Interested in landing a job as a data scientist? Now’s a great time to choose a career in data science—Glassdoor has once again named Data Scientist the #1 best job in America. But how do you get your foot in the door, and what does it take to succeed?
What IS Data Science?
Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. This can be daunting if you’re new to data science, but keep in mind that different roles and companies will emphasize some skills over others, so you don’t have to be an expert at everything.
Apply today for an opportunity to master valuable Data Science skills with a Udacity scholarship from Bertelsmann!
Lifelong learners across the globe interested in pursuing careers in Data Science have a fantastic new opportunity to achieve their dreams. Today, Bertelsmann formally announced 15,000 new Data Science scholarships for study with Udacity. Following on the 60,000 scholarships announced by Udacity and Google in September 2017, this brings to 75,000 the total number of scholarships offered through the partnership of Bertelsmann, Google, and Udacity.
If you ask a data scientist how to start or advance your data career, one of the first things they’ll tell you is to read. Not the answer you’d expect? You’d be surprised! Data scientists constantly read and explore what’s happening in the rapidly changing data landscape.
If you’re just getting started in the field, understanding current industry trends can set you apart in the job interview process, making it clear that you’re someone who is engaged and knowledgeable about the data science space.
Teaching at the forefront of technology—as we at Udacity are fortunate to do—is both exciting and challenging. To fulfill our promise to our students, it’s critical we maintain the up-to-the-minute relevance of our content at all times. Given how fast technology changes, this process is pretty much ongoing, every day. Sometimes the changes are minor; an upgrade here, a new version there. Other times, the opportunity presents itself to engage in a significant program overhaul.
A Complete Path to a Data Career
The recent launch of our Data Foundations Nanodegree program presented just such an opportunity. The addition of this new program has made it possible to now offer a complete path to a data career. But, changes to other programs in our data ecosystem—which includes the Business Analyst and Data Analyst Nanodegree programs—were necessary to fully optimize this path for our students.
We’re very excited today to share details with you about new changes we’ve made to the Data Analyst Nanodegree program.
When choosing a career, there are safe paths to pursue, and there are risky ones.
A career in data offers the best of both worlds. On the one hand, it is a secure choice—demand for data talent continues to increase, and shows no sign of abating. With data skills in your toolkit, you’re going to be in demand in virtually any industry. On the other hand, it’s a brave new world out there. We’re producing massive amounts of data, and that data is making amazing new things possible. But, the methods and strategies we’re having to continually invent to harness all that data means the future is continually being redefined in real time. Those on the data front lines are at the forefront of technological progress.
The good news is, that no matter which route you take—the secure one, the risky one, or something in between—there are ample career opportunities out there for anyone interested in data.
But, how do you actually get started?
That’s where this guide comes in. At Udacity, we’re extremely fortunate to collaborate with some of the most forward-thinking companies in the world, and we work with some of the most innovative thinkers and creators in the data space. Our hiring partners represent some of the best career opportunities in the field, and are a critical source of information about what companies are seeing in their data hires.
We’ve marshaled all these resources together to create this guide for you, and all of our expert contributors offer unique perspectives and experiences. If you’re interested in pursuing a career in data, this is your complete guide. To access the guide, just enter your email address below:
The exponential rise of machine learning is as much a result of technological advancement as it is the active community growing around it. This includes researchers working on core algorithms, as well as practitioners who are pushing the boundaries of how machine learning can be applied. It also includes an increasing number of machine learning enthusiasts with atypical backgrounds who are joining the conversation, bringing in diverse experiences and points of view.
Discovering and Attracting Machine Learning Talent
The increasingly symbiotic relationship between companies that need machine learning expertise, and data science competition platforms like Kaggle, has greatly impacted how rapid advancement is being achieved. This relationship has also changed the hiring landscape. Companies today face ever-increasing pressure to innovate in order to remain competitive, and they are pursuing comparatively unconventional means for discovering and attracting new talent in order to maintain their edge. The need for machine learning talent is so great, that companies are looking far further afield than once they might have.
The pursuit of educational inclusion brings us into close contact with an absolute wealth of wonderful organizations—motivated communities united around the noble goal of ensuring that any and all aspiring learners have the unfettered opportunity to pursue self-empowerment through education.
Women Who Code
Women Who Code is just such an organization, and we were recently able to work with their Silicon Valley chapter on an event that we hosted here at Udacity HQ.