Ph.D. in Data Science
The doctoral students in Data Science are required to take the same 10 core courses as in the M.S. program, as well. Furthermore, the doctoral students will need to take at least 2 electives (any letter-graded courses) from AMS or CS departments, plus an additional 42 credits of electives (including at least 18 thesis research credits) to satisfy the minimum 78-credit Ph.D. program requirement. A doctoral student will take the written doctoral qualifying exam at the end of their first academic year. The doctoral qualifying exam consists of a 3-hour CS foundation exam, and a 3-hour Data Mining exam. These two exams will be held at the end of May/beginning of June - based on the following eight Data Science core courses taught in the first year of the Data Science Graduate Program under the usual Fall admission:
- AMS 507 Probability
- AMS 572 Data Analysis
- AMS 580 Statistical Learning
- AMS 597 Statistical Computing
- CSE 581, Computer Science Fundamentals: Theory
- CSE 582, Computer Science Fundamentals: Data Structures and Algorithms
- CSE 583, Computer Science Fundamentals: Programming Abstractions
- ISE 503 Data Management.
The Data Science program provides a pathway for M.S. students to transfer to the Ph.D. program upon completing the set of eight core courses with GPA >= 3.5 and passing the doctoral qualifying exam.