Become A Data Scientist... In 12 Weeks?

San Francisco-based academy claims to turn qualified applicants into big data gurus in less than three months.

Jeff Bertolucci, Contributor

September 13, 2013

4 Min Read
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 Big Data Analytics Masters Degrees: 20 Top Programs

Big Data Analytics Masters Degrees: 20 Top Programs


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What's the best way to become a data scientist? Well, you could earn an advanced degree from an accredited university, a process that may take several years and cost tens of thousands of dollars. Or you could go the express route: A 12-week boot camp that teaches the pragmatic skills needed to land a data science gig at a reputable business.

One such fast-track school is Zipfian Academy, a San Francisco-based facility that this week is welcoming its first class of data science students. Its goal is to teach its students what they need to know to be proficient data scientists in just 12 weeks.

Certainly the Zipfian Academy isn't alone in this field, as a quick Web search readily demonstrates. Major universities are in on the action too. In July, for instance, the University of California at Berkeley launched its Master of Information and Data Scienceprogram, which school officials called the nation's first online master's degree program for data scientists.

Zipfian already has partnered with several major tech companies, including Facebook and LinkedIn, all of which need data scientists to analyze their growing big data workloads.

"A few of these companies actually reached out to us," said Zipfian Academy cofounder and instructor Ryan Orban in a phone interview with InformationWeek. "They're very excited about what we're doing, and the fact that we're a data science-, data engineering-focused academy that's focusing on the practical skills necessary to be effective as a data scientist."

[ Implementing a big data plan for your organization? Don't begin with the end in mind. Read more at Big Data Planning: Start Slow, Let It Grow. ]

About 220 applicants vied for just 13 spots in Zipfian's inaugural class, which started its intensive 12-week program this week. "[The selected students] range from various quantitative backgrounds -- business analysts, statisticians, PhDs, master's degrees -- and all have a general programming knowledge," said Orban.

How does a new data science school attract candidates from students and major tech companies?

"We spread by word of mouth," recalled Orban. "In the very beginning, we targeted a few prominent data scientists and data science blogs in order to get our message out there. It pretty much spread like wildfire. There's incredible demand, not just from companies looking to hire data scientists to distill information from their data, but also from people looking to make transitions into this new field."

Zipfian's small cadre of instructors has plenty of hands-on data science experience. Cofounder and instructor Jonathan Dinu, for instance, previously worked for data science firm Alpine Data Labs, where he developed distributed machine learning algorithms for predictive analytics on Hadoop. And another instructor, Paul Duan, currently works as a data scientist at Eventbrite, which also happens to be one of Zipfian's business partners.

Applicants be forewarned: The program is pricey. If you make the cut, Zipfian's 12-week course will set you back a whopping $14,400. On the plus side, the Academy offers payment deferral plans (up to 1/2 half of the tuition) and a $4,000 reimbursement to graduates who accept a job through Zipfian's hiring program.

"Many of our students come from academic backgrounds or research positions, and they might not have the available tuition," said Orban. "So we try to work with them to make the program a good fit."

A data scientist needs good communications skills, and the Zipfian course addresses this requirement. "At the end of this project, not only do you have a full data science project under your belt, but we also require you to write up and present your results, because your insight is only as good as how effectively you can communicate it," Orban said. "If you're talking about complicated predictive models, you need to not only understand how they work, but also be able to explain how they work in layman's terms so that people can understand them and get on board."

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About the Author

Jeff Bertolucci

Contributor

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, The Saturday Evening Post, and InformationWeek.

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