Master of Applied Data Science University of Michigan
Become a data science leader with Applied Data Science and get a degree from the #1 public research university in the U.S.
Learn in-demand data science skills and how to apply them to real-world problems with the online Master of Applied Data Science (MADS) degree from the University of Michigan School of Information.
In this online degree program, you’ll have the unique opportunity to develop an end-to-end perspective on data science and prepare for leadership in the field. As a MADS student, you’ll master core concepts and delve into essential topics such as big data, data ethics, data privacy, machine learning, natural language processing, network analysis, and more. By working with real data sets from top companies, you’ll put learning into practice, build your portfolio, and be ready to advance a successful data science career in any industry.
The only prerequisites to enroll in the program are knowledge of statistics and Python. You are not required to have a bachelor’s degree in a science or math discipline, or work experience in a technical field. We do not require the GRE or any other additional tests as part of your admissions process.
Advance your data science career
As an online student in the University of Michigan’s School of Information, you’ll prepare to be a leader in the field by developing an end-to-end perspective on data science. Past graduates from the School of Information’s on-campus programs have a 95% job placement rate, and go on to become data scientists at places like Google, Facebook and Amazon.
Earn your degree from a top-ranked institution
The University of Michigan is considered the #1 public research university in the U.S., according to the National Science Foundation. With more than 630,000 proud alumni, U-M is a leader in higher education, attracting top students and faculty from across the globe. More than 1 million learners have taken courses online from UMSI faculty since launching on Coursera.
Join a global community
Whether you’re in the Upper Peninsula of Michigan, or in Europe, Asia, or Africa, MADS learners all share one thing: a passion for data. As a member of our global community, you’ll have opportunities to connect and collaborate with other School of Information students through peer review sessions, mentorship, the student Slack channel, and more.
The next application deadlines are:
- Applications Open: July 19, 2023
- Priority Deadline: October 1, 2023
- Final Deadline: November 15, 2023
Have questions? Attend an upcoming Information Session or email firstname.lastname@example.org.
Get a head start on your degree with courses, specializations or certificates.Learn more
Hear from our learners
“I really love how innovative and engaging I’ve felt the content has been so far. It really is like no other education I’ve had before.”
— Ani M.
“Applying my knowledge to something meaningful based on real-life scenarios is important to me. It helps me maintain a level of curiosity that drives my passion.”
— Stacy B.
“The big draw of this program was that it was an online program for students with diverse educational backgrounds. I am amazed at how much I have been able to learn in such a short amount of time.”
— Jenna M.
Interested in getting started, but not yet ready to commit?
Prepare for this degreeAssociated with
These courses are related to the degree program. They may provide you with a preview of the topics, materials and instructors covered in a related degree program which can help you decide if it is right for you.
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Get Started with Applied Data Science
Interested in this degree? Need more programming experience? The following two specializations from University of Michigan will give you the Python and statistics background needed to begin the Master of Applied Data Science degree:
The Python 3 Programming Specialization teaches the basics of programming in Python 3. It covers fundamental techniques like variables, conditionals, and loops. The course also includes intermediate materials like keyword parameters, list comprehensions, lambda expressions, and class inheritance.
The Statistics with Python Specialization covers beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will explore where data comes from, what types of data can be collected, data design, data management, and how to effectively carry out exploration and visualization. Students will utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures.
About the Program ( Applied Data Science)
The University of Michigan School of Information’s Master of Applied Data Science welcomes applicants from diverse backgrounds. The curriculum is designed for applicants who want to devote themselves to full-time study, as well as those who want to complete their degree while working.Learn more about Admissions
The Master of Applied Data Science Program equips students with the skills needed to apply data science in any number of real world contexts. It blends theory, computation, and application in a flexible online format.Learn more about Academics
University of Michigan School of Information master’s students earn the highest average salaries of any graduate program in similar areas of study, and 98%+ of our students report finding jobs in their field of choice.Learn more about Careers
Students will have access to renowned University of Michigan faculty and resources. They will also have opportunities to build community with other University of Michigan School of Information students who are working on graduate degrees.Learn more about Student Experience
About University of Michigan
With 102 top-10 graduate programs, the University of Michigan is ranked as the #1 public research university in the U.S. by the National Science Foundation.Learn more about University of Michigan
Start Learning Applied Data Science
Although not part of the MADS curriculum, we encourage you to enroll in our Python 3 Programming Specialization to preview what it is like to learn from UMSI faculty.Learn more
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