The University of Kansas offers a Master of Science in Computer Science through the Department of Electrical Engineering and Computer Science in the School of Engineering.
The 31-credit degree is taught on the Lawrence campus and can be finished with a thesis, a project, or coursework only. Machine learning is not required of every student. It enters the degree through electives such as Machine Learning, Advanced Data Science, and Computer Vision, which students choose with a faculty adviser.
Last reviewed: October 2026
Quick Facts
| Degree | MS in Computer Science |
| School | Department of Electrical Engineering and Computer Science, School of Engineering |
| Location | Lawrence, Kansas |
| Format | On campus |
| Credits | 31 |
| Culminating Experience | Thesis, project, or coursework only |
| Minimum GPA | 3.0 |
| GRE | Optional |
| Tuition | $501.80 per credit hour for Kansas residents, plus a $95 engineering course fee per credit hour |
| Priority Deadlines | December 15 (fall), September 30 (spring) |
| Typical Length | About two years |
| STEM Designated | Yes |
Official EECS master’s programs page
Curriculum
KU does not offer a standalone master’s degree in machine learning or artificial intelligence through the School of Engineering. Students earn the MS in Computer Science and build a machine learning plan from the department’s graduate course list. The catalog lists no formal tracks or concentrations.
Students complete 31 graduate credits consisting of:
- 1 credit of required coursework, the department colloquium
- 24 credits of computer science graduate coursework, at least eight courses from the department’s graduate course list
- 6 credits for the completion option, a thesis, a project plus one course, or two additional courses
No more than two courses at the 500 or 600 level count toward the degree, and one course from outside the department may be approved by petition. Students file a Plan of Study in their first semester.
Required Course
- EECS 802 – Electrical Engineering and Computer Science Colloquium and Seminar on Professional Issues
This 1-credit colloquium is the only course every student must take. Because the rest of the plan is chosen from a department-wide list, it is possible to finish the degree without a machine learning course.
Machine Learning and Data Science Electives
The graduate course list includes these 700 and 800 level courses, each for 3 credits:
- EECS 730 – Introduction to Bioinformatics
- EECS 740 – Digital Image Processing
- EECS 767 – Information Retrieval
- EECS 835 – Advanced Data Science
- EECS 836 – Machine Learning
- EECS 841 – Computer Vision
- EECS 868 – Mathematical Optimization with Applications
EECS 836 covers Bayesian decision theory, dimensionality reduction, clustering, neural networks, hidden Markov models, reinforcement learning, and Bayesian learning. EECS 835 is a project-oriented survey of data collection, transmission, and analysis.
Three introductory courses are also on the list, but they fall under the two-course limit on 500 and 600 level work:
- EECS 568 – Introduction to Data Mining
- EECS 649 – Introduction to Artificial Intelligence
- EECS 658 – Introduction to Machine Learning
The list has no course titled deep learning or natural language processing.
Other Elective Areas
The same list covers the rest of the department, so students can combine machine learning with courses such as:
- EECS 739 – Parallel Scientific Computing
- EECS 750 – Advanced Operating Systems
- EECS 764 – Analysis of Algorithms
- EECS 765 – Introduction to Cryptography and Computer Security
- EECS 766 – Network Security
- EECS 844 – Adaptive Signal Processing
- EECS 861 – Random Signals and Noise
The department encourages computer science students to choose a focus area early. The areas it lists are Computational Science and Engineering, Data Science and Engineering, Cybersecurity, Computer Systems Design, Languages and Semantics, Theory of Computing, and Computing in the Biosciences.
Thesis, Project, or Coursework
- Thesis: EECS 899 – Master’s Thesis for 6 credits, with an oral defense in the final semester
- Project: EECS 891 – Graduate Problems for 3 credits plus one additional course, with an oral defense and a written project document
- Coursework only: two additional courses, for 10 courses and 30 credits of graduate coursework plus the colloquium
The department also offers a coursework-only Master of Engineering in Electrical Engineering and Computer Science, which draws on the same course list.
Cost and Tuition
KU charges graduate tuition by the credit hour, with separate rates for Kansas residents and nonresidents. School of Engineering courses carry an additional course fee per credit hour.
For the 2026–27 academic year, the Registrar lists these rates for the Lawrence campus:
| Category | Kansas Resident | Nonresident |
|---|---|---|
| Graduate tuition, per credit hour | $501.80 | $1,176.10 |
| Engineering course fee, per credit hour | $95.00 | $95.00 |
| Tuition and course fee, per credit hour | $596.80 | $1,271.10 |
| Estimated 31-credit total, tuition and course fee | $18,501 | $39,404 |
Graduate students also pay required campus fees each semester. At six or more credit hours in fall or spring, the required student fee is $287.10 and the wellness fee is $245.40, for $532.50 per semester.
The totals above are estimates based on 31 credits and do not include required campus fees, the application fee, books, or living costs. Rates can change each year, so students should confirm current costs with the Registrar.
View University of Kansas tuition and fees
Admission Requirements
Applicants need a bachelor’s degree from a regionally accredited institution or an equivalent degree from another country. Most applicants hold a degree in computer science or a related field.
The department expects a GPA of 3.0 or higher on a 4-point scale.
Applicants with degrees in other fields may be assigned undergraduate prerequisite courses by the department’s Graduate Studies Committee. These courses must be completed before graduate coursework and do not count toward the degree.
Application Materials
Applicants submit:
- online graduate application and application fee ($65 domestic, $100 international)
- statement of objectives and resume
- official transcript
- three letters of recommendation
- TOEFL or IELTS scores for international applicants
- financial statement for international applicants
GRE scores are optional. The department’s 2026–27 graduate handbook describes them as highly recommended and says that scores, when submitted, are used in admission, scholarship, and assistantship decisions.
The catalog states that the department’s English proficiency standard is higher than the general KU requirement. The department’s master’s page lists a TOEFL internet-based score of 90 or higher.
Application Deadlines
| Entry Term | Priority Deadline | Final Deadline |
|---|---|---|
| Fall | December 15 | March 1 |
| Spring | September 30 | October 1 |
Applicants who apply after the priority deadline may not be considered for fellowships or assistantships. These dates come from the department’s master’s page and its 2026–27 graduate handbook. The 2026–27 catalog lists later final dates of April 1 for fall and November 1 for spring, so applicants should confirm the deadline with the department.
Program Format
The MS in Computer Science is taught in person on the Lawrence campus. The department does not list an online option for this degree.
The department says its master’s programs are intended to take about two years to complete. Students can enter in fall or spring.
KU’s International Student Services lists the Computer Science MS among the KU degrees on the federal STEM list, which allows eligible international students to apply for the STEM OPT extension.
The department reports that more than 75 percent of its graduate students receive assistantships or fellowships. That figure covers all of the department’s graduate students, including doctoral students.
Who Is This Program Best For?
The University of Kansas MS in Computer Science is a strong option for students who want machine learning inside a flexible, research-oriented computer science master’s degree at a public university.
It may be especially appealing to students interested in:
- machine learning and data science electives chosen with a faculty adviser
- computer vision, image processing, and information retrieval
- a thesis or project as preparation for doctoral study
- combining machine learning with cybersecurity, systems, or signal processing courses
- a STEM-designated degree with optional GRE scores
- assistantship and fellowship funding on a research campus
The degree is a computer science master’s first. Machine learning is a choice within it, not a requirement, and the course list has a small number of machine learning courses and none titled deep learning or natural language processing. It is also a campus program with no online option. Students who want a degree built entirely around AI, who need online study, or who lack a computing background may want to compare other Kansas schools or KU’s online MS in Applied Statistics, Analytics and Data Science.
Official University of Kansas Program Links
- EECS master’s programs page
- Academic catalog entry
- EECS graduate programs
- Data Science and Engineering focus area
- KU graduate application
- English proficiency requirements
- STEM OPT extension information
- Tuition and fees
Related Machine Learning Programs in Kansas
Students can also compare University of Kansas with other master’s programs in machine learning, artificial intelligence, and related fields offered in Kansas.
- Fort Hays State University – Hays
- Kansas State University – Manhattan
- Ottawa University – Overland Park
- Pittsburg State University – Pittsburg
- Wichita State University – Wichita