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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 5625ÌýÌýÌý
Artificial Intelligence CAP 6635ÌýÌýÌýÌý
Data Mining and Machine Learning CAP 6673ÌýÌýÌýÌý

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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 6411ÌýÌýÌý
Computer Vision CAP 6415ÌýÌýÌý
Machine Learning for Computer Vision CAP 6618ÌýÌýÌý
Visual Information Retrieval COP 6728ÌýÌýÌý

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Data Analytics and Algorithms

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

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Knowledge Management and Reasoning

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

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Machine Learning

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

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Applications

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

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