WPI Launches New Graduate Program in Data Science

The program, the first in Massachusetts, responds to a rapidly growing demand for professionals who can help organizations deal with the rise of big data
November 21, 2013

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Responding to a skyrocketing demand for professionals who understand how to analyze and distill value from massive data sets, popularly known as big data, Worcester Polytechnic Institute (WPI) is launching the first graduate program in data science in Massachusetts and one of only a handful of such programs in the nation. The interdisciplinary program, which leads to either a master of science degree or a graduate certificate, is enrolling students now in existing courses; the first cohort for the master's program will formally begin in the fall of 2014.

"Technological advances in devices, software, networking, and other technologies have given rise to digital data rich in variety, volume, velocity, and complexity," said Elke Rundensteiner, professor of computer science and director of the new graduate program. "These data represent an exceptional opportunity to harvest and extract insights important for competitive business and for innovation in healthcare, science, engineering, and societal well-being.

"The data bonanza and the growing use of data analytics in business, education, and government has created a need for a new breed of professionals, called data scientists, who have expertise in such specialized areas as machine learning, statistical modelling, data warehousing, predictive modeling, and large-scale database architecture and management."

WPI's interdisciplinary program will be offered jointly by faculty members in the Department of Computer Science, the Department of Mathematical Sciences, and the School of Business. "To effectively tackle the challenge of modern big data analysis, data scientists need a cross-disciplinary technical and scientific background that emphasis these three disciplines," Rundensteiner said.

The program will prepare students to apply and advance state-of-the-art data analytic tools and methods (including data mining, big data algorithms, and data visualization) in order to develop transformative solutions to problems across a number of domains; to use the knowledge and skills they gain in analytics, computing, statistics, and business intelligence to understand and explain their results and their applicability and validity; and to serve as visionary leaders and project managers in data analytics.

Students interested in data science have the option of pursuing a master of science degree in the field or completing a graduate certificate in data science. Students who opt for the degree program complete a minimum of 33 credits of work, which includes a capstone graduate qualifying project or thesis research. Both options offer experience in applying data science skills to real-world problems and are carried out in cooperation with a sponsoring organization, a faculty member, or an industrial partner. The degree can also be completed as part of a combined five-year BS/MS program. A graduate certificate can be earned by completing 18 credits of relevant graduate coursework; the credits can later be applied to complete the master of science degree.

Whichever option students choose, they will be prepared for a robust and growing profession, Rundensteiner said. "Data scientists are already in high demand by top-tier employers in fields like financial services, education, healthcare, security, insurance, science, government, social media, and Internet commerce," she noted, "and nationally, the number of data science job postings grew by 58 percent from the first half of 2010 to the second half of 2012.

"And the demand will only grow. According to a recent market analysis report by McKinsey Company, the United States faces a shortage of 140,000 to 190,000 people with analytical expertise and needs another 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data."

To learn more about WPI's new graduate program in data science, visit the data science website.