Applicants admitted into the Ph.D. program with a Master’s Degree or a graduate degree recognized as relevant to Data Science by the Data Science Steering Committee must complete 60 credits towards their Ph.D. degree.

Students admitted with a B.S. degree only, must complete 90 credits of related work at the graduate level. 

These Ph.D. 90 students must complete the Data Science Master’s degree at WPI using the M.S. Thesis option as the first step towards the Ph.D. Degree. Thereafter for the remaining credits towards the Ph.D., they follow the same guidelines as Ph.D. 60 students as outlined below.

Each Ph.D. student is assigned an Academic Advisor and together they formulate a Plan of Study. This plan outlines the courses the student chooses to satisfy the Ph.D. degree requirements. 
The Plan of Study is then approved by the Data Science Steering Committee.

Ph.D. Requirements (60 credits) 
Ph.D. students must satisfy each of the following requirements. If a course is listed below as satisfying more than one requirement, a student can only count such a course towards one course work requirement. If a requirement listed below has already been met as part of the student’s M.S. degree, then the student can petition to the Data Science Steering Committee to take alternate elective courses instead.

  1. Core Breadth Competency: (At least 15 credits)
    All data science Ph.D. degree students must gain core knowledge of mathematical analytics, data access and management, data analytics and mining, and business intelligence. To meet this core breadth competency, students complete at least one 3-credit core course in each of the five data science core areas for a total of 15 credits. Students must earn an A or B grade for courses to be used to satisfy this requirement.

  2. Core Depth Competency (6 credits) 
    Students must gain depth in areas of mathematical analytics, data access and management, data analytics and mining, and business intelligence by taking a second course in at least two of the above Data Science core areas, for a total of two additional courses (additional 6 graduate credits). Students must earn an A or B grade for courses to be used to satisfy this requirement.

    A student must earn an A grade in 4 of the 7 courses taken in the Data Science Core areas to meet the Core Breadth and Core Depth Competency requirements. 
    They must be completed within 2 years after starting the Ph.D. 60 program.
  3. Program Electives (9 credits) 
    An elective may be any graduate course on the approved list of courses for the Data Science M.S. and Ph.D. degrees. Other graduate courses, Graduate Research Credits, or ISGs may also be used, with prior approval of the Data Science Steering Committee.

  4. Research Credits (30 credits)
    At least 30 credits must be Research Credits, consisting of DS 597 Directed Research and DS 699 Dissertation Research. Prior to Admission to Candidacy, a student may receive up to 18 credits of Pre-Dissertation Research under DS 597 Directed Research. Only after passing the Research Qualifying Exam and subsequently being admitted to Ph.D. Candidacy, a student may receive credit  toward Dissertation Research under DS 699.

  5. Electives and Areas of Concentration (remaining credits) 
    A student in the Ph.D. Data Science Program may take any additional course work from the approved list of courses for the Data Science M.S. and Ph.D. Degrees to satisfy the remainder of the course credit requirement. Other graduate courses, Graduate Research Credits, or ISGs may be used with prior approval by the Data Science Program's Steering Committee.

Beyond these credits, students are required to pass a Qualifying Examination, and propose and defend Dissertation Research.

To learn more about the Ph.D. milestones, including the Ph.D. Qualifying Examination, the Ph.D. Dissertation Proposal and the Ph.D. Final Dissertation Defense follow this link.