Here is how to begin your data science journey:
- Buy a book on modern data science, avoid statistics textbooks re-labeled as data science like plague: they will lead you to nowhere. Any public-domain stuff that's been invented 50 years ago will lead to a job that will eventually be replaced by a robot - we are working on this to make it happen. If you have an analytic background, my book is a good start. Older versions are still available for free, but the Wiley version is much more organized and easy to read, and costs less than $25. Other books can be found in the reference section below. In April, We will publish a new book data science 2.0. initially available for free to Data Science Central members. This book will have more source code, even advanced spreadsheets, and detailed explanations on many data science concepts.
- Read our data science cheat sheets: the version for beginners, or the more advanced version, depending on your background. Also read our resources section where you will find articles featuring plenty of useful external links about Python, machine learning, deep learning, Hadoop, R programming and more. Also check out the reference section at the bottom of this article: it offers a selection of books, training, conferences, jobs, salary surveys and other career-related stuff like job interview questions for data scientists.
- Get data and work on real projects. Check out our project list for data science apprentices. Schools like Zipfian Academy are worthwhile, though it's tough to be admitted (you need a PhD).
- Launch your career: apply for a job at AnalyticTalent.com, create your start-up (here are a few ideas for data scientists, check also this link), collect and sell data (for instance, stock market forecasts delivered via an API), become a consultant, or a digital publisher like us. And don't forget to connect with practitioners on DataScienceCentral.com - you will find people interested in your ideas, and able to help you, if you contribute intelligently.
Source for picture: InsideBigData
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