5 Reasons to Drop Everything and Learn R

Don’t drop everything yet. R is a programming language, so unless you’re an experienced developer, setting your current obligations aside and learning R might not be in your best interest

But if you are a coder, read on. There has never been a more exciting time to learn R, and there’s a plethora of reasons why this is the case. R, of course, is a statistical language that produces precise visual representations of data. As business intelligence and analytics become integral across several different verticals, the reasons for learning R just keep stacking up.

r programming

Here are five of them:

  1. Be an early adopter.

If you want to impress a future employer or are looking to merge your programming prowess with the upsurge in demand for data, learning R might be just the ticket. The same goes for entrepreneurs who want to create a data-centric app or add data-related functionality to an app they already have in mind.

If you get your R training now, you’re still an early adopter. The demand for your skills is growing, and in the next few years there should be an even greater need for them.

  1. Use it on any platform.

R runs on everything. Windows. Mac. Linux. No matter which OS you use, it’s absolutely possible to start learning R today.

  1. Integrate with other languages.

We all know that languages like Ruby on Rails and Python are in high demand. They’re used to create some of the most common applications that businesses and consumers rely on.

If you’re already proficient in one of these admittedly more ubiquitous programming languages (Java and C++ included), knowing R can help you add a statistical analysis element to the apps you’re working on. It’s a feature many organizations can use to add useful functionality.

And as data analysis becomes preeminent, it’s already a key component of many new apps – especially in the B2B space.

  1. Join the community.

The R community is large, and it’s getting bigger. As an open source programming language, R’s very nature fosters an active, inquisitive community of programmers and data scientists who are passionate about stats and figures.

They’re also passionate about helping each other learn. Working toward R proficiency means gaining experience with some of the world’s best tutors – most of whom “work” for free.

  1. Get 2000 free library cards.

Whether it’s finance, cluster analysis, high performance computing or any of a number of different statistical areas, there are over 2000 free R libraries available for your unlimited use.

It’s just another benefit of joining the R community. With resources galore and a network of experts ready to guide you, R has a relatively low barrier to entry when compared to some other languages.

Granted, R has a reputation for being hard. That’s why it’s absolutely necessary that the learner (that’s you) take full advantage of these resources. In the end, you’ll know a language that few others can work with and that’s in increasing demand.

And that’s never a bad position to be in. Never.

 Author Bio:

Hank Phalstaff contributed this post on behalf of Revolution Analytics, which helps organizations boost data mining effectiveness through R analytics solutions.

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  1. Well learning R sounds like an interesting endeavor I think I’ll stick to the languages I’m comfortable with.