Master of Applied Data Science (MADS) students
The Master of Applied Data Science welcomes applicants from diverse backgrounds. We offer an agile curriculum that suits a wide range of applicants, including those who are returning to school full-time to pursue advanced study in data science and those who will complete their degrees while working part- or full-time.
Our MADS students study data science from across the country and the globe while managing all kinds of life and career circumstances. These Faces of UMSI profiles will introduce you to students who are parents, full-time employees, entrepreneurs, athletes and more -- and each individual has a unique perspective to offer as a member of the first cohort of UMSI's MADS program. Read about our students' areas of interests and educational histories and how they balance coursework as full- or part-time students. They describe their experience in the online classroom and the advantages of being a U-M student with full access to university and school resources up to thousands of miles off-campus.
(Student profiles are not routinely updated post-publication.)
Michelle LeBlanc is launching her data science career identifying fraud, waste and abuse in the healthcare industry.
Matt Wiese has developed some deviceful practices to help him balance work and home life while pursuing his second master’s.
Albert Lee is building community with his classmates and using his data science skills in the real world.
MADS Information Mentor Jordan Marquez has found surprising community in the fully online degree program, which has helped him balance unique aspects of life.
As a mechatronics engineer, David Hernandez believes data science is key to solving problems in the automotive industry.
Koon Leong Ho said earning his MADS degree while managing the analytics requirements for a hotel chain is like a "marathon," but it's not difficult with support — and it's paying off at work.
Rachel Wyatt is able to balance working full time and participating in MADS with caring for her school-age children during a pandemic. It's not a cinch, but it's worth it.
Ayansola Akanmu envisions using his education to work on real-life applications of machine learning and computer vision.
Carlo Tak is a data scientist from South Africa who is boundlessly curious about his own field.
Jenna Mekled is leaning into a career shift from auditor to data analyst in business and accounting.