M.S. in Robotics Coursework
Take classes in several departments across the College of Science and Engineering as part of the M.S. in Robotics program. We pair real-world issues with an educational setting, and our industry collaboration allows students to connect to multiple outlets in Minnesota companies and beyond.
Course Listing
This Minnesota Robotics Program is structured to be completed across three semesters, culminating in a total of 31 credits. Candidates are required to complete one course from each key area, amounting to 9 to 10 credits, selected from a designated shortlist of foundational courses respective to each area. The remaining credits will be allocated toward the capstone project (3 to 6 credits), thesis (10 credits), or the Robotics Colloquium (1 credit). Additional credits may be earned through elective courses offered by participating departments.
You can view more information about each course in the University of Minnesota's M.S. in Robotics program catalog.
Course | Enforced Prereq |
| CSCI 5511 - Artificial Intelligence I | Graduate Student Standing |
| CSCI 5512 - Artificial Intelligence II | Stat 3021 and (CSci 3041 or 4041)) or Graduate Student Standing |
| CSCI 5521 - Introduction to Machine Learning | STAT 3021, (CSci 2033 or Math 2142 or Math 4242) |
| CSCI 5525 - Machine Learning | CSci 5521 |
| CSCI 5561 - Computer Vision | CSci 5521 |
Robotics Colloquium (1 credit) — Required
The Robotics Colloquium will serve as an introductory course wherein new students will be introduced to the fundamentals of robotics and sensing. Additionally, they will gain insights into the industry, potential opportunities, and how the Master's program at the Minnesota Robotics Institute can be beneficial for them.
Key Areas (9 to 10 credits total) — Choose one (1) from each area.
- Cognition
- Computer Science 5511 - Artificial Intelligence I (3 cr)
- Computer Science 5512 - Artificial Intelligence II (3 cr)
- Computer Science 5521 - Intro to Machine Learning (3 cr)
- Computer Science 5525 - Machine Learning: Analysis and Methods (3 cr)
- EE 5521 - Machine Learning & Data Science for ECE and ROB Students (3 cr)
- Perception
- Computer Science 5561 - Computer Vision (3 cr)
- Electrical Engineering 5271 - Robot Vision (3 cr)
- Electrical Engineering 5561 - Image Processing and Applications (3 cr)
- Robot Modeling and Control:
- Computer Science 5551 - Introduction to Intelligent Robotic Systems (3 cr)
- Computer Science 5552 - Sensing/Estimation in Robotics (3 cr)
- Mechanical Engineering 5286 - Robotics (4 cr, includes a lab)
- Electrical Engineering 5231/Aerospace Engineering and Mechanics - 5321 Linear Systems and Optimal Control/Modern Feedback Control (3 cr)
Final Projects — Choose one (1), either Plan A: Master's Thesis OR Plan B: Capstone project
Plan A: Master's Theses (10 cr): Master’s theses (Plan A) will be supervised by a faculty advisor and adhere to university regulations. Students are required to assemble a committee comprising at least three faculty members, compose a thesis, and present an oral defense before their committee. The Master’s thesis is advantageous for students contemplating a future transfer to a Ph.D. program or seeking a more extensive research experience. Please refer to the Plan A student planning checklist for definitive grade and credit requirements, milestones, and policy procedures.
Plan B: Capstone Project (3 - 6 credits): Capstone projects are overseen by faculty members and may involve collaboration with industry partners. A capstone project generally requires a minimum of one semester (3 credits for the Plan B course), with the possibility of extension to a second semester. Students are expected to compile their work into a comprehensive final report and deliver a presentation via video to their final examination committee, consisting of three faculty members. Please refer to the Plan B student planning checklist for definitive information regarding grade and credit requirements, milestones, and policy procedures associated with Plan B.
Elective Courses (fill in credit total to 31 credits) — Choose up to six (6) additional classes
Students may also use courses from the key areas below as electives, though a course can count toward only one requirement: the program's core course requirement or the elective requirement, not both.
Please visit the Student Handbook to view the current list of approved elective courses. If there is a course you would like to take as an elective that is not approved, you can submit an approval request using the link here.
Key Areas:
- Aerospace Engineering and Mechanics
- Biomedical Engineering
- Computer Science
- Design
- Electrical Engineering
- Finance
- Industrial and Systems Engineering
- Human Factors
- Mechanical Engineering
- Product Design
- Psychology
- Robotics
Industry and Academic Collaboration
Courses are paused during the summer months to facilitate student participation in highly esteemed and competitive internships and programs within the industry.
As previously outlined in the benefits section, MnRI faculty maintain connections with prominent industries and leading companies within Minnesota and internationally. Currently, on-campus personnel from Honeywell are being integrated. The State of Minnesota provides extensive research opportunities, supported by substantial local presence from corporations such as 3M, Amazon, Honeywell, Toro, General Mills, Boston Scientific, Medtronic, Land O'Lakes, among others.
MnRI benefits from extensive connections with approximately thirty-six faculty members throughout the University of Minnesota. Nevertheless, these collaborations extend beyond the Twin Cities. The institution hosts nearly weekly presentations by international speakers discussing their research and pertinent issues within the robotics industry, while also engaging in collaborations with various educational and governmental organizations.