Northern Arizona University offers a Master of Science in Computer Science through the School of Informatics, Computing and Cyber Systems in Flagstaff.
The 30-unit program is broader than a dedicated machine learning master’s degree, but students can use the flexible curriculum to build substantial expertise in machine learning, artificial intelligence, and data science.
Quick Facts
| Degree | Master of Science in Computer Science |
| School | School of Informatics, Computing and Cyber Systems |
| Location | Flagstaff, Arizona |
| Credits | 30 units |
| Format | Campus |
| Machine Learning Concentration | No formal concentration |
| Thesis | Thesis and non-thesis options |
| Minimum GPA | 3.0 |
| Accelerated Option | Available to eligible NAU undergraduates |
View the official MS in Computer Science program
Program Overview
Northern Arizona University’s MS in Computer Science gives students considerable flexibility in choosing advanced computer science coursework.
The program covers areas including:
- machine learning and data science
- artificial intelligence
- cybersecurity
- computer networks
- high-performance computing
- software engineering
- software architecture and testing
Students can choose between thesis and non-thesis options. The non-thesis route is geared more toward professional preparation, while the thesis option provides additional research experience for students considering doctoral study or research careers.
The degree requires 30 units. Students complete one required computer science course and then build the remainder of the program primarily through electives.
Machine Learning and AI Coursework
NAU does not offer a named machine learning concentration within the MS in Computer Science. Instead, students can select machine learning and AI courses as part of their graduate coursework.
Relevant courses include:
CS 570 – Artificial Intelligence
This graduate-level AI course covers core artificial intelligence concepts, including knowledge representation, planning, game playing, learning, and genetic algorithms.
CS 572 – Unsupervised Machine Learning
This course focuses on learning from unlabeled data. Topics include clustering, Gaussian mixture models, change point detection, and dimensional reduction.
CS 573 – Interpretable Machine Learning
Students study machine learning methods that combine predictive performance with understandable results. Topics include sparse linear models, decision trees, nearest-neighbor methods, and model-agnostic methods for interpreting predictions.
INF 504 – Data Mining and Machine Learning
This graduate informatics course covers machine learning with an emphasis on uncertainty modeling, Bayesian inference, graphical models, message passing, Markov Chain Monte Carlo methods, and current research problems.
Course availability and prerequisites vary, so students interested in building an ML-heavy curriculum should confirm their planned electives with the program before enrolling.
Curriculum
The MS in Computer Science requires 30 units.
Students select either CS 552 or INF 503 for the program’s three-unit computer science coursework requirement. The remaining 27 units depend on the student’s thesis or non-thesis path.
The program requires a significant amount of formal, letter-graded coursework, including graduate-level CS courses. Thesis students can devote a larger portion of the degree to research.
This structure makes the program especially useful for students who want a broad graduate education in computer science while choosing several courses related to machine learning and AI.
Thesis and Non-Thesis Options
Students can select a path based on their career and research goals.
Non-thesis students primarily complete coursework and can use electives to develop expertise in areas such as machine learning, AI, cybersecurity, or software engineering.
Thesis students work on a research project under faculty mentorship and prepare and defend a master’s thesis. This route may be a better fit for students considering research positions or a PhD.
Admissions
Applicants should have a bachelor’s degree in computer science or a related field.
NAU’s general graduate admission standard includes an undergraduate GPA of at least 3.0 on a 4.0 scale.
Computer Science students must also satisfy the program’s Computer Science Milestone. Students can do this by passing the Initial Skills Inventory Exam or completing CS 500 and CS 501 before beginning graduate-level CS coursework.
NAU lists additional application requirements in its current catalog, and requirements are changing for students applying for Fall 2027 and later. Prospective students should verify the requirements for their intended entry term directly with the university.
View NAU’s current admission requirements
Tuition and Cost
Northern Arizona University charges different graduate tuition rates based on residency.
For the 2026–27 academic year, NAU estimates full-time Flagstaff graduate tuition and mandatory fees at approximately:
| Residency | Tuition + Mandatory Fees per Semester* |
|---|---|
| Arizona Resident | $7,604 |
| Out-of-State / International | $17,713 |
*Based on NAU’s 2026–27 graduate financial aid planning figures. Program fees may be additional.
Actual degree cost depends on residency, enrollment load, program fees, and the number of semesters required to complete the 30-unit degree.
View current NAU graduate tuition and fees
Who Is This Program Best For?
Northern Arizona University’s MS in Computer Science is a good option for students who want a broad computer science master’s degree with the ability to pursue graduate coursework in machine learning and AI.
It may be particularly appealing to students who:
- want access to machine learning courses without committing to a narrowly focused ML degree
- have a computer science or closely related undergraduate background
- want the choice between a professional coursework path and a research-oriented thesis
- may eventually pursue doctoral study
- want to study on NAU’s Flagstaff campus
Students specifically looking for a degree titled Machine Learning or a formal ML concentration should compare NAU with programs that offer a dedicated specialization.
Related Machine Learning Programs in Arizona
Compare Northern Arizona University with other machine learning master’s programs in Arizona, including:
- Arizona State - Tempe
- Avila University - Goodyear
- University of Arizona - Tucson