Artificial Intelligence (AIG) Subplan Requirements

Degree Requirements

• Students enrolled in the Professional MS in Computer Science (MSCPS) program with the Artificial Intelligence (AIG) subplan must complete 30 credit hours of graduate coursework according to the degree requirements listed on the MSCPS degree requirements, including the requirements for the AIG subplan:
  • 9 hours - Bin/Breadth courses
    • You must earn a grade of ‘B’ or better to satisfy each of the three BIN/breadth course requirements.
  • 6 hours - Project courses
    • Students must complete both project courses from one project course sequence.
    • Students must earn grades of ‘B’ or better in both courses.
    • Students cannot count just one project course to the degree.
  • 15 hours - Elective courses
    • You may take up to two, approved, non-CS courses.
    • Any non-Computer Science courses that can count towards a subplan will count against the two maximum allowable non-CS classes.
  • AIG Subplan courses
    • Must complete at least 12 credit hours of eligible AIG subplan courses with a grade of ‘B’ or better.
  • Counting courses for the AIG subplan
    • Students can satisfy subplan requirements by counting eligible BIN and/or Elective courses towards the AIG subplan requirements. This means:
      • Students may count an eligible course towards BOTH a BIN/breadth requirement AND an AIG subplan requirement.
      • If the student does not need to count an eligible course towards the breadth/bin requirement, the course can count towards BOTH an elective requirement AND an AIG subplan requirement.
    • For example, if a student got a grade of ‘B’ or higher in CSCI 5832:
      • …and still needed to complete their Bin 2 requirement - they could count CSCI 5832 as BOTH their Bin 2 course and as an AIG subplan course.
      • …and already completed their Bin 2 requirement - they could count CSCI 5832 as BOTH an Elective course and as an AIG subplan course.

Artificial Intelligence (AIG) Subplan Course Options

• CSCI 5202/ROBO 5000 - Intro to Robotics
• CSCI 5214 - Big Data Architecture
• CSCI 5254 - Convex Optimization
• CSCI 5302 - Advanced Robotics
• CSCI 5322 - Algorithmic Human-Robot Interaction
• CSCI 5352 - Network Analysis and Modeling
• ​CSCI 5434 - Probability for Computer Science
• CSCI 5502 - Data Mining
• CSCI 5622 - Machine Learning
• CSCI 5673 - Distributed Systems
• CSCI 5722 - Computer Vision
• CSCI 5822 - Probabilistic Models of Human and Machine Learning
• CSCI 5832 - Natural Language Processing
• CSCI 5922 - Neural Networks and Deep Learning
• CSCI 7000 - Special Topics - Robot Perception
• CSCI 7000 - Special Topics - Reinforcement Learning
• CSCI 7000 - Special Topics - Physical Human Robot Interaction
• APPM 8500 - Statistics, Optimization, and Machine Learning Seminar