Master of Science in Data Science

The Data Science Institute (DSI) at Brown offers a master's program (ScM) that prepares students from a wide range of disciplinary backgrounds for distinctive careers in Data Science. With connections to departments across campus, in particular Brown's Division of Applied Mathematics and Department of Computer Science, the master's program offers a unique and rigorous education for people building careers in data science. The program empowers students to work through data science projects from formulation, data collection, exploratory data analysis, model development and evaluation to deployment and communicating results with technical and non-technical audiences. Students have the opportunity to learn about various methods and algorithms in data science including but not limited to statistical methods, machine learning, deep learning, generative and agentic AI. The program also provides experience in important, frontline data-science problems in a variety of fields, and introduces students to ethical and societal considerations surrounding data science and its applications.

The program's course structure, including the capstone experience, ensures that students meet the goals of acquiring and integrating foundational knowledge for data science, applying this understanding in relation to specific problems, and appreciating the broader ramifications of data-driven approaches to human activity. 

Most students begin the program in the fall semester, which starts in early September. Students may also begin in the spring semester, which starts in late January. The default program length is 21 months for students who start in the fall and 24 months for students who start in the spring. Students who start in the fall may choose to complete the program in 12, 16, 21, or 24 months. Students who start in the spring may choose to complete the program in 16, 21, or 24 months; the 12-month option is not available for spring starts.

The curriculum for the Data Science Master's Program consists of nine credits: four core courses (this includes the capstone experience), four courses chosen from a list of restricted electives, and one unrestricted elective.   

Exceptionally well-prepared students may be permitted to substitute additional restricted electives for some core courses, with the exception of DATA 2050. Substitutions are approved by the Director of Graduate Studies and the instructors of the core courses on a case-by-case basis. Decisions can be based on the syllabi of comparable courses completed previously and corresponding grade thresholds or a proficiency exam.

In addition, students choose four restricted electives from the approved course list below. The courses are grouped into categories to help students identify options aligned with their interests. At least one course needs to be selected from the Responsible Data Science category to ensure students are exposed to ethics in data science. Students may select the other three courses from the full list. Note that overrides for non-DATA courses can be difficult to obtain. Pre-registration is highly recommended! The list will be updated regularly by the Director of Graduate Studies to reflect changes in course offerings. Courses will be added upon departmental or instructor approval.

Students may complete one unrestricted elective. This elective may be any graduate-level course that offers domain knowledge relevant to the student’s individual interests. To qualify, the course’s four-digit course number must begin with a nonzero digit, and it needs to be completed for a letter grade, not the SNC grade option. Students may select a course from the restricted-electives list as their unrestricted elective. Students considering a course outside the DSI, Computer Science and Applied Mathematics Departments are advised to consult the Director of Graduate Studies before enrolling.

While the open curriculum offers flexibility and student choice, we also recognize that some may find it difficult to navigate the course selection process. To that end, we suggest the following focus areas, which are oriented toward various data science roles and domains. All focus areas include the core courses (DATA2010, DATA1030, DATA1050, and DATA2050) unless a substitution is approved by the DGS.

• Data Analyst
  • DATA1491, DATA1500, DATA2020, STAT1560 or STAT2550, one elective
• General Data Scientist (most popular)
  • DATA1491,  DATA2060 or CSCI1420, DATA2080 or CSCI1470, DATA2100, an elective (DATA1500 or APCOMP215 are recommended)
• Machine Learning Engineer
  • DATA1491,  DATA2060 or CSCI1420, DATA2080/CSCI1470 or CSCI2470, DATA2100, an elective 
  • If a student can substitute one core course, we recommend APCOMP215
  • If a student can substitute two core courses, we recommend APCOMP215 and DATA2980 to cover an internship
• Machine Learning Researcher 
  • Substitute DATA2010 with DATA2060 or CSCI1420, DATA1491, CSCI2470, DATA2100, APMA1690, an elective
  • If a student can substitute additional core courses, we recommend STAT2690
  • These are theory- and proof-heavy courses; best suited for students with a strong CS and math background aiming for highly technical/theoretical roles or a PhD in ML research
• Public Good Data Scientist
  • DATA1250, DATA1491, CSCI1302, CSCI2953B, HIST/DATA1954S, or substitute one of these courses with an elective
• Computational Biology / Genomics Data Scientist
  • DATA1491,  APMA1080, CSCI1810/2810, BIOL2525, an elective
  • If a student can substitute one core course, DATA2080 is recommended
  • If a student can substitute two core courses, DATA2080 and DATA2100 are recommended
• Healthcare Analytics / Public Health Data Science:
  • BIOL2535, BIOL2595, DATA2020, STAT2590, an elective
  • If a student can substitute one core course, DATA2080 is recommended
  • If a student can substitute two core courses, DATA2080 and DATA2100 are recommended

We also offer the option of a 5th-year Master's Program if you are an undergraduate at Brown. This allows you to substitute a maximum of 2 credits with courses you have already taken. 5th-Year students must complete their Master's degree in one year (September - August).