A Practical Intro to Data Science

A Practical Intro to Data Science

There are plenty of articles and discussions on the web about what data science is, what qualities define a data scientist, how to nurture them, and how you should position yourself to be a competitive applicant. There are far fewer resources out there about the steps to take in order to obtain the skills necessary to practice this elusive discipline. Here we will provide a collection of freely accessible materials and content to jumpstart your understanding of the theory and tools of Data Science.

At Zipfian Academy, we believe that everyone learns at different paces and in different ways. If you prefer a more structured and intentional learning environment, we run a 12 week immersive bootcamp training people to become data scientists through hands-on projects and real-world applications. We also host a free Skillshare course covering much of this material at a high level.

We would love to hear your opinions on what qualities make great data scientists, what a data science curriculum should cover, and what skills are most valuable for data scientists to know. Share your thoughts over at Hacker News!

_While the information contained in these resources is a great guide and reference, the best way to become a data scientist is to make, create, and share!

A simple guide to getting started with data science

There are many articles on this subject from renowned data scientists (Dataspora, Gigaom, Quora, Hilary Mason). This post captures my journey (a software engineer) on learning Statistics and Data Visualization.

I'm mid-way in my 5 year journey to become proficient in data science and my learning program has included self-learning (books, blogs, toy problems), projects at work, class-room training (Stanford), teaching/presentations, conferences (UseR, Strata). Here's what I've done so far and what worked and what didn't...