UC Berkeley Pioneers an Online Master’s Degree in Data Science
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machine learning—the creation of algorithms to detect patterns in big data sets. Classes will be taught by tenured faculty who have helped design the curriculum, Saxenian says. Students can complete the degree program in 12 to 21 months.
The School of Information created the program in a partnership with the online education company 2U Inc. of Landover, MD, which helped finance the initiative, and will split the tuition revenues with UC Berkeley. 2U provides an interactive online classroom for live sessions, student support, and other services. The company has similar partnerships with other graduate schools, including the University of Southern California School of Social Work and USC’s Rossier School of Education.
UC Berkeley has two other graduate degrees offered primarily online—the Master of Advanced Study in Integrated Circuits, and the Masters in Public Health. Saxenian says her school’s data science program is the first to collaborate with an outside education technology company. Accreditation for online degree programs, especially those designed in concert with outside companies, has been a contentious issue of late, but the new Berkeley degree MIDS has received interim approval from the accreditation body overseeing California schools—the Western Association of Schools and Colleges—and final approval is expected by the end of October, according to a 2U spokesperson.
The full program will cost about $60,000; students may be eligible for federal financial aid. Admission will be selective—a maximum of 30 students will be chosen for the inaugural class. The final application deadline is Nov. 14 for the session that begins Jan. 14.
Students will attend a one-week immersion course in South Hall on the Berkeley campus, which will include opportunities to visit companies in the Bay area. Once established, the program could possibly be scaled up, Saxenian says. But it’s too soon to say how many students it might one day accommodate.
“The first and foremost thing is insuring quality,” Saxenian says. “Then we’ll figure out how many students we can take.” If the program grows, the school would work to keep the original faculty engaged by teaching some sections and helping new instructors, who might be professional practitioners in the data field, alumni of the program, or post-doctoral students working on their own research in data science.
An expansion might make it possible for the school to offer specialized degrees in data analysis for particular fields, such as health care, education, or data journalism, Saxenian says. A scale-up might also provide the means to create fellowships for students who want to work in the non-profit sector or other lower-paid professions, Saxenian says. But many students will be able to recoup their investment in the degree, she says.