Academic Programs Master's in Data Science

Application Requirements

  • GRE General: recommended
  • GRE Subject: not required
  • Record of grades or other academic performance
  • Letters of reference (you might suggest to your letter writers that they look at this site)
  • TOEFL (for applicants whose native language is not English)

Application Procedure

We accept applications until March 15 for fall admission. We admit students on a rolling basis but cannot accept applications after the deadline has passed. Once the application system has closed, it will not reopen until September for new applications. You will be notified by the Graduate School if you are admitted.

Note: if you are current Brown PhD student applying for a doctoral certificate, see the doctoral certificate page. 

We strongly urge you to provide unofficial (scanned) copies of your transcripts as part of the electronic application. You will be prompted to mail an official copy of your transcript if you are accepted to the program.

Graduate applications are handled by a combination of the Data Science Initiative and the Graduate School. Your application is formally processed by the Graduate School. Its content is then read by members of the Data Science Initiative, who then forward their recommendations to the Graduate School. The Graduate School formally admits you to the program. Therefore, you may receive correspondence from either of these entities.

Admission Requirements

The new master’s program at Brown aims to admit students from a wide range of backgrounds for distinctive careers in Data Science. 

Students entering the program will be required to have completed at least a year of calculus (at the level of MATH 0090 & 0100), a semester of linear algebra (at the level of MATH 0520), a semester of calculus-based probability and statistics (at the level of APMA 1650), and an introduction to programming (at the level of CSCI 0150 or 0170).

We also admit exceptional students who lack one or more of the minimum requirements in linear algebra, probability and statistics, and computer science. The four departments (Math, Applied Math, Computer Science, and Biostatistics) will offer a suitable course in each of these three topics during the Brown summer session before the first semester.

The students may also acquire the necessary prerequisites at another institution, with the approval of the program director.

5th-Year Master's Program

You can apply to this program by following this link. The application requirements are the same as above. However, the application for this program is possible until commencement. The program has the same course structure as the normal Data Science Master's program. The only difference is that two credits can be substituted by courses taken during the undergrad studies. In the following table we show which courses of the Data Science Master's program can be substituted. We group the courses by the different concentrations that a student selected for the undergraduate studies.


Course of the Master’s Program

Possible substitute Courses

Applied Mathematics / Mathematics / Statistics


DATA 1010: An Introduction to Topics in Probability, Statistics, and Machine Learning (2-credit course)

APMA 1690: Computational Probability and Statistics

APMA 1740/2610: Recent Applications in Probability and Statistics

Computer Science

DATA 1030: An introduction to Topics in Data and Computational Science
(2-credit course)

CSCI1951-A: Data Science and one of

  • CSCI1270 Database Systems
  • CSCI1380 Distributed Systems

Any other


DATA 2080: Data & Society (1-credit course)


DATA 0080: Data & Society


Elective Course (1-credit course)

An appropriate 1000-level or 2000-level course to be determined by the student and approved by the program advisor.