Engineering-focused machine learning master’s programs combine advanced computing with the design, deployment, and application of intelligent systems. The programs below have a meaningful engineering component alongside machine learning, artificial intelligence, data science, or signal processing.
Our current inventory includes 6 master’s programs classified under engineering. Use the table to compare degree type, location, delivery format, tuition, and program length. Each school links to a detailed profile with curriculum, admissions, and cost information.
Engineering-Focused Machine Learning Master’s Programs
| School | Location | Degree | Format | Tuition | Length |
|---|---|---|---|---|---|
| Dartmouth Engineering | Hanover, NH | Master of Engineering (MEng), Artificial Intelligence | campus | $71,697 | 9 months |
| Duke University | Durham, NC | MS or MEng in Electrical & Computer Engineering | campus | $107,040 | 3-4 semesters |
| Milwaukee School of Engineering | Milwaukee, WI | Master of Science in Machine Learning | online | $52,992 | 12 Months |
| North Carolina A&T State University | Greensboro, NC | M.S. in Data Science and Engineering | Online | $303/credit in-state | 2–3 semesters |
| University of Cincinnati | Cincinnati, OH | MEng in Artificial Intelligence | Campus | $7,955 per term | 12 months |
| University of Wisconsin | Madison, WI | Machine Learning and Signal Processing | campus | $33,000 | 12 Months |
What Makes a Program Engineering-Focused?
Engineering programs usually place more emphasis on building systems than on analysis alone. Coursework may cover machine learning, artificial intelligence, software systems, optimization, embedded or electrical systems, signal processing, model deployment, and engineering design.
For this directory, we use the engineering classification when engineering is part of the degree, formal track, or substantial curriculum. A single engineering elective is not enough.
Engineering vs. Data Science
Data science programs often focus on statistics, data preparation, analysis, visualization, and predictive modeling. Engineering-focused programs tend to put more weight on designing, implementing, integrating, and deploying technical systems.
The categories overlap. A data science and engineering degree can fit both classifications, while an electrical or computer engineering degree may combine machine learning with signal processing, hardware, or software systems.
How to Compare Engineering Programs
Check the degree structure. Determine whether machine learning is a formal track, concentration, required core, or a set of electives inside a broader engineering degree.
Compare technical depth. Look for multiple graduate courses in machine learning and related areas rather than one introductory AI course.
Review the application focus. Some programs emphasize AI engineering and production systems. Others connect machine learning to electrical engineering, signal processing, data engineering, or applied computing.
Compare cost and format. Tuition, residency rules, online availability, and completion time can differ sharply between engineering programs.
Who Is an Engineering-Focused Program Best For?
This path can fit students who want to build and deploy machine learning systems or apply AI within engineering environments. It may also appeal to students with backgrounds in computer science, electrical engineering, computer engineering, software engineering, mathematics, or related technical fields.