A year ago, Elke Rundensteiner, a computer science professor at the Worcester Polytechnic Institute, organized a meeting to discuss starting a new data science graduate school program. About 20 percent of the school’s faculty and administration showed up.
The gathering drew those already teaching courses in Hadoop and analytics. But those expressing interest also included specialists in engineering, signal processing, sensor processing, biomedical engineering, health sensors and other electronic devices, as well as business, mathematics, social sciences and biology professors.
To Rundensteiner, the director of WPI’s data science program that officially will launch this fall, the range of expertise in that meeting room represents an important theme: students studying analytics benefit from learning about the technical aspects of managing and processing data—and from exposure to the diverse fields in which practitioners can use analytics tools.
“We’re trying to make this truly interdisciplinary,” Rundensteiner said, adding she expects that some students will come with computer science backgrounds. But she wants also to attract non-engineers, including those backgrounds in physics, social sciences and other fields.
“As long as they have quantitative skills and are interested in going in that direction, we can pull them into this new area. We believe they will bring an innovative perspective,” she said.
The program, based at the school’s Worcester, Mass., campus, will offer a Master of Science degree in Data Science, with the inaugural class expected to have between 10 and 20 students. The school also plans to offer bachelor degrees and certificates in the data science, and will consider tailoring a program for the corporate education market.
The WPI program comes as many at the school recognize the large and growing market for people with data analytics training, Rundensteiner said.
Armend Hoxha, a student in Rundensteiner’s big data class in 2013, is one of those soon to enter the job market. A 30-year-old computer science graduate student from Kosovo, Hoxha had experience working as a software developer at an architectural firm and a bank before coming to Worcester for a computer science graduate degree.
Introduced to the concepts in the big data course, Hoxha said he got excited by two converging dynamics: the ubiquity of data—“Everybody is contributing to big data,” he noted—and the challenges that analysts face in the quest to gain insights from all that data. “If we know how to analyze all of that information, we can tell a lot. What people are interested in, what is going on in a particular place in the globe, what people are afraid of. There may be a lot of noisy information, but we have potentially valuable information hiding inside … a lot of data,” he said.
For one of his class projects, Hoxha said his three-person team had to build a Facebook-style social graph to determine the relationships among different elements in the provided datasets. The experience has influenced his decision to focus on courses related to more data analysis and software engineering so he can develop data science tools. Eventually, he said, he would like to be part of a big team working at a company like Facebook or LinkedIn.
• Degree awarded: Master of Science in Data Science
• Program scheduled to launch in fall 2014 with 10 or 20 students; some specific classes will include students from other degree programs.
• Students may enroll full- or part-time
• Requirements: 33 credits of relevant work at the graduate level. Credits must include either a three-credit graduate qualifying project, or a nine-credit master’s thesis, as well as 15 credits of core data science coursework, and 9 to 15 credits of electives and areas of concentration (amount depends on whether student chooses qualifying project or thesis).
• Cost: $1,281 per credit.
• Tools students may use include: DB2, Hadoop, IBM software (including Cognos, SPSS Modeler, InfoSphere Big Insights, InfoSphere Streams), Mahout, MATLAB, MySQL, R, RapidMiner, SAS, Spotfire, SQL Server, Tableau Software and Weka machine learning software, among others.
Students earning WPI’s graduate certificate in data science require 18 credits of graduate work, including one course in each of five core categories of data science, plus one elective. These credits can be applied toward a master’s degree.
Michael Goldberg is the editor of Data Informed. Email him at Michael.Goldberg@wispubs.com.