Become the engineer who confidently uses data science to transform big data into informed, high-impact actions.
Many industries are in critical need of engineers who understand and can apply data science 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:
Testimonials
“The most valuable part of the program was being able to apply what I learned in the classroom immediately to my work. I was able to be a part of teams at work that were in problem-solving situations and I was able to provide recommendations based on what I learned just the week before!” —Elizabeth Bitante, Cudahy, WI, MEDA Class of 2021
“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
30 credits
2-3 years
$1300 per credit
Resident and non-resident
July 1/Nov 1/May 1
Fall/spring/summer application deadlines
Susan Ottmann Program Director
Email SusanJustin Kyle Bush Graduate Academic Advisor
Email JustinListen to our Podcast: Tony Orzechowski on Data and Analytics
Listen NowVirtual Office Hours
Calling all current and prospective students! Join Graduate Academic Advisor Justin Kyle Bush every Tuesday from 11:00am-12:00pm CST to ask questions about your courses, program, the application process, or anything else that’s on your mind. Learn More
- Course and Degree Plan
- Learning Online
- Faculty & Staff
- Admission Requirements
- Tuition and Financial Aid
Academics
At the University of Wisconsin, we empower our students to become creative problem solvers, able to integrate statistical and data analysis with design and optimization, seek out and create new applications in computing, and adapt to new situations. Curriculum 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
- Business
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- ISyE 412 Fundamentals of Industrial Data Analytics
- ISyE 512 Inspection, Quality Control and Reliability
- 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
- LIS 751 Database Design for Information Professionals
- ME 548 Introduction to Design Optimization
- ISyE 620 Simulation and Modeling Analysis
- ISyE 602 Interactive Data Visualization
- ISyE 603: Special Topics: Applied Temporal Data Analytics for Engineers
- EPD 611 Engineering Economics and Management
- EPD 612 Technical Project Management
- EPD 619 Fostering and Leading Innovation
- ISyE 412 Fundamentals of Industrial Data Analytics
- 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
- ISyE 512 Inspection, Quality Control and Reliability
- ISyE 615 Production Systems Control
- 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
- Program Director: Susan Ottmann, MS
- Graduate Academic Advisor: Justin Kyle Bush, M.Ed.
- Kaibo Liu, PhD
- Dan Negrut, PhD
- Leyuan Shi, PhD
- Krishnan, Suresh, PhD
- Barry Van Veen, PhD
- Jiao (Tina) Xu, PhD
- Shiyu Zhou, PhD
Admission Requirements
Application Overview 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 Academic 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.
- Library use
- Use of the web-conferencing software for group project work for program courses
- Advising
- Access to campus computing resources
News
UW–Madison Online Graduate Engineering Programs Ranked 9th by U.S. News & World Report
MADISON, Wis.—UW-Madison’s online master’s degrees in engineering were ranked #9 in the nation by U.S. News & World Report. This is the eleventh year in the row that the online engineering programs, offered by the College of …
Student Spotlight: Walter Schlesser
Walter Schlesser is a student in our Master of Engineering Data Analytics program and will graduate in 2024. Like many of our students, he’s working while completing his degree, and his current role is a …
Epod Episode 4: Theresa Pelkey—An Alumna’s Perspective on Manufacturing Systems Engineering
On this episode, Justin Kyle Bush talks to Theresa Pelkey, the Manufacturing and Project Engineering Director at Kite Hill. Theresa received a Bachelor’s in Chemical Engineering and a Master’s in Manufacturing Systems Engineering from UW-Madison. She discusses her personal and professional development and the challenges of working, studying and being a parent. She also talks about her experience in the MSE program and gives advice for those who are thinking about continuing their education—whether through a degree or professional development.
- More news