MS Artificial Intelligence - Graduate Courses

Core Courses

Students are required to select 2 courses from the following 3 courses:

Title Course No.
Computational Foundations of Artificial Intelligence CAP 5625   
Artificial Intelligence CAP 6635    
Data Mining and Machine Learning CAP 6673    


In addition, students pursuing the non-thesis option are required to take 4 AI Electives and 4 EECS Electives. Students pursuing the thesis option must take 2 AI Electives, 6 thesis credits, and 4 EECS Electives.

AI Electives – courses are structured in the following areas: Vision, Data Analytics and Algorithms, Knowledge Management and Reasoning, Machine Learning, and Applications.


Title Course No.
Foundations of Vision CAP 6411   
Computer Vision CAP 6415   
Machine Learning for Computer Vision CAP 6618   
Visual Information Retrieval COP 6728   


Data Analytics and Algorithms

Title Course No.
Introduction to Data Science CAP 5768   
Social Networks and Big Data Analytics CAP 6315   
Data Mining for Bioinformatics CAP 6546   
Big Data Analytics with Hadoop CAP 6780   
Computer Performance Modeling CEN6405
Analysis of Algorithms COT 6405   


Knowledge Management and Reasoning

Title Course No.
Natural Language Processing CAP 6640   
Information Retrieval CAP 6776   
Web Mining CAP 6777   
Semantic Web Programming COP 5859   


Machine Learning

Title Course No.
Introduction to Neural Networks CAP 5615   
Evolutionary Computing CAP 6512   
Sparse Learning CAP 6617      
Deep Learning CAP 6619      
Advanced Data Mining and Machine Learning COP 6778      



Title Course No.
Robotic Applications EEL 5661      
Artificial Intelligence in Medicine and Healthcare CAP 6683     
Computational Advertising and Real-time Data Analytics CAP 6807       


EECS Electives – graduate courses offered by the EECS department. Course substitution is allowed with prior approval of the advisor.