Data Analytics Degrees: How Can Universities Meet the Demand?
Universities expecting an influx of data science students in coming years are stepping up their investments in related data science curriculum and facilities as they prepare to serve one of the fastest-growing areas of the workforce.
Experts forecast the demand for data scientists will grow exponentially in the years ahead, with an expected 2.7 million jobs open by 2020, according to a report from IBM, Burning Glass Technologies and Business-Higher Education Forum. Those jobs will be both plentiful and financially rewarding, the report says, for those with data science degrees potentially, on average, $8,000 more annually than recipients of other bachelor’s degrees.
At the University of California, Berkley, data science professors are already seeing an increase in students signing up for their courses.
The trend represents a big opportunity for institutions to increase enrollment and improve retention by developing robust data science curricula.
MORE FROM EDTECH: 4 things universities should know when designing data science programs.
What It Takes to Build Data Science Facilities to Train Data Analysts
Investing in classroom technology and even entire buildings to support data science disciplines is one way that institutions are seeking to establish their dominance in an emerging field.
Late last year, MIT administrators announced plans for a $1 billion building devoted to data science programs. The Stephen A. Schwarzman College of Computing will serve as an interdisciplinary hub designed to teach students how to use data science — along with other emerging areas of computing —in both STEM and liberal arts studies, including political science, linguistics and anthropology.
“As computing reshapes our world, MIT intends to help make sure it does so for the good of all,” says MIT President L. Rafael Reif in an MIT newsletter. “The college will equip students and researchers in any discipline to use computing and AI to advance their disciplines and vice-versa, as well as to think critically about the human impact of their work.”
Other universities have formed partnerships with tech companies that have both expertise in data analytics and a need for future employees with cutting-edge skills.
The University of Houston, for example, now has a state-of-the-art data science institute on its campus through a partnership with Hewlett Packard Enterprise. The HPE Data Science Institute is equipped with two high-powered computing clusters designed to handle a multitude of data analytics projects.
Students also have access to data visualization theaters outfitted with a 16-foot-by-9-foot 4K screen, Sony SRX-S105 projectors and a system powered by dual Intel Xeon Haswell processors, all designed to help students explore data science in new ways.
MORE FROM EDTECH: Universities are introducing data science into liberal arts programs as humanities industries become more tech-enabled.
Data Analytics Curriculum Bolsters by Tech Company Resources
Another cost-effective way to increase data science programs at universities — and a good option for that interim period when new programs are maturing — is to adopt data science certificate programs through partners such as IBM and Microsoft. Instructors can leverage these online courses in conjunction with existing IBM Watson or Microsoft Azure licenses to augment an effective, hands-on curriculum.
At the University of New Hampshire, both students and faculty are able to take advantage of IBM Watson analytics resources. The university offers a library of video tutorials, an online workbook and data sets, as well as online courses. All of the resources can be used independently or in tandem with in-person classes at UNH.
“The end goal is to help prepare you for the new demands of the workforce and we believe Watson Analytics will help prepare the next generation of ‘citizen’ data scientists and be instrumental in helping close a critical skills gap identified in the workforce,” notes UNH’s website. “At a time where employers expect individuals at all levels of the organization to use raw data for new insights, the more prepared our students are to deliver results and insights, the better.”
This article is part of EdTech: Focus on Higher Education’s UniversITy blog series.