M.S. Plan B

The Plan B option replaces the requirement of a formal thesis with a project defense and an increased course load. Consult with your advisor about this option. Refer to the Master's admissions guidelines for minimum requirements.

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MS in Electrical Engineering

The Plan B student must do a presentation to their committee about their project OR conference/journal paper OR course work.

The following documentation is associated with the plan B option:

Plan B Credit Allocation (30 Hrs. minimum - all at 4000 level minimum):

  • Minimum 18 Course Hrs in Electrical and Computer Engineering Course Work
  • Minimum 3 Course Hrs in Formal Course Work outside the Electrical and Computer Engineering Department
  • 9 Additional Formal Course Hrs in or out of the Electrical and Computer Engineering Department
  • No more than 12 credit hours can be at the 4000 level
  • No more than 3 credit hours of independent study

See Course Catalog

MS in Computer Science

The student must complete a minimum of 33 credit hours of courses, including the CORE &  BREADTH REQUIREMENTS. At least 22 credit hours must be COSC courses. All COSC courses must be at the 5000 level. Courses from other departments, including no more than 6 hours of 4000-level courses, may be included with the approval of the supervising M.S. committee.

UW Coursework Requirements for M.S. Transfer Students: M.S. transfer students must complete at least 21 credit hours at the University of Wyoming. At least 12 credits of the CORE & BREADTH REQUIREMENTS must be taken at the University of Wyoming. No more than one class per category of breadth may be counted towards this 12-credit total. The algorithms course credits may be counted toward this 12-credit total.

Summary of Credit Requirements

  • Core: COSC 5110: 3
  • Breadth: theory course, AI course, two systems courses: 12
  • Additional courses: 18
  • Thesis/Dissertation (COSC 5960/5980): 0
  • Other credits (may include courses or COSC 5960/5980): 0
  • Total: 33

See Course Catalog

MS in Artificial intelligence (AI)

The Plan B degree program, a non-thesis option, consists of 28 hours of required coursework credits and two hours of seminar credits. A student pursuing the Plan B degree program as part of the 28 hours of required coursework credits can do an independent study project at the graduate level of a maximum of three credits.

Summary of Credit Requirements

Core Courses (9 Credits): Complete core courses from the core course list below:

  • COSC 5550: Introduction to Artificial Intelligence, Credits: 3.0
  • COSC 5555: Machine Learning, Credits: 3.0
  • EE 5410: Neural Networks, Credits: 3.0
  • MATH 4500, Matrix Theory, Credits: 3.0
  • STAT 5380, Bayesian Data Analysis, Credits: 3.0

Elective Courses (19 Credits):

  • EE 5440, Geometric and Deep Computer Vision, Credits: 3.0

  • COSC 5557, Practical Machine Learning, Credits: 3.0

  • EE 5885, Explainable AI, Credit: 3.0

  • EE 5885, AI for Multi-agent Systems, Credits: 3.0

  • EE 5885, Advancement in 3D Computer Vision, Credits: 3.0

  • EE 5885, Deep Reinforcement Learning and Control, Credits: 3.0

  • EE 5885, Cooperative Robotics, Credits: 3.0

  • EE 5885, AI and Game Theory for Machines

  • EE/COSC 5880 – Independent Study, Credits: 1.0 to 3.0

  • COSC 4800*, Introduction to Deep Learning, Credits: 3.0

  • EE/COSC 5885/5010, Introduction to LLMs

  • EE/COSC 5885*, Advanced Deep Learning, Credits: 3.0

  • EE/MATH 5885*, Mathematics for Machine Learning, Credits: 3.0

  • EE/COSC 5885/5010, Neurosymbolic AI

  • EE 5885, Directive-Based Parallel Programming

Seminar Courses: Credits: 2.0

  • COSC 5552, Advanced Topics in AI, Credits: 1.0
  • Course*, Credits: 1.0

*- New courses to be developed

Thesis Credits: EE/COSC 5960, Credits: 4.0

 

AI/ML Teaching Faculty:

1. Diksha Shukla, Associate Professor, EECS

2. Zejian Zhou, Assistant Professor, EECS

3. Shivanand Sheshappanavar, Assistant Professor, EECS

4. Chao Jiang, Associate Professor, EECS

5. Yaqoob Majeed, Assistant Professor, EECS

6. Dane R. Taylor, Assistant Professor, School of Computing

7. Lars Kotthoff, Associate Professor, EECS

8. John E. McInroy, Professor, EECS

9. Suresh Muknahallipatna, Professor, EECS