People love to make pronouncements about a year. 2016 is the Year of … what? Data? That certainly doesn’t seem possible, given that we’ve been talking about data—both big and otherwise—for some time now. And yet, there was Glassdoor, rating Data Scientist as the #1 Best Job in America for 2016. They weren’t the only ones either. CareerCast.com put Data Scientist at #1 as well. These two studies have been so extensively cited that it’s essentially become a given that Data Scientist is one of THE hot jobs of today, and of the future as well. So how do you prepare for a data science career? Let’s begin by looking at the skills you’ll need.
Projects are at the heart of our approach to learning. We believe you should learn by doing, and when you’re a Udacity student, projects are what you do. They’re how you learn, and they’re how we assess your learning. Ultimately, they’re also how you’ll demonstrate what you’ve learned. From the moment you enroll, to the moment your portfolio earns you the job offer, it’s all about projects.
Udacity projects can be hard work, and the stakes are often high. Expert project reviewers are standing by at any hour of the day, ready to deliver detailed assessments of your efforts. Between you and your Nanodegree credential, there is a path marked with projects that must be mastered before you can advance. You’ve got your work cut out for you. Sound fun?
It is! And to prove it to you, we’re going to look at five different projects from five different Nanodegree programs that are really, really fun!
Didi Chuxing may be one of the most electrifying companies in the world right now. The Chinese ride-sharing service just received a $1 billion dollar investment from Apple, and is poised to grow significantly in the coming year. Which is why we are thrilled to partner with Didi on the global Di-Tech Algorithm Competition, which boasts a $100K prize for the winner, and perhaps more exciting, the opportunity to join the Didi Research Lab and work on innovations that will affect hundreds of millions of riders.
Excited to talk about Machine Learning, Data Science, and Artificial Intelligence? Great! Us too. Ready to discover the key influencers you need to follow to stay current on all the latest happenings in these fields? Excellent! We’ve got the resources you need.
You see, at Udacity, we talk a great deal about Machine Learning, Data Science, and Artificial Intelligence. We talk to each other, we talk to our students, and we talk to the world at large. If you’re engaging in these same kinds of conversations, then you know how incredibly exciting these spaces are—everywhere you turn, there are more amazing voices with more amazing insights to contribute.
But honestly, it can be a little overwhelming!
At Udacity, we strive to be as responsive as possible to student queries of all kinds, and virtually every member of every team gets the opportunity to speak directly with students at one time or another. This is in fact one of the most gratifying things about working at Udacity, this direct connection to our students.
When certain subjects and topics start to come up with more frequency, we often turn to a particular Udacian for insight. One subject that has definitely come up a great deal lately is the question of how to get data projects online. To speak to this matter, our own Mat Leonard—a Udacity course developer—is here to offer some thoughts and experience!
First, a bit of “official” background on Mat:
Mat Leonard earned a PhD in Physics from UC Berkeley, where he wrote his dissertation on neural activity related to short term memory. When it came time to make sense of his data, he turned to Python and the science stack including Numpy, Scikit-learn, and Pandas. He created his personal blog, Matatat.org, to publish small data projects online. For example, he explored linear regression models for predicting body fat percentage and a Bayesian approach to A/B testing.
Few jobs have been surrounded by as much hyperbole as has Data Scientist. Most famously, the Harvard Business Review referred to is as “The Sexiest Job of the 21st Century.” With hype like that, a backlash is inevitable, and there certainly was one, with some of the more apocalyptic voices even stating that the role would be replaced completely by automation within a decade.
That’s not going to happen.
There is virtually no field in the modern employment landscape that does not rely on data. The Oakland Athletics made data so famous it became a Brad Pitt movie!
But when I ask you what you want to be when you grow up, are you likely to say “Data Analyst?” Probably not. Why is that?
Could it be a holdover sentiment from another era, when data really wasn’t very exciting? Say “data” to some people and it may conjure in their minds images of anonymous automatons squinting through bifocals at reams of seemingly unintelligible numbers as they sit hunched over drab desks in drab offices producing drab reports for drab enterprises that do drab things.
Or maybe it’s the idea that data only ever sits in the backseat? Data provides the numbers, but someone else goes out and gets the glory? Data cast as the perennial Cyrano de Bergerac?
Maybe data just seems too hard?
Whatever the reasons why Data Analyst may not be tip of tongue when it comes to career choices, it may be time to revise any prevailing assumptions about the field, because data has never been hotter as a career. Why? Because EVERYONE needs to know how to collect it, analyze it, contextualize it, report on it, and act on it.