Graduate Data Science Certificate Program

Note: New academic requirements are in effect for students who are accepted to the program after Oct., 2022. Students who have already enrolled in the program by Oct., 2022 will still follow the previous requirements.

Overview

The Graduate Data Science Certificate Program is open to all graduate students at the University of Michigan. The goal of the program is to improve the students’ research skills by exposing students to the foundations of data science and allowing them to gain basic data science skills that can be applied to a wide range of fields of graduate research. This program is the starting point of the students’ journey on gaining data science expertise. 

The program provides interactive data-centered training and involves 9 credits of courses and 3 credits of experiential training that require a written report on data analytics. The program is open for enrollment in both fall and winter semesters. U-M graduate students from any field are eligible to enroll. Minority and underrepresented students are strongly encouraged to enroll and complete the program.

Students are encouraged to take classes outside the student’s core degree program/department. Completion of the program can be done in 2-4 semesters; but the students may complete the program anytime before they graduate from U-M. The Graduate Data Science Certificate Program aims to provide core experiences in:

Analysis Methods (AM):

Data Management (DM):

Algorithms and Applications (AA):

Prerequisites

Graduate students interested in enrolling in the MIDAS Data Science Graduate Certificate Program are encouraged to review the Prerequisites and complete the Graduate Data Science Readiness Self-Assessment Pretest.

NOTE: The Graduate Data Science Certificate Program is only open to U-M students currently enrolled in a graduate degree-granting program.

Certificate Program Committee

Eunshin Byon

Associate Professor, Industrial and Operations Engineering, College of EngineeringCivil and Environmental Engineering, College of Engineering

Kevyn Collins-Thompson

Associate Professor, School of Information, EECS, College of Engineering

Ivo D. Dinov

Professor, Computational Medicine and Bioinformatics Human Behavior and Biological Sciences Michigan Institute for Data Science (MIDAS)

Rich Gonzalez

Professor, Psychology, LSA Statistics, LSA Marketing, Ross School of Business

Danai Koutra

Assistant Professor, Computer Science and Engineering, College of Engineering

Kerby Shedden

Professor, Statistics, LSABiostatistics, School of Public HealthDirector of Consulting for Statistics, Computing, and Analytics Research (CSCAR)