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 courses. Besides the mandatory Data Science Capstone course, students are recommended to choose 7 Data Science courses (DATS), two courses of choice from the following departments: Statistics (STAT), Mathematics (MATH), Geography (GEOG), or 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 make sure 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.

Data Science Department Courses:

  • DATS 6101 Introduction to Data Science
  • DATS 6102 Data Warehousing and Analytics
  • DATS 6103 Introduction to Data Mining
  • DATS 6201 Numerical Linear Algebra and Optimization
  • DATS 6202 Machine Learning I 
  • DATS 6203 Machine Learning II
  • DATS 6401 Visualization of Complex Data
  • DATS 6402 High Performance Computing and Parallel Computing
  • DATS 6450 Topics in Data Science

Examples of courses to be chosen in consultation with your advisor:

  • MATH 6522 Introduction to Numerical Analysis
  • STAT 6207 Methods of Statistical Computing
  • STAT 6214 Applied Linear Models
  • STAT 6242 Regression Graphics/Nonparametric Regression
  • GEOG 6304 Geographical Information Systems I
  • GEOG 6306 Geographical Information Systems II
  • GEOG 6307 Digital Image Processing
  • PSC  8120 Nonlinear Models
  • PSC  8132 Network Analysis
  • PSC  8185 Topics in Empirical and Formal Political Analysis

Capstone Core Course (1 course)

  • DATA 6501 Data Science Capstone

This three-credit course helps students apply what they have learned in data science courses to data-intensive real-world problems. Faculty will mentor each student in choosing an appropriate topic and enhancing communication, teamwork, and analytics skills.

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.


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