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November 14, 2013 06:00 pm GMT
Hot on the heels of a new $37 million White House initiative designed to encourage data science work at American universities, education startup, Udacity, is responding with a data science initiative of its own. Today, the Palo Alto-based company launched an inexpensive, comprehensive degree program that will allow anyone with basic computer science skills to get schooled in the wild and woolly world of data science. It’s a good thing, too, because as smart sensors, devices and networks proliferate, computing power and capacity expand, and everything becomes increasingly “connected,” we’ve officially entered the Data Era. The amount of data the world creates today, and the amount of data now available at our fingertips, is exploding. Exponentially. As a result, data analysis, data munging, cleaning, transforming and everything in between are now terms and jobs that every industry is familiar with — and data scientists of every stripe are in high demand. But there’s a problem. While “Big Data” is the buzzword of the day, and many companies are scrambling to hire these elusive and expensive data wizards, the word on the street is that they’re in low supply. And the forecast doesn’t look good. “There is a shortage of big data experts,” said Michael Rappa, the Director of Advanced Analytics at North Caroline State University in a recent interview with Federal Computer Week. “I don’t see the gap narrowing. Universities aren’t producing enough.” TechCrunch readers are likely familiar with the work of data scientists in some capacity, even if they couldn’t pick one out of a lineup. But just in case, if Facebook or Google ads have ever suggested things eerily familiar to your personal life, well, you have your friendly neighborhood data scientist to thank for that. He or she likely played a role in architecting the very preference-predicting algorithms that brought you that ad. Now, to be clear, data scientists come in many shapes and sizes — quantitative, operational, marketing, product, predictive modelers, statisticians, engineers, miners, visualizers, warehousers, machine learners and so on — and they perform many different roles within an organization. However, boiled down, a data scientist’s job is to mine reams of digital static and noise (content, user behavior, whatever it may be) in search of a signal. Data scientists, among other things, help identify patterns and glean insight from our ever-changing datasets. Luckily, with the list of potential applications for data science in the
Original Link: http://feedproxy.google.com/~r/Techcrunch/~3/axzXqTQCoe8/
Education Startup Udacity Bets It Can Fill The Need For More Data Scientists With New Online Degree Program
Hot on the heels of a new $37 million White House initiative designed to encourage data science work at American universities, education startup, Udacity, is responding with a data science initiative of its own. Today, the Palo Alto-based company launched an inexpensive, comprehensive degree program that will allow anyone with basic computer science skills to get schooled in the wild and woolly world of data science. It’s a good thing, too, because as smart sensors, devices and networks proliferate, computing power and capacity expand, and everything becomes increasingly “connected,” we’ve officially entered the Data Era. The amount of data the world creates today, and the amount of data now available at our fingertips, is exploding. Exponentially. As a result, data analysis, data munging, cleaning, transforming and everything in between are now terms and jobs that every industry is familiar with — and data scientists of every stripe are in high demand. But there’s a problem. While “Big Data” is the buzzword of the day, and many companies are scrambling to hire these elusive and expensive data wizards, the word on the street is that they’re in low supply. And the forecast doesn’t look good. “There is a shortage of big data experts,” said Michael Rappa, the Director of Advanced Analytics at North Caroline State University in a recent interview with Federal Computer Week. “I don’t see the gap narrowing. Universities aren’t producing enough.” TechCrunch readers are likely familiar with the work of data scientists in some capacity, even if they couldn’t pick one out of a lineup. But just in case, if Facebook or Google ads have ever suggested things eerily familiar to your personal life, well, you have your friendly neighborhood data scientist to thank for that. He or she likely played a role in architecting the very preference-predicting algorithms that brought you that ad. Now, to be clear, data scientists come in many shapes and sizes — quantitative, operational, marketing, product, predictive modelers, statisticians, engineers, miners, visualizers, warehousers, machine learners and so on — and they perform many different roles within an organization. However, boiled down, a data scientist’s job is to mine reams of digital static and noise (content, user behavior, whatever it may be) in search of a signal. Data scientists, among other things, help identify patterns and glean insight from our ever-changing datasets. Luckily, with the list of potential applications for data science in theOriginal Link: http://feedproxy.google.com/~r/Techcrunch/~3/axzXqTQCoe8/
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