Data science—the “science” of gathering and parsing the enormous flood of data pouring into America’s more technologically-adept firms—is so hot that even US president Barack Obama has declared it an educational priority. The Harvard Business Review called data science “the sexiest job of the 21st century” (paywall). Startups are producing so much data they’ve become “frantic” to find more data scientists, making salaries on the order of $300,000 a year not unreasonable.
But becoming a data scientist is no easy feat. You’ll need a grounding in statistics and the basics of computer science, or a willingness to learn both. As SAP noted, “Data scientists combine the analytical capabilities of a scientist or an engineer with the business acumen of the enterprise executive.”
Traditionally, you’d have to pay a place like UC Berkeley $60,000 to attend school full time for two years in order to get a Master’s degree in Data Science. But what mid-career switcher has that kind of time or money?
Enter Udacity, the online education startup. For about $2,000 and two months’ effort, students will soon be able to take a course in data science at Udacity taught by a Facebook engineer or an engineer from retail startup Yub. A “degree” from Udacity won’t have the cred of a sheepskin from Berkeley, but considering how quickly the field of data science is moving, students might be better off learning directly from teachers who are currently practicing data science, anyway. And for those who want to try out a site that’s still in progress, a startup called DataCamp is working on a beta of a self-teaching course for data science—current price, $0.
The recent crop of online courses in data science adds to a growing pile of online and in-person schools offering coding or startup education.
As an alternative to traditional degrees in data science, which are increasingly common, online courses are a quicker avenue to learning on the job. That’s a wise move considering how varied the field of data science has become—these days being a data scientist could involve anything from working in the fraud department of a bank to the analytics desks of a media company.