Effective September 2012
For Ph.D. Students beginning in Fall 2012
In addition to the general exam, the requirement must be satisfied: breadth.
A total of 6 courses will be required. The first three constitute the core breadth requirement. You must take one course from each group -- AI, Systems, and Theory -- from the courses listed below. The remaining three courses can be any 400 or 500-level course from any department in the University, or with approval required from your academic advisor and the Director of Graduate Studies for courses outside of Computer Science. (Please note for Fall 2018 only: ELE 396 will also count as one of the "remaining three courses")
All courses must be taken for a grade. A grade of B+ or higher is required to get credit towards course requirements, although at most one B will be accepted for a course that does not satisfy the core breadth requirements.
Individual research areas may set additional requirements for their students; they may specify certain courses to be taken or may require that courses in excess of the departmental requirement be taken.
Core Course List
- 402 Artificial Intelligence
- 424 Fundamentals of Machine Learning
- 485 Neural Networks
- 511 Theoretical Machine Learning
- 513 Foundations of Probabilistic Modeling
- 475 Computer Architecture (See ELE 475)
- 518 Advanced Computer Systems
- 561 Advanced Computer Networks
- 510 Programming Languages
- 516 Automated Reasoning About Software
- 521 Advanced Algorithm Design
- 522 Computational Complexity
To be readmitted you must satisfy the following schedule:
- Year 1: Successful completion of 3 courses + research progress
- Year 2: Successful completion of 4th course (including all three core breadth courses) + general exam
- Year 4: Successful completion of last two courses, for a total of 6
The Master of Arts degree can be awarded after successfully completing all the year 2 requirements -- 3 core courses, one additional course, and passing the general exam.