference the lists above for course offerings.

Combined Bachelor of Science and Master of Science in the Field of Data Science

Students in the combined BS/MS degree program must complete requirements for both degrees. By taking a specified number of graduate credits as part of their undergraduate degree, students may decrease the number of credits normally required for the master's degree, allowing them to complete the MS in a shorter period of time and at a lower cost. For more information about the combined BS/MS degree program please refer to the Columbian College of Arts and Science's page on the University's Bulletin.

Curriculum for Master of Science in Data Science

Specific admission requirements are shown on the Graduate Program Finder.

The following requirements must be fulfilled:

The general requirements stated under Columbian College of Arts and Sciences, Graduate Programs.

30 credits, including 24 credits in required courses and 6 credits in elective courses.

DATS 6101Introduction to Data Science
DATS 6102Data Warehousing
DATS 6103Introduction to Data Mining
DATS 6501Data Science Capstone
DATS 6202Machine Learning I: Algorithm Analysis
DATS 6203Machine Learning II: Data Analysis
DATS 6401Visualization of Complex Data
DATS 6402High Performance Computing and Parallel Computing
6 credits in elective courses from the following:
DATS 6201Numerical Linear Algebra and Optimization
DATS 6499Data Science Applied Research
DATS 6450Topics in Data Science
GEOG 6304Geographical Information Systems I
STAT 6210Data Analysis
STAT 6214Applied Linear Models
STAT 6242Modern Regression Analysis

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