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 archived June 17 MEDA info session:
$1300 per credit
Resident and non-resident
July 15/Nov 1/May 1
Fall/spring/summer application deadlines
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* 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
- 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
- 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
- EPD 690 Data Visualization (special topics)
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.
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, challenged and supported by your fellow learners, as well as instructors. Our students and alumni consistently point to the value of the global professional network they develop through our programs, built through teamwork, challenges, and projects, and lasting a lifetime.
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 Student Services. 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
Click here to begin the application process.
$1,300 per credit, payable at the beginning of each semester.
- Library use
- Use of the web-conferencing software for group project work for program courses
- Access to campus computing resources
Total tuition for this program is $39,000*.
*This total does not include textbooks or course software. Software required for courses is typically available 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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