Engineering Data Analytics ME Online | UW–Madison

Engineering Data Analytics ME Online | UW–Madison
niversity
of
isconsin
–Madison
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.
How to Apply
Request Info
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
Starting Fall 2026, tuition will be $1,100 per credit for eligible programs, with an automatic $100 per-credit Wisconsin Resident Scholarship.
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.
How to Apply
Request Info
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?
27 years
of delivering interactive online education, reflecting deep experience designing high-quality online programs for working professionals.
#9 ranking
Online Graduate Engineering Programs (Industrial)
U.S. News & World Report, 2026
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).
Student Experience
This engineering data analytics program combines machine learning, predictive analytics, and visualization with leadership and communication skills. You’ll learn to apply theory to practice, turning complex engineering data into clear, actionable insights.
Machine learning and predictive analytics
Data science and statistical modeling
Data visualization tools and techniques
Database design and management
Programming for engineering applications
Leadership and project management
Communicating technical insights to stakeholders
Applying data analytics to engineering systems
“I have a family and a full-time job, so I wasn’t ever sure I was going to be able to find an opportunity to pursue my master’s degree. The professors have been great. They put in a lot of effort. I wanted to be part of the community here, and I wanted to further my education. I’m a big believer in continuing education. I’m glad I was able to find the opportunity.”
Dave McCabe
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 (3 credits)
EPD 416 – Engineering Applications of Statistics (3 credits)
ISYE 412 – Fundamentals of Industrial Data Analytics (3 credits)
ISYE/ME 512 – Inspection, Quality Control and Reliability (3 credits)
ISYE/COMP SCI/ECE 524 – Introduction to Optimization (3 credits)
ISYE 603 – Special Topics: Applied Temporal Data Analytics for Engineers (1-3 credits)
ISYE 649 – Interactive Data Analytics (3 credits)
ME 459 – Computing Concepts for Applications in Engineering (3 credits)
ME 548 – Introduction to Design Optimization (3 credits)
ME/​COMP SCI/​ECE/​EMA/​EP 759 – High-Performance Computing for Applications in Engineering (3 credits)
Elective Courses & Concentrations
MEDA Concentrations include:
Data Analytics
3 additional courses from the core courses listed above
Artificial Intelligence
EPD 522 – Generative Artificial Intelligence for Engineering Applications (3 credits)
ISYE 516 – Introduction to Decision Analysis (3 credits)
ISYE 521 – Machine Learning in Action for Industrial Engineers (3 credits)
Leadership
EPD 611 – Engineering Economics and Management (3 credits)
EPD 612 – Technical Project Management (3 credits)
EPD 619 – Fostering and Leading Innovation (3 credits)
Manufacturing
ISYE 615 – Production Systems Control (3 credits)
ISYE 618 – Quality Engineering and Quality Management (3 credits)
ISYE/ME 641 – Design and Analysis of Manufacturing Systems (3 credits)
Sustainable Systems
EPD 660 – Core Competencies of Sustainability (3 credits)
EPD 690 – Special Topics: : Distributed Renewable Systems Design (1-3 credits)
OTM 770 – Sustainable Approaches to System Improvement (4 credits)
Additional Elective Courses
EPD 455 – Python for Applications in Engineering (1 credit)
EPD 614 – Marketing for Technical Professionals (3 credits)
EPD 637 – Polymer Characterizations (3 credits)
EPD 678 – Supply Chain Management (3 credits)
EPD 706 – Change Management (1 credit)
EPD/GEN BUS/MHR 783 – Leading Teams (1 credit)
ME 446 – Automatic Controls (3 credits)
Other courses offered in the College of Engineering Online Engineering portfolio may be used as electives with approval.
View full course descriptions
Tuition and Financial Aid
$1,300 per credit payable at the beginning of each semester. Starting Fall 2026, tuition will be $1,100 per credit for eligible programs, with an automatic $100 per-credit Wisconsin Resident Scholarship. Students are billed for courses in which they are enrolled each term. There is no lump sum payment plan.
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.
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, May 12, 2026
5-5:30 PM CT
Join program staff for a conversation about our online graduate programs, including curriculum, application process and career impact.
Register Now
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.
Career Spotlight: Engineering Data Analytics
Faculty and Staff
Sinan Tas
Academic Director
Email Sinan
Libby Miller
Graduate Student Advisor
Email Libby
John Lee, PhD
Jeff Linderoth, PhD
Kaibo Liu, PhD
Dan Negrut, PhD
Anthony Orzechowski, PhD
Krishnan, Suresh, PhD
Barry Van Veen, PhD
Jiao (Tina) Xu, PhD
Shiyu Zhou, PhD S
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.
How to Apply
Request Info
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