Data Science
MASTER OF SCIENCE IN
DATA SCIENCE
Purdue’s innovative Master of Science in Data Science (MSDS) is an accessible, skills-focused master’s designed to meet the needs of professionals who have some background in data science and want to accelerate their expertise. This online technical degree exposes students to coursework in in-demand areas like data visualization, machine learning, data mining, data analysis, communication and more. Applicable to many different fields and career paths, this master’s empowers professionals to harness the power of data and push their careers to new heights. This fully online program incorporates the innovation and research strength of Purdue University’s West Lafayette faculty and academic community.
Ready to dive into the world of Data Science?
Data Science
Build In-Demand Data Skills Through Hands-On Learning
- Build technical skills in data science by completing hands-on projects with real-world applications.
- Gain expertise in in-demand areas like machine learning, data visualization, data mining, project management and more.
- Prepare yourself for a career in data science or learn to incorporate data skills into your current role.
- Develop an understanding of where the data field is heading and master state-of-the-art trends and techniques.
Ready to learn more?
Take our Readiness Self-Assessment to evaluate your skills and start your journey to success!
Take the first step toward mastering data science with our tailored self-assessment tool. This resource was designed to align with the program’s learning outcomes to help you evaluate your current skills in Basic Programming, Intermediate Programming, and Math & Probability.
Master of Science in Data Science
Curriculum Overview
The Master of Science in Data Science curriculum consists of a total of 30 credit hours. 18 credit hours can be taken from core courses and 12 credit hours can be taken from selected focus areas or electives.
Faculty
John Springer
John Springer is a Professor in the Department of Computer and Information Technology (CIT) at Purdue University. His main research area is Data Science with recent emphasis on data-intensive applications in Cybersecurity, and he serves as the leader of the Purdue DATA Laboratory. Dr. Springer currently serves in a variety of leadership roles at Purdue; these include as the co-chair of the CIT Undergraduate Curriculum Committee and the co-chair of Purdue’s Integrative Data Science Initiative (IDSI) Curriculum Committee.
Chris Brinton
Chris Brinton is the Elmore Rising Star Associate Professor of Electrical and Computer Engineering (ECE) at Purdue University, where he leads the ION research lab. ION conducts research at the intersection of networking, communications, and machine learning. Contemporary network architectures we investigate include Fog computing systems, the Internet of Things (IoT), NextG Wireless, and social learning networks (SLN), and our foundational techniques include convex and non-convex optimization, machine learning, and signal processing. Since joining Purdue, he has received several external early career research awards, including NSF’s CAREER Award, ONR’s YIP (Young Investigator Program) Award, DARPA’s YFA (Young Faculty Award), AFOSR’s YIP Award, and Intel’s RSA (Rising Star Faculty Award).
Jen Tang
Professor Tang’s teaching interests are applied statistics, quantitative methods, and business analytics. His current research includes the areas of applied statistics, statistical quality control, and reliability analysis. Professor Tang also has considerable expertise in the distribution theory of multivariate statistical analysis. He was/is on the editorial boards of IIE Transactions and Production and Operation Management Journal. Prior to joining the Krannert faculty, Professor Tang was a member of technical staff at Bell Communications Research (Bellcore, 1984-91) and an assistant professor in the Department of Mathematics, Statistics, and Computer Science at Marquette University (1981-84). He received his Ph.D. in Mathematical Statistics from Bowling Green State University (1977-1981) and BS in Applied Math from Soochow University in Taipei (1969-1973).
Gang Shao
Gang Shao is an assistant professor of data science at Purdue Libraries and School of Information Studies. His research interests include data science education and information science using machine learning, Natural Language Processing (NLP), and computer vision. He is also a remote sensing scientist using optical imagery and lidar to understand land ecosystems and the changing climates.
Cherie Maestas
Cherie D. Maestas, is Professor and Head of the Department of Political Science at Purdue University. Previously she served as the Marshall A. Rauch Professor of Political Science and Director of the interdisciplinary Public Policy Program in the College of Liberal Arts and Sciences received her PhD from the University of Colorado, Boulder in 2000. Dr. Maestas received her PhD from the University of Colorado, Boulder in 2000. Her current research examines how emotions and personal characteristics (e.g. emotion regulation, personality traits, political predispositions) moderate the effects of media messages and policy framing.
Kyle Hultgren
Kyle Hultgren is the founding director of the Purdue University College of Pharmacy’s Center for Medication Safety Advancement. Dr. Hultgren is a co-author of a process improvement program in partnership with Purdue University and the United States Veterans Health Administration that has been provided to thousands of professionals in health systems nationwide. His current research includes extensive work on dashboards and measurement systems for evaluating and improving medication use systems and integration of publicly available social media data as potential surveillance signals. As a result of this work, he led his Center through the creation of SafeRx, a large, curated, relational database containing millions of adverse drug events.
Bryce Dietrich
Bryce Dietrich is an Associate Professor in the Department of Political Science and research scholar at the Center for C-SPAN Scholarship and Engagement (CCSE). His research uses novel quantitative, automated, and machine learning methods to analyze non-traditional data sources such as audio (or speech) data and video data. Professor Dietrich’s work has appeared in the Nature, American Political Science Review, Journal of Politics, Political Analysis, and Political Psychology. This work has also received grant support from major organizations, including the National Institutes of Health and the National Science Foundation. He received his Ph.D. from the University of Illinois and was recently a postdoctoral research fellow at Harvard’s Kennedy School and Northeastern University.
Jacob Hosen
Dr. Jake Hosen uses high frequency sensors to study how microbes and environmental change influence ecosystem functions and water quality. Before joining the Department of Forestry & Natural Resources, he was a postdoctoral associate at the University of Florida and Yale University. In his previous positions, Jake worked with a national team to study how microbial metabolism stabilizes water quality in river networks. Dr. Hosen received his B.Sc. from the College of William & Mary in Chemistry and Biology, and a Ph.D. in Behavior, Ecology, Evolution & Systematics from the University of Maryland. In his position at Purdue, Dr. Hosen will leverage internet of things technology to deploy environmental sensors networks that will provide real-time sensing for predictive ecosystem models.
Vinayak Rao
Vinayak Rao is an Assistant Professor at the department of Statistics at Purdue University. He completed his PhD at the Gatsby Unit at University College London. He then spent two years as a postdoc at the department of Statistical Science at Duke University before joining Purdue in 2014. Vinayak’s research interests lie in the areas of probabilistic machine learning, Bayesian statistics and modeling and computation for stochastic processes.
Career Outlook
Get your career started by working in one of the following roles: Data Scientist, Software Developer, Machine Learning Engineer, Data Analyst, Quantitative Analyst, Data Engineer, and more!
Purdue University’s rigorous online programs allow you to earn a prestigious Purdue degree anytime and from anywhere. These programs give you access to outstanding faculty and top-quality curriculum in a convenient, flexible format to move your career and the world forward.
Source: LightcastTM (2023). Unique job postings for July 2022-2023. Projected growth for years 2023-2033.
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