Data Science Master’s program at University of Michigan-Ann Arbor

Data Science is often viewed as the confluence of (1) Computer and Information Sciences (2) Statistical Sciences, and (3) Domain Expertise. These three pillars are not symmetric: the first two together represent the core methodologies and the techniques used in Data Science, while the third pillar is the application domain to which this methodology is applied. In this program, core data science training is focused on the first two pillars, along with practice in applying their skills to address problems in application domains.

We characterize the required Data Science skills in two categories: statistical skills, such as those taught by the Statistics and Biostatistics departments, and computational skills, such as those taught by the Computer Science and Engineering Division and the School of Information. The design of the program is to require every student to receive balanced training in both areas. To create an academic plan that achieves this balance, and to foster a greater sense of shared community, we do not intend to offer any sub-plans or tracks within the proposed degree program. Rather, we will expect graduates of this program to understand data representation and analysis at an advanced level.

With the MS in Data Science all students will be able to:.

Design and evaluate analytical procedures appropriate to the data.

Implement these efficiently over large heterogeneous data sets in a multi-computer environment.

To see the graduate level course offerings for the current (or previous) term, use the credit type drop down menu at the top of the page.

Students must take the following core courses (unless waived by the course review process, to be determined after matriculation):.

EECS 403: Data Structures for Scientists and Engineers.

All Students must take the following core courses:.

Select 1 course of at least 3 credits from each group. Students may not double-count a course in multiple categories.

· At least 25 units of graduate-level coursework must be completed during residency in the Data Science program.

· Expertise in Data Science Techniques part 1 can be fulfilled by STATS 413 if taken before program start.

· Expertise in Data Science Techniques part 2 can be fulfilled by EECS 445 if taken before program start.

· Program requirements: the cumulative GPA must be B (3.0) or better as required by Rackham.

You can review our application requirements here. Please also review Rackham Graduate School minimum requirements to apply, and if relevant the Required Academic Credentials from Non-U.S. Institutions.

LSA College of Literature, Science, and The Arts University of Michigan.