Upgrade Your Skillset with R Programming

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R is an effective programming language which incorporates loops, conditions, user defined functions and input & output facilities. R is a programming language widely used by data analysts, statisticians and researchers to recover, analyze, delete and present data. R programming training is designed to help students learn the concept and use of R programming to collect data from various sources by forming models and making graphs, charts and other data representation. The training program offers hands- on practical sessions, which shows R is useful tool for solving various data science problems. Here are some of the features of R that shows how R is beneficial:

  • R provides a facility of storage and effective data handling
  • It has various operators that perform calculations on lists, arrays matrices and vectors.
  • R’s programming includes exporting data, database input, viewing data, variable, missing data, etc.
  • R provides data analysis facilities and display either directly at the systems or printing at the papers.
  • R provides a vast, intelligible and integrated set of tools for data analysis.
  • R supports procedural programming that includes procedure, modules, records, and procedure calls.
  • R is an interpreted language and supports matrix arithmetic.

As R programming is mainly user run software, hence anyone can provide code improvements and innovative packages. It is a compatible platform and can runs on several operating systems. It can work with both Microsoft windows and Linux operating systems with similar clarity. Moreover, R can also perform well with data analytics tools; SPSS, SAS and MySQL.  R Programming Training in Noida is Ideal for individuals who have a keen interest to work in analytics industry and want to improve their skills with modern edge approaches. Individuals who want data analytics as their career must go for this program. This is a must learn training program for professionals from the background of Mathematics, Statistics or Economics.

  • Business intelligence professionals
  • SAS developers willing to learn open source technology
  • Software engineers and data analysts
  • Individuals aiming a career in data science
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