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.

Vision

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

 

Applications

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.