Data science is among the trendiest fields in technology. The demand for data science professionals is huge – so much so that Glassdoor named it the number-one job in America for four consecutive years. Despite the buzz it generates, data science is intimidating for many programmers since it requires a strong mathematical backbone and is unapproachable for mathematicians because of coding prerequisites.
That’s why the discrepancy between demand and supply in data science is vast. There’s a word in the street that, if you want to acquire skills that’ll land you jobs, data science is your best option.
At the start of your data science journey, you will need to choose a programming language to run algorithms. There are many programming languages developers use, such as R, Clojure, Julia, or Scala.
In this post, however, I’d like to compare two languages that lead Stack Overflow’s Top Software Development Languages survey – Python and Java. Let’s discuss the benefits, drawbacks, and applications of these technologies in data science.
