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November 13, 2014

Plotting a Big Data Career Change

When MIT opened up its “Tackling the Challenge of Big Data” course earlier this year, administrators were optimistic they had put together a good online program for working professionals to learn about big data analytics. But they had no idea it would turn out the way it did.

“It blew me away,” says Clara Piloto, Director of Global Programs at MIT Professional Education. “We did our proper diligence and did our forecasting and a lot of sales and marketing around promoting the program. But we really didn’t think we’d get close to 3,500 enrollments.”

What drove such a big turnout for MIT’s inaugural big data correspondence course? There are likely several factors involved, including the chance to virtually rub elbows with big data rock stars in the MIT CSAIL lab, such as Mike Stonebreaker, John Guttag, and Sam Madden, for a mere $500, which is the entry fee for the class.

But an even bigger factor is likely scarcity. There’s been a massive spike in interest about big data and related technologies for the past several years, but few places to get a big data education. Universities are ramping up their data science programs and adding undergraduate and graduate tracks, but these programs are focused on helping students become the next generation of data scientists.

Thankfully, continuing education programs like “Tackling the Challenge of Big Data” offer a chance for professionals to get up to speed with big data analytics, and perhaps chart a career change.

MIT’s five-week program attracted people from all walks of professional life, Piloto says. A good percentage of people had computer-oriented jobs, like programmer, analyst, and architect. But there were also a fair number of people with non-IT backgrounds, such as scientists, marketers, and CEOs.

More than 60 percent said they were big data novices, so it bringing other skill sets to the table is a requirement. “You need to be able to be creative, adaptable, and an authentic leader in order to be successful in any industry or company,” she says. “I think being a learner and curious is really important nowadays.”MITPEOXP-logo

The next generation of data scientists may feature a higher percentage of folks with big data degrees from the university programs that are currently ramping up. But many people who identify as data scientists today don’t have specialized educations in data science. In many cases, having a background in hard sciences is a big advantage.

A great of example of this are the co-founders of Datascope Analytics, Mike Stringer and Dean Malmgren, who graduated in 2009 with PhD.s from Northwestern. “Even though my degree on paper is physics and Dean’s degree on paper is chemical engineering, essentially what we were working on were big data problems,” Stringer says.

Working in the hard sciences gave them the quantitative skills that are in such high demand today. “Even though the degree says physics, it was really writing code to make sense and analyze large data sets,” Stringer says. “Anybody who has background in science or engineering, where analyzing data is a major part of what they did–that’s the type of background that’s pertinent for big data and data science.”

It used to be that Wall Street was the most prominent destination for newly minted scientists who didn’t go into the field for which they prepared. These “quants” devised the algorithms used to build complex securities models that powered high speed trading operations.

That has all changed with the big data explosion. “I think there’s still a lot of people with hard scientific quantitative backgrounds” going into finance, Stringer says. “But personally I find it exciting that….if you’re a curious person with a science or engineer background who wants to apply it to real world, then your option is no longer limited to finance. It’s really about anything.”

The big data education space is evolving rapidly and nothing stays still for long. Last week MIT started its second “Tackling the Challenge of Big Data” course. There were “only” 1,300 people signed up for the class, which is probably a more reasonable number. This will be a little longer than the first class; some attendees felt too much info was crammed into a short five-week class.

MIT Professional Education is taking applications for one more online big data course starting in early February. After that, they will look for new ways to keep the course content fresh and relevant. “Part of our value proposition is to offer the latest knowledge and research that’s coming out of CSAIL and MIT to a global audience. We hope find new ways to continue to reinvent and this course for fall of 2015.”

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Meanwhile, MIT has a lot more competition than it had just earlier this year. The guys at Datascope have teamed up with Kaplan and Metis to offer a 12-week course on big data called the Data Science Bootcamp. The class, which is slated to start in New York City in January, promises to educate participants on the fundamentals of data science and help make them familiar with big data tools like the Hadoop stack. At $14,000, it’s a bit pricier than MIT’s distance learning class, but is much more immersive too.

Related Items:

Masters of Big Data: New Graduate Programs Debut at U.S. Universities

Big Data University Programs Get Real

Six Big Name Schools with Big Data Programs

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