Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...Full Bio
Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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Get started in data science: 5 steps you can take online for free
From gaining the right skills to acing your first interview, these resources can help put you on the right track
Making a career change is never easy, but few things are more motivating than the prospect of a good salary and a dearth of competition. That's a fair summary of the data science world today, as at least one well-publicized study has made clear, so why not investigate a little further?
There's been a flurry of free resources popping up online to help those who are intrigued learn more. Here's a small sampling for each step of the way.
1. Understand what it is
Microsoft's website might not automatically spring to mind as a likely place to look, but sure enough, a few months ago the software giant published a really nice series of five short videos entitled "Data Science for Beginners." Each video focuses on a specific aspect, such as "The 5 questions data science answers" and "Is your data ready for data science?"
2. Dig a little deeper
If you think you might be interested in a career in data science, you may want to start getting a feel for the lay of the land by tapping into some of the big blogs and community websites out there. The newly revamped OpenDataScience.com is one example; KDnuggets is another useful resource. A recent post on Data Science Central (another good site) lists key accounts to follow on Twitter. KDnuggets suggests some good e-books to read before plunging into a data science career.
3. Learn the ropes
Still interested? Then you're probably going to need to acquire some skills, as Adam Flugel, a data-science recruiter with Burtch Works, noted in an interview earlier this year. DataCamp delivers instruction for both groups and individuals; other online options include Open Source Data Science Masters and this introductory textbook, which is available as a free PDF through a Creative Commons license. KDnuggets has a nice list of its own with other good options.
4. Get a job
There are lots of places to look for data scientist jobs today, including the aforementioned OpenDataScience.com, which has a section dedicated to that purpose. Kaggle has a jobs board of its own, and there are more to be found on Glassdoor and Indeed.com. Correlation One, a site that just launched earlier this year, bills itself as a matchmaker for data scientists and employers.
5. Prepare to impress
Once you get an interview, there's nothing more confidence-building than expert tips for acing it. Look no further than KDnuggets, which has published just what you need in a post entitled, "21 Must-Know Data Science Interview Questions and Answers." Good luck! Continue Reading>>