What is R Programming?

R is a statistical programming language with object oriented and functional programming structure that helps statisticians and data scientists in intricate and complicated data analysis to gain business insight.The language is actively used by data miners and statisticians to develop data analysis tools and statistical software.

R is a component of the GNU project and is open-source freely available under the GNU General Public License. Virtually every operating system can avail of the free binary versions that are pre-compiled and runs on a number of UNIX platforms, MacOS and Windows.

The suite of software created with R facilitates the integrated calculation, manipulation and graphical display of data, including:

  • Effective storage and handling of data
  • Data analytics tools
  • Graphical representation of analysed data
  • Recursive functions with output and input facilities

Though many of those that use R consider it a statistical system, it actually is more akin to an environment that contains statistical techniques that are being implemented.

Benefits of R Training

To begin with, R language is like a magic wand for data scientists, which allows them to manage and analyse humongous amounts of unstructured and complex data. That said, R is not an easy language to learn and apply. You have to learn it through a training course that gives you comprehensive theoretical knowledge and sufficient practical experience of using it. But looking at all that you can do with R, it is worth learning.

Here are some of the many convincing reasons for you to learn R programming:

Platform Independent Language: The language is completely platform agnostic, and besides running on Mac, Linux and Windows, it is also known to run on a few mainframe operating systems.

Can Manage Petabytes of Data: Though the R language is known to be a memory guzzler, certain commercial versions of R make handling a huge amount of data hassle-free.   Petabytes of data are managed easily by working it on parallel processors, using an analytic algorithm known as ScaleR.

More than a Statistics Tool: R is a lot more than just a tool for statistics. While making the most of the speed of complied code, programmers can reap the benefits of a language that is interactive and supports complied code embedding in other languages such as C or Fortran. C++, Python and Java are also popular languages being embedded with R.

Extensive Online Community: R language has a mammoth community on line that shares, supports and reviews with you to help make you perform better. It almost is a continuous training even after having learnt the language, giving you insights of the many new possibilities with it.

Free Open-Source Code: Besides being able to use it for free, programmers can access the source code and make improvements which goes on to help the entire community of programmers using R.

Incorporated in Programs: Widely accepted and use programs, such As SAS and SPSS have special tools written to allow its data read by commercial programs that are used by statisticians.

Lucrative Salary:For those sinking their hopes into making a career in data science using R programming will be pleasantly surprised to know that an R Programmers salary is as well-paying, if not more, than that of a MapReduce or NoSQL programmer.

Who should learn R-Programming?

This course is for all enthusiasts of data science. But to get more specific:

  • Business Analytic professionals
  • Software professionals that want to delve into data science
  • Anyone with a background of statistics ad economics with a penchant for data analytics
  • Anyone and everyone that has a keen interest in data analytics

Prerequisite

Though basic statistics knowledge could be considered a prerequisite, it is nullified because the training course has a module that trains newbies on basic statistics required for R. So effectively, anyone with  the desire to be in the data science and analytics field is the right candidate to learn R-Programming.