Master’s Degree in Data Science Requirements

Students applying to the M.S. Degree program in Data Science are expected to have a Bachelor's Degree with a strong quantitative and computational background including coursework in programming, data structures, algorithms, univariate and multivariate calculus, linear algebra and introductory statistics. Students with Bachelor's Degrees in computer science, mathematics, business, engineering and quantitative sciences would typically qualify.

Requirements for the Master’s Degree

Students pursuing the M.S. degree in Data Science must complete a minimum of 33 credits of relevant work at the graduate level. These 33 credits must include either the 3-credit Graduate Qualifying Project (GQP) requirement or the 9-credit M.S. thesis, and the core coursework requirements in Data Science as described below. These M.S. degree requirements have been designed to provide a comprehensive yet flexible program to students who are pursuing an M.S. degree exclusively and also students who are pursuing a combined B.S./M.S. degree.

 Upon acceptance to the Data Science Master of Science degree Program, students will be assigned an Academic Advisor. In consultation with the Academic Advisor, the student will prepare a Plan of Study outlining the course selections chosen to satisfy the M.S. Degree requirements. 

The Plan of Study must then be approved by the Data Science Steering Committee and brought to the Data Science office admin.  

DATA SCIENCE CORE COURSE WORK REQUIREMENT - (15 credits)  

A student in the M.S. program must satisfy the Data Science Core coursework requirements, i.e., students take one course from each of the five Data Science Core Areas.

GRADUATE QUALIFYING PROJECT or M.S. THESIS  (3 or 9 credits)

Students in the M.S. Data Science Program must complete one of the following two options:

  1. A Graduate Qualifying Project (3 credits). (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. 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.
                                                            
  2. A Master’s Thesis (9 credits). (DS 599) The Thesis choice in the Data Science Program consists of a Research Project worth a minimum of 9 Graduate Credits. Students interested in research, and in particular those considering a Ph.D. in a related area, are encouraged to select the M.S. Thesis option.  Students are required to choose a Faculty Advisor to oversee their thesis work, and may choose any affiliated Data Science faculty. If, however, the chosen Faculty Advisor is not a faculty affiliated with the Data Science program, then a Data Science affiliated tenure-track faculty must serve as the Thesis Academic Co-advisor. The Thesis Proposal must be approved by the Academic Advisor and the Data Science Steering Committee before the student can register for more than three Thesis Credits. The student  must satisfactorily complete a written M.S. Thesis and present the results to the Data Science Faculty in a public presentation.

ELECTIVES and AREAS of CONCENTRATION ( 9 - 15 credits)   

A student in the M.S. in Data Science program must take course work from the Program Electives in order to satisfy the remainder of the  33 credit requirements. An elective may be any of these graduate-level courses a approved for the Data Science Program, with the restriction that no more than 16 of the 33 credit Data Science Degree Program may be courses offered by the Robert A. Foisie School of Business.

While the core areas ensure that students have adequate coverage of essential Data Science knowledge and skills, the wide variety of electives allows students to tailor their Data Science Degree program to domain and technique areas of personal interest. Students are expected to select electives to produce a consistent program of study. While the core coursework requirements provide the needed breadth in Data Science core categories, students can 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 Data Science Program Electives may also be chosen as elective courses, but only with prior approval by the Data Science Steering Committee, and only if consistent with the student’s Plan of Study. For example, a student may choose to concentrate their data science expertise on areas of health, engineering or sciences not captured in the electives choices. Independent Study and Directed Research courses also require prior approval by the Data Science Steering Committee.