M.S. in Data Science

Students in the M.S. program must take both courses in the Integrative Data Science category and one (1) course from each of the other core Data Science categories listed below:

If a student has completed a B.S. degree in Data Science at WPI, then the “Integrative Data Science” core area requirement is waived. Instead, the student can earn the corresponding 3 credits by taking any of the data science courses listed in the graduate catalog, including DS 501.

If a student does not have prior background in a particular core category, then it is advised that the student take the course with an asterisk * in the title within that category. If two or more courses have an asterisk *, then the student may select either of these courses based on their personal interest and background. Students must take at least 1 course in each of these core areas, but are encouraged to take several. Additional courses taken in a core category will count as electives and/or concentration courses as described below.

Graduate Qualifying Project GQP or M.S. Thesis

A student in the M.S. program must complete one of the following two options:

• 3-credit Graduate Qualifying Project. (DS 598) This project is most commonly done in teams, and will provide a capstone experience in applying data science skills to a real-world problem. It will be carried out in cooperation with a sponsor or an industrial partner, and must be approved and overseen by a faculty member affiliated with the Data Science Program. The graduate qualifying project is typically taken for 3 graduate credits. With permission by the instructor, a student can take the course a second time for additional credit, up to a total of 6 graduate credits. This means that the student could take two offerings of the course concurrently in one semester or could register for three credits in one semester and another three credits in a subsequent semester. A student that follows this practice-oriented project option must gain sufficient Data Science depth by selecting at least 2 courses beyond the required Data Science core courses from among the electives below within the same area of concentration.

• 9-credit Master’s Thesis. (DS 599) A thesis in the Data Science Program consists of a research or development project worth a minimum of 9 graduate credit hours. Students interested in research, and in particular those who are considering a Ph.D. in a related area, are encouraged to select the M.S. thesis option. Any affiliated DS faculty may serve as the thesis advisor. If the advisor is not a tenure-track faculty at WPI, then a DS affiliated tenure-track faculty member must serve as the thesis co-advisor. A thesis proposal must be approved by both the DS Program Review Board and the student’s advisor before the student can register for more than three thesis credits. The student must then satisfactorily complete a written thesis and present the results to the DS faculty in a public presentation.

A student seeking an M.S. in Data Science must take coursework from the Program electives listed below in order to satisfy the remainder of the 30-credit requirement. An elective may be any of these graduate level courses, with the restriction that no more than 14 credits of the 30- credit Data Science degree program may be courses offered by the School of Business. Any graduate course in the graduate catalog listed with a DS number, if not used for any other requirements, can be automatically considered an elective for the MS in DS program, unless otherwise stated in that particular course's description.

While the core areas ensure that students have adequate coverage of essential Data Science knowledge and skills, the wide variety of electives enable students to tailor their Data Science degree program to domain and technique areas of personal interest. Students are expected to select elective course work to produce a consistent program of study. While the core coursework requirements provide the needed breadth in Data Science core categories, students will gain depth in one or several concentrations by choosing appropriate electives from the list of pre-approved courses relevant to data science.

Other courses beyond the pre-approved Program electives may be chosen as electives, but only with prior approval by the DS Program Review Board, and if consistent with the student’s Plan of Study. For example, students might choose to concentrate their data science expertise on areas of physics, engineering, or sciences, not captured in the electives below. Independent study and directed research courses also require prior approval by the DS Program Review Board.

Other Relevant Graduate Courses and Concentration Areas:
Beyond courses in the three core disciplines of computer science, business, and statistics, relevant graduate courses in other potential areas of concentration, such as Finance, Manufacturing, Healthcare, National Security, Engineering, Fraud Detection, Science, Smart Grid Management, Sustainability and the like, may be added in the future to the above list of pre-approved Program electives.

Specializations of the Data Science degree in targeted areas of high societal impact ranging from Health Care to National Security may be designed in the future. We expect these specializations to naturally fit into the flexible structure of the Data Science degree framework.