Data science has captivated you, making you interested in learning what is it all about and how can you use it to build your career in academia or industry. Then, you try to find resources to learn this new craft and you stumble into a world of intricate acronyms: , dplyr, , numpy, , ggplot2, , and the list goes on and on.

Why should you dedicate your precious time into learning a language that is almost never mentioned in any job listing, lab position, postdoc offer, or academic job description? The answer is that Julia is a fresh approach to both programming and data science. Everything that you do in Python or in R, you can do it in Julia with the advantage of being able to write readable2, fast, and powerful code. Therefore, the Julia language is gaining traction, and for good reasons.