Become the engineer who confidently uses data analytics to transform big data into informed, high-impact actions.
Many industries are in critical need of engineers who understand and can apply data analytics tools and methods to drive improvements to products and processes, research, design, testing, and operations. UW-Madison’s Master of Engineering in Data Analytics (MEDA) program uniquely combines data science learning with focused applications in engineering and skills needed to lead projects and teams.
What you will learn in this program:
- Machine learning and predictive analytics.
- Statistical methods and decision science.
- Visualization tools and techniques.
- Optimization of products, processes, research, design, testing and operations.
- Leadership and communication skills to effectively manage change.
Learn more about this program:
Watch the most recent information session:
“Some of the best parts of this program for me is it is a different type of learning than your undergraduate courses. It’s so much easier to apply learning the next day and intertwine company projects and company work with learnings from class. This puts me ahead of the other analysts that I work with on different data techniques!”
—Morgan Zaref, MEDA Class of 2023
“I really liked the flexibility of an online program. The classes really excelled at engaging the students even in a virtual environment.”
—Omar Saleh, Milwaukee, WI, MEDA Class of 2021
“Started the program as an online learning skeptic. Ended the program with immense respect for the entire process and especially UW engineering and InterPro faculty.”
—Jamie Weigandt, Lisle, IL, MEDA Class of 2021
$1300 per credit
Resident and non-resident
July 1/Nov 1/May 1
Fall/spring/summer application deadlines
Justin Kyle Bush
Listen to our Podcast:
Tony Orzechowski on Data and Analytics
- Course and Degree Plan
- Interactive Online Learning
- Faculty & Staff
- Admission Requirements
- Tuition and Financial Aid
How Our Program Works
You will earn a degree in Engineering Data Analytics (MEDA) upon completion of 30 graduate credits. The program and course schedule are designed to be flexible for part-time students, but the degree program can be completed in two years.
Complete 15-credit core curriculum in data analytics and 15 elective credits that span either additional data science courses or other online engineering and professional development courses.
Classes meet online once a week; each class is recorded, so you can participate regardless of your travel schedule or location.
Curriculum* for this program is the result of a joint effort led by the College of Engineering and faculty across campus working in the areas of big data and analytics.
These departments include:
- Electrical and Computer Engineering
- Mechanical Engineering
- Industrial Systems and Engineering
- Library and Information Sciences
Our courses will build your ability to assemble and analyze data needed to face challenges in engineering systems. You will also learn to evaluate advanced computing tools, simulations, modeling, and engineering optimization. Additionally, you will develop and polish your skills in project management, team leadership, and effective communication.
You will earn a Master of Engineering in Engineering degree with an emphasis in Engineering Data Analytics (MEDA) upon completion of 30 graduate credits required by the University of Wisconsin. The program and course schedule are designed to be flexible for part-time students, but the degree program can be completed in two years.
No On-campus Residency Requirement
All of the courses are completely online, and students are not required to participate in an on-campus residency program. The MEDA program is offered in conjunction with the Wisconsin Applied Computing Center, and students are welcome to attend the annual Wisconsin Forum on Advanced Computing in Engineering in the spring of each year. Here they can share and learn from leading experts from academia and industry.
Courses in the MEDA curriculum will provide you with knowledge and application of the latest best practices and innovations. Course projects that you select enable you to customize your learning and gain immediate impact. Your elective courses provide complementary opportunities for focused application of data analytic methods and tools. Professional development electives provide insights to improve your leadership of engineering data analytic initiatives.
Required Courses (15 credits from the following)
- ISyE 412 Fundamentals of Industrial Data Analytics
- ISyE 512 Inspection, Quality Control and Reliability
- ISyE 524 Introduction to Optimization
- EPD 416 Engineering Applications of Statistics
- ME 459 Computing Concepts for Applications in Engineering
- ECE/COMP SCI/ME 532 Matrix Methods in Machine Learning
- ME/COMP SCI/ECE/EMA/EP 759 High-Performance Computing for Applications in Engineering
- ISyE 649 Interactive Data Visualization
- ISyE 603: Special Topics: Applied Temporal Data Analytics for Engineers
Students choose 15 elective credits from courses above or courses within Engineering Management, Manufacturing Systems, Polymer Engineering, and Sustainable Systems Engineering in consultation with their advisor.
MEDA Concentrations include:
3 additional courses from the core courses listed above
- EPD 611 Engineering Economics and Management
- EPD 612 Technical Project Management
- EPD 619 Fostering and Leading Innovation
- ISyE 615 Production Systems Control
- ISyE 618 Quality Engineering and Quality Management
- ISyE/ME 641 Design and Analysis of Manufacturing 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
- ISyE 512 Inspection, Quality Control and Reliability
- 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 783 Leading Teams
- ME 446 Automatic Controls
Other courses offered in the College of Engineering Online Engineering portfolio may be used as electives.
Interactive Online with UW-Madison
At UW–Madison, we’ve built a learning experience to meet you where you are.
Whether your work involves frequent travel, changing hours, or periods of intense demand, our courses help you grow wherever you happen to be and whenever you have online access. We develop and deliver courses for high-performing professionals, with a deep understanding of the challenges those professionals face.
As a UW student, you will be part of a vibrant community where you will be challenged and supported by your fellow learners and instructors. Our students and alumni consistently point to the lasting, lifetime value of the global professional network they develop through our programs, which they built through teamwork, projects, and challenges.
Support and Collaboration to Help You Succeed as a Working Professional
With internet-based tools such as web conferencing, online discussion forums, email, and video calls, our program emphasizes close collaboration among students and instructors.
The ability to work independently is crucial to your success as a distance learner. However, this does not mean you are alone. Our instructional design team develops every course to meet online learner needs.
Your instructors and teaching assistants are always available to answer your questions. In addition, faculty and staff understand the challenges you face as a working professional and distance learner, and proactively monitor your progress. A full-time program advisor will assist and guide you throughout the program.
Try Out an Online Course with Us
Technical Project Management (TPM) is a three-credit graduate engineering course that addresses the principles, strategies, and tools of project management that apply to a broad range of engineering projects.
This course gives you the opportunity to sample the type of graduate-level courses you’ll experience in our online degree programs, while strengthening your project management skills!
Earn UW credits that can be applied to other programs—including graduate certificates and online master’s degrees.
UW-Madison’s academic reputation, research focus, and industry partnerships partners guarantee high-caliber staff for each of our online modules. Professors are dedicated to keep students engaged, progressing, and confident that their learning goals are being met. Our academic advising will ensure you get the responsiveness and support you need, while keeping you on track in your studies.
The admissions process has been designed to conduct a holistic review of your likelihood of success in the program. Decisions are based on your academic and professional background.
To start the process, please read the admission requirements to determine your eligibility. If you have questions about your eligibility, please request an eligibility review by emailing our Graduate Advisor Justin Kyle Bush. This email should include a copy of your current resume and informal transcripts.
Admission requirements for the Master of Engineering in Data Analytics degree program are listed below.
Exceptions to standard admission requirements are considered by the admissions committee on an individual basis.
- A bachelor of science (BS) degree in engineering from a program accredited by the Accreditation Board for Engineering and Technology (ABET) or the equivalent.* International applicants must have a degree comparable to an approved U.S. bachelor’s degree.
- A minimum undergraduate grade-point average (GPA) of 3.00 on the equivalent of the last 60 semester hours (approximately two years of work) or a master’s degree with a minimum cumulative GPA of 3.00. Applicants from an international institution must have a strong academic performance comparable to a 3.00 for an undergraduate or master’s degree. All GPAs are based on a 4.00 scale. We use your institution’s grading scale; do not convert your grades to a 4.00 scale.
- Applicants whose native language is not English must provide scores from the Test of English as a Foreign Language (TOEFL). The minimum acceptable score on the TOEFL is 580 on the written version, 243 on the computer version, or 92 on the Internet version.
- GRE is not required. Applicants who have taken the test are encouraged to submit their scores.
- Registration as a professional engineer by examination, if achieved, should be documented to support your application.
*Equivalency to an ABET accredited program: Applicants who do not hold a bachelor’s degree from an ABET accredited program may also qualify for admission to the program. Students are encouraged to contact the program director for more information.
All applicants are advised to determine whether this program meets requirements for licensure in the state where they live. See the National Society of Professional Engineers website for contact information for state licensing boards
$1,300 per credit, payable at the beginning of each semester.
- Canvas Learning Management System
- 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
- Technical support
- Access to campus resources
Total tuition for this program is $39,000*.
*This total does not include textbooks or course specific software. Software required for courses is typically available by UW-Madison or in educational versions at substantial discounts.
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.
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
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