There are three fundamental requirements for earning a Graduate Data Science Certificate.
- Nine graduate credit hours of coursework in approved courses. These courses are designated as core and elective Methods, Technology or Applications. Only one course may be double-counted (up to 3 credits). It is recommended, but not required, that courses outside the main graduate program of study be selected to broaden the student data-science experiences (e.g., statistics students may take engineering courses, social-science students may take outside statistics and application courses, etc.).
- A Data Science related experience (3 credit semester equivalent, over 160 hours for work). This can take the form of non-credit activity like an internship, practicum, or professional project equivalent to a three credit-hour course, or additional coursework of at least three credits from the approved course list. (This course may be double-counted with another Rackham degree program.) To satisfy this “Plus Requirement” with a data-related experience, students will need to have their supervisor or mentor sign the verification form certifying that the student spent sufficient time working on a data-intense project during that practicum. Alternatively, if allowed and approved by the mentor, students may complete and submit to the DS Certificate Program Chair a report (2-6 pages) describing their experience and results, which will be evaluated to ensure the project demonstrates Data Science content, relevance and applications.
- Regular attendance of the MIDAS Seminar Series, which brings nationally recognized data scientists to U-M, is required. One semester (1-credit) enrollment in EECS 409 (MIDAS Seminar) is required (could count towards the 9 didactic credits). This colloquial training will expose students to current DS developments beyond the boundaries of their own discipline. Students will be required to attend 75% of all seminars (attendance will be taken) to complete the requirement.