Students wishing to pursue the Computing option of the Ph.D. in Data Science will meet the following requirements.

PhD students with a recognized Baccalaureate degree are required to take ten (NJIT minimum: eight) 600-level or 700-level 3-credit courses (30 credits) of coursework beyond the Baccalaureate degree as well as four additional 700-level 3-credit courses (12 credits), for a total of fourteen (NJIT minimum: twelve) 3-credit courses (42 credits).

PhD students with a recognized Master’s degree or equivalent are required to take seven graduate courses, of which four should be 700-level 3-credit courses (21 credits). (NJIT minimum: four 700-level courses.)

Master’s project (course DS 700), Master’s thesis (course DS 701), or more than two independent study courses (courses DS 725 and DS 726) cannot be used to satisfy these coursework requirements.

Students will be required to take DS 644 (Introduction to Big Data), DS 675 (Machine Learning), and MATH 644 (Regression).

All required courses can be substituted by courses of equal difficulty, if the PhD advisor and the PhD directors in both options agree to them in writing. For example, if a student has already taken an equivalent course to a required course, then a substitute will be determined.

Students may request to transfer between the options prior to passing their qualifying exams.

With approval by the academic advisor and dissertation advisor, a student is allowed to take elective courses based on the dissertation topic.

Core courses listed here are a selection. All courses may be found at https://catalog.njit.edu/ Required courses are highlighted.