Build data skills that strengthen engineering judgment and support better technical decisions.
UW–Madison’s online Master of Engineering in Engineering Data Analytics is a 30-credit graduate program for practicing engineers who want to apply analytics to real engineering problems. Learn through flexible online courses taught by faculty with industry experience while completing the degree alongside full-time work.
| Degree awarded | Master of Engineering in Engineering |
| Credits | 30 graduate credits |
| Format | 100% Online, part-time friendly |
| Duration | 2-4 Years (part-time) |
| Tuition | $1,300/credit |
| Start | Fall / Spring / Summer |
| Application Deadlines | Spring: November 1 Summer: May 1 Fall: July 1 |
Is This Program Right for You?
Engineers across industries must turn data into actionable insights. This flexible online program gives you the tools to analyze, visualize, and act on complex data, while allowing you to tailor your coursework to your professional goals. Build in-demand skills in machine learning, predictive modeling, and engineering data analytics on a schedule that supports your career, your family, or both.
- Participate in an interactive online learning experience built for working engineers
- Network with peers, faculty, and industry professionals to extend learning beyond the classroom
- Gain hands-on experience applying data analytics in engineering systems
- Customize your program by choosing core data analytics courses and using electives to shape your focus in areas such as AI, manufacturing, sustainability, or leadership.
Online by Design
Our courses blend recorded instructor materials, applied activities, and structured opportunities for interaction. This intentional design supports strong engagement, clear guidance, and meaningful results.
Why This Program?
26 years
of delivering interactive online education, reflecting deep experience designing high-quality online programs for working professionals.
#9 graduate ranking
among U.S. public universities
U.S. News & World Report, 2024
Enhance your
AI skills
with an optional 9-credit graduate certificate in Artificial Intelligence for Engineering Data Analytics, available as part of your 30-credit program (no extra coursework needed).
Curriculum and Requirements
Complete 30 graduate credits, including 15 credits in data analytics and 15 elective credits that span either additional data science courses or other online engineering and professional development courses. You will typically take two courses each semester.
Live course web sessions are scheduled in the evening to accommodate working professionals. All other weekly assignments can be completed on days and times of your choice. Plan for roughly 3 to 4 hours of work per credit each week. For a 3-credit course, this usually means 9 to 12 hours, depending on the course and your professional background.
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Required Courses
Students must complete at least 15 credits from the following courses:
- ECE/COMP SCI/ME 532 – Matrix Methods in Machine Learning
- EPD 416 – Engineering Applications of Statistics
- ISYE 412 – Fundamentals of Industrial Data Analytics
- ISYE/ME 512 – Inspection, Quality Control and Reliability
- ISYE/COMP SCI/ECE 524 – Introduction to Optimization
- ISYE 603 – Special Topics: Applied Temporal Data Analytics for Engineers
- ISYE 649 – Interactive Data Analytics
- ME 459 – Computing Concepts for Applications in Engineering
- ME 548 – Introduction to Design Optimization
- ME/COMP SCI/ECE/EMA/EP 759 – High-Performance Computing for Applications in Engineering
Elective Courses & Concentrations
MEDA Concentrations include:
Data Analytics
- 3 additional courses from the core courses listed above
Leadership
- EPD 611 – Engineering Economics and Management
- EPD 612 – Technical Project Management
- EPD 619 – Fostering and Leading Innovation
Manufacturing
- ISYE 615 – Production Systems Control
- ISYE 618 – Quality Engineering and Quality Management
- ISYE/ME – 641 Design and Analysis of Manufacturing Systems
Sustainable Systems
- EPD 660 – Core Competencies of Sustainability
- EPD 690 – Special Topics: : Distributed Renewable Systems Design
- OTM 770 – Sustainable Approaches to System Improvement
Additional Elective Courses
- EPD 455 – Python for Applications in Engineering
- EPD 614 – Marketing for Technical Professionals
- EPD 637 – Polymer Characterizations
- EPD 678 – Supply Chain Management
- EPD 706 – Change Management
- EPD 708 – Creating Breakthrough Innovations
- EPD/GEN BUS/MHR 783 – Leading Teams
- ME 446 – Automatic Controls
Other courses offered in the College of Engineering Online Engineering portfolio may be used as electives with approval.
Tuition and Financial Aid
$1,300 per credit payable at the beginning of each semester. Students are billed for courses in which they are enrolled each term. There is no lump sum payment plan.
Tuition includes:
- Technology costs for internet course delivery
- Live web-conferencing
- Toll-free telephone line for the audio portion of conference calls
- Library use
- Use of the web-conferencing software for group project work for program courses
See Tuition & Cost for more information.
Employer Support
Many students receive some financial support from their employers. Often, students find it beneficial to sit down with their employer and discuss how this program applies to their current and future responsibilities. Other key points to discuss include how participation will not interrupt your work schedule.
Federal Loans
Students who are U.S. citizens or permanent residents are eligible to receive some level of funding through the Federal Direct loan program. These loans are available to qualified graduate students who are taking at least four credits during the fall and spring semesters, and two credits during Summer. Private loans are also available. Learn more about financial aid.
Admissions and Events
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Program requirements
All applicants must:
- Have a Bachelor of Science in engineering or a related STEM field from an accredited institution.
- Have a minimum undergraduate GPA of 3.0 on the last 60 semester hours of coursework.
- Have a minimum of two years of post-baccalaureate engineering experience. Engineering co-op or intern experience may be applied to the experience requirement.
- Submit evidence of English language proficiency, if applicable. See the Graduate School Requirements for more information.
- GRE is not required. Applicants who have taken the test are encouraged to submit their scores.
The admissions committee considers exceptions to standard requirements on an individual basis.
Application materials
- Online application
- Resume/CV
- Personal statement
- Transcripts
- Two letters of recommendation
For complete application details visit UW–Madison’s Guide
Application Deadlines by Term:
| Summer 2026 | May 1, 2026 |
| Fall 2026 | July 1, 2026 |
| Spring 2027 | November 1, 2026 |
Online Graduate Programs Overview
Tuesday, January 13, 2026
5-5:30 PM CT
Join program staff for a conversation about our programs, including curriculum, application process and career impact.
Online Graduate Programs Overview
Tuesday, February 10, 2026
12-12:30 PM CT
Join program staff for a conversation about our programs, including curriculum, application process and career impact.
Online Graduate Programs Overview
Tuesday, March 10, 2026
5-5:30 PM CT
Join program staff for a conversation about our programs, including curriculum, application process and career impact.
Program Overview: Engineering Data Analytics MEng
Wednesday, April 1, 2026
12-12:30 PM CT
Join program staff to get more information about the Engineering: Engineering Data Analytics MEng program including curriculum, application process and potential career paths.
Watch anytime on YouTube:
Program Overview: Engineering Data Analytics
Graduate Student Advisor Libby Miller provides an overview of the Engineering Data Analytics program, including curriculum, application process and potential career paths.
Faculty and Staff
FAQ
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Q: Is the program fully online?
A: Yes. The MEng in Engineering Data Analytics is 100% online and designed for working professionals.
Q: How long does it take to complete?
A: Most students finish in about two to four years while working full time.
Q: What is the tuition?
A: Tuition is charged per credit. See Tuition & Fees for more information.
Q: Can I keep working full time?
A: Yes. Courses are designed for part-time study alongside a full-time job.
Q: Will my diploma indicate that the degree was completed online?
A: No. The diploma awarded is a UW–Madison graduate degree and does not reference online delivery. Courses are taught and assessed under the same academic standards used across UW–Madison graduate programs. The mode of instruction does not change the credential earned.
Q: How do I apply?
A: Submit your application through the Graduate School. See Admissions for details or click here.
Ready to lead with confidence? Advance your career with UW–Madison’s online MEng in Engineering Data Anaytics.
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