Data Science

Requirements

An individual graduate program is arranged by the student with an advisor during the first semester and approved by the student’s Graduate Committee. All students complete three required computer science courses and a master’s project course. Elective courses round out the student’s program.

Required Courses

Either DSC 530/CIS 568 Data Visualization or CIS 530/DSC 531 Advanced Data Mining Credits: 3
DSC 550 Data Science Practicum Credits: 3
MTH 522 Mathematical Statistics Credits: 3
CIS 552 - Database Design Credits: 3
- (CIS 452, CIS 530, or CIS 430 may be substituted for CIS 552 with prior approval from the Program Director)
EAS 520 - High Performance Scientific Computing Credits: 3

Select five additional approved 500- or 600-level courses

Approved courses from another department may be substituted, with prior approval from the Graduate Curriculum Committee or Director(s) of the Data Science Program. Students approved to do a formal thesis register for DSC 690 Master’s Thesis (3) as one of these elective courses.

Additional Requirements

As many as two undergraduate technical electives may serve as graduate electives, only with prior approval of the Graduate Curriculum Committee.
No more than 9 credits of coursework taken as a non-degree special student may subsequently be credited toward the graduate degree.
Students must meet the university graduate requirement of at least a 3.0 grade point average; only courses graded C or better may count toward the degree.
Students doing a Master’s Thesis will prepare and defend their thesis to a faculty committee.
As many as three online courses may be used towards the Master’s degree.