M.S. in Computer Science: Artificial Intelligence

Major Requirements (6 Credits/2 classes)

The following two (2) courses are required by the program:

Either class above can be substituted with another graduate course under the discretion of GPD if students had their equivalent in their undergraduate program.

Artificial Intelligence Concentration (12 Credits/4 classes)

Note

COMP 479: Machine Learning is a required course for the Artificial Intelligence Concentration

One (1) of the following courses

COMP 429: Natural Language Processing

COMP 487: Deep Learning

COMP 488: Topics in Computer Science (Artificial Intelligence related topics)

Two (2) of the following courses

COMP 406: Data Mining

COMP 429: Natural Language Processing

COMP 458: Big Data Analytics

COMP 487: Deep Learning

COMP 488: Topics in Computer Science (Artificial Intelligence related topics)

Note

Topics in Machine Learning is the specific section of COMP 488: Topics in Computer Science to be taken.

The department may declare that other newly created permanent courses may count. Similarly, some Topics in Computer Science offerings (temporary courses) may also be designated. Students are responsible for verifying any such substitutions in advance with their Graduate Program Director.

General Electives (12 Credits/4 classes)

MSCS students must take 12 credits of other electives.

Electives can be any COMP 400 level class, except the preparation courses (COMP 400A, COMP 400B, COMP 400C, COMP 400D, COMP 400E)

General electives include any COMP 400 level course. The elective course options are common for all programs, differing only in the total number of credits required.

There are numerous options for independent study, including a programming project, research, or a service-oriented project.

Note

Students may take up to a maximum of 6 credit hours of COMP 490: Independent Project and/or COMP 499: Internship.