MS Artificial Intelligence Concentration Requirements

MS on campus students wishing to add the Artificial Intelligence Concentration to their MS degree are asked to submit the application and are required to:

  • Complete 30 course credits meeting the AI Course Requirements (courses taken to satisfy core/elective requirements are included)
  • Satisfy all MS in CS core/course requirements (courses taken to satisfy AI requirements are included)
  • Satisfy two AI Fundamental Requirements
  • Satisfy three AI Elective Requirements

AI Course Requirements

1. Elective Requirements
You must have satisfied three AI Elective requirements. All courses taken must earn a B or better in them. 

2. Fundamental Requirements
You must have satisfied two AI Fundamental requirements. This requirement is usually satisfied by taking courses and earning a B or better in them.

3. Credits
You must take a total of 30 credits with the following restrictions:

  • No more than 18 of the course credits may come from courses at the 500 level. 500-level classes taken to satisfy core requirements fall into this group.
  • At least 12 of those credits must come from courses at the 600-900 level that are not independent studies. 600-level classes taken to satisfy core requirements fall into this group.
  • No more than 12 credits may come from independent studies.
  • No more than nine credits may come from courses outside of the Computer Science Department. (Credit for graduate courses from other departments must be approved by the GPD.)
  • No more than six credits may come from independent studies, practicums and/or SAT (Also known as Pass/Fail). The SAT option for graduate students is only allowed by instructor consent.
  • Classes with a grade below a C may not be counted toward the MS degree.
  • Only a limited number of credits may be transferred from other programs or institutions.

4. GPA

Your overall grade point average for those 30 credits must be 3.0 or higher.

AI Core Requirements

All AI Fundamental courses can be used toward the CompSci MS core requirements.

The AI fundamental courses provide the mathematical, algorithmic, and conceptual underpinnings of AI, emphasizing principles, theoretical foundations, and algorithms.

The following courses can be used to complete the AI Fundamental requirements:

  • COMPSCI 589 Machine Learning
  • COMPSCI 651 Optimization for Computer Science
  • COMPSCI 682 Neural Networks: A Modern Introduction
  • COMPSCI 683 Artificial Intelligence
  • COMPSCI 687 Reinforcement Learning
  • COMPSCI 689 Machine Learning

AI Elective Requirements

Students must complete three of the following courses with a grade of B or better. Courses that are crossed-listed as core and elective may only satisfy one area requirement. 

  • COMPSCI 524 Health Informatics and Data Science
  • COMPSCI 546 Applied Information Retrieval
  • COMPSCI 585 Introduction to Natural Language Processing
  • COMPSCI 590ED Educational Data Mining and Learner Analytics
  • COMPSCI 590L Making Predictions
  • COMPSCI 590OP Applied Numerical Optimization
  • COMPSCI 603 Robotics
  • COMPSCI 646 Information Retrieval
  • COMPSCI 650 Applied Information Theory
  • COMPSCI 670 Computer Vision
  • COMPSCI 685 Advanced Natural Language Processing
  • COMPSCI 688 Probabilistic Graphical Models
  • COMPSCI 690AB Systems for Deep Learning
  • COMPSCI 690K Advanced Robot Dynamics and Control
  • COMPSCI 690L Deep Generative Models
  • COMPSCI 690S AI Alignment
  • COMPSCI 690U Computational Biology and Bioinformatics

The concentration equips students with a strong grounding in the theoretical foundations and practical skills necessary to design, analyze, and deploy AI algorithms and systems.

The concentration is intended for students pursuing careers in industry, research, or further doctoral study in AI-related fields.