R is an open source programming language and software environment, commonly used for statistical computing within data heavy roles such as data mining and statistics.

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R has had a resurgence in recent years with a growing number of programmers using its data generation and analysis capabilities within machine learning and other emerging data-dependant technologies.

We discuss why you should learn and use R and how to get skilled up.

Why should I learn R programming language?

While R can seem overly complex at the start, for those looking for a programming language with a lot of meat on the bones, R is worth your consideration.

In fact, a number of well-known organisations are taking advantage of R's impressive statistical features.

Some Facebook employees are using R to analyse user behaviour, while over 500 Google employees are using R to make its advertising more effective, says Revolution Analytics.

R uses command-line scripting, which is ideal for storing numerous series of complex data-analysis and recycling that analysis' on similar sets of data.

R is totally free and open source, so unlike its rivals such as SAS or Matlab, R can be customised, cloned and even redistributed.

One of the biggest benefits to open source software is that upgrades to the software are much more regular.

This is extremely advantageous for statistical programming languages and environments.

R is available on Windows, Linux and Mac OS X and able to import data from a whole host of programmes including Microsoft Excel, MySQL and Oracle.

R really is a data analyst or statistician's dream - it packs a punch. R is able to handle an incredible amount of data and its two million users can vouch for that.

In fact, one of R's selling points is that exact community. R's large and active online community supply a myriad of documentation, tutorials and online query forums.

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How do I learn R programming language?

If you're not 100 percent sure that R is for you, you might want to take an introductory course. Online video courses are very popular and won't break the bank. 

Udemy offers a range of online classes for R and statistical programming languages as a whole. These can start at around £10, so why not give it a shot. 

Another popular route for those with a background in programming is to just get stuck in. 

Just visit r-project.org to install and get started.

While you don't need any additional downloads to begin working with R, it is a good idea to install RStudio, the free R integrated development environment (IDE).

This studio includes useful features to make the learning process a little less daunting from syntax highlighting and code auto-completion. 

You'll be able to take advantage of lots of online tutorials and documentation, including coding shortcuts, here.

For a full guide on getting started with R, see here.

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