The following requirements must be fulfilled: Non-Thesis option—30 credits, including 12 credits in required courses and 18 credits in elective courses. Thesis option—30 credits, including 12 credits in required courses and 12 credits in elective courses, and 6 credits in thesis.

At least 24 of the 30 credits must be taken at the 6000 level or above. At least 24 of the 30 credits must be taken in the Department of Computer Science. 

Required
CSCI 6212Design and Analysis of Algorithms
CSCI 6364Machine Learning
CSCI 6366Neural Networks and Deep Learning
CSCI 6510Trustworthy AI
Electives
CSCI 6365Advanced Machine Learning
CSCI 6511Artificial Intelligence
CSCI 6513Natural Language Processing
CSCI 6514Large Language Models
CSCI 6527Introduction to Computer Vision
CSCI 6443Data Mining
CSCI 6444Introduction to Big Data and Analytics
ECE 6882Reinforcement Learning
BME 6830Introduction to Medical Imaging Methods
BME 6840Digital Image Processing
Additional electives for non-thesis option
Non-thesis students take two additional elective courses (6 credits). These can be any CSCI courses numbered 6200 and above, graduate-credit-bearing courses from math, statistics, neuroscience, physics, or any SEAS departments, subject to approval of the faculty advisor.A non-thesis option student can take up to two CSCI 6908 Research courses.
Thesis Option
A thesis option student may not take CSCI 6908 Research course but instead must take CSCI 6998 Thesis research and CSCI 6999 Thesis Research

This program can be used with the BA+MS or BA+MS (4+1) program, where up to two classes may be double-counted between the BA/BS and the MS, and where the BS/BA can be in any major in SEAS

Scholarship requirements:

At least a 3.0 GPA overall. A student who receives two or more grades of F will be dismissed from the program. A student who receives three or more grades below B- will be dismissed from the program.