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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.

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

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Why should I learn R programming language?

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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.

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

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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.

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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.

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

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

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This is extremely advantageous for statistical programming languages and environments.

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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.

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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.

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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?

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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. 

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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. 

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

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

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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).

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

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

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

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