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January 10, 2014

Universities Roll Out New Big Data Programs

Alex Woodie

The insatiable demand for data scientists is creating a major bottleneck in the capabilities of organizations to complete their big data projects. In response, the nation’s universities are stepping up and putting new big data programs in place in an attempt to meet demand. MIT and the Worcester Polytechnic Institute are two universities that recently unveiled new big data classes and programs.

MIT’s new four-week class on big data, titled “Tackling the Challenges of Big Data,” will be made available over the Internet as an “Online X” course. The class, which MIT announced yesterday, is targeted at science, engineering, and technology professionals who are interested in learning about big data topics and technologies and bringing those skills back to their organizations.

The MIT course will be taught by 12 faculty experts from the school’s Computer Science and Artificial Intelligence Laboratory (CSAIL) at the School of Engineering. Topics will include data collection (from smartphones and sensors); data storage and processing (including relational databases and Hadoop); analytics (including machine learning algorithms); and visualization.

“With the teaching power of a ‘who’s who’ list of thought leaders on the subject from CSAIL, I am confident this course will allow industry players to not only learn of new approaches to big data, but will spark innovative thinking among teams charged with finding solutions to big data challenges,” says Bhaskar Pant, executive director of MIT Professional Education. The course runs from March 4 to April 1 and costs $495.

Meanwhile, WPI is gearing up to start a new graduate program on big data this fall. Unveiled by the university in November, the multi-disciplinary program be led by WPI faculty in the areas of computer science, math, and business, and will lead to either a Master of Science degree or a graduate certificate.

The WPI course is expected to cover data mining, big data algorithms, and data visualization. Students will get their hands on tools such as Hadoop, relational databases, IBM business intelligence software (including Cognos and SPSS Modeler), Weka machine learning software, software from SAS, Tableau, and Spotfire, as well as the R programming language.

“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,” says Elke Rundensteiner, professor of computer science at WPI and director of the new program.

The relationship between the corporate world and academia is not always a smooth one. The lack of highly skilled data scientists with university degrees undoubtedly irks the corporate bosses, who need those types of people in abundance to guide their big data projects. This situation is affecting how data analytics vendors develop their software products, including attempts to automate the algorithm work that data scientists would otherwise do.

However, some big data leaders see signs that data science production could be turning around. Pivotal’s Annika Jimenez, for one, is bullish on the prospects of freshly minted data scientists emerging from the nation’s universities.

“We should theoretically start seeing the output of the new academic curriculum around data science,” Jimenez says in a blog posting. “We should see a greater population of data scientists coming out of those programs.”

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