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R is an open source programming language which has quickly gained huge popularity in the statistical software industry. With millions of statisticians and data scientists using this language all over the world, its popularity is expected to grow rapidly in the coming years. R can be considered as a statistical analytical package which includes all types of models, tests and analyzes for manipulation and management of data. Those who wish to grow their career in the world of data science should definitely opt for R Programming Training. Why R Programming Language is Hugely Popular among Data Scientists R offers businesses

Since the advancement of Data Science is capturing more popularity. Job opportunities in this field are more. Therefore, in order to gain knowledge and become a professional worker, you need to have a brief idea about at least one of these languages that is required in Data Science. PYTHON Python is a general purpose, multiparadigm and one of the most popular languages. It is simple, easy- to-learn and widely used by the data scientists. Python has a huge number of libraries which is its biggest strength and can help us perform multiple tasks like image processing, web development, data mining,

Data Science is a study of analyzing data in different aspects. In several cases of consideration of data analysis, there is a general abstract framework that describes a basic structure on how data has to be designed. For example, in the generation of music notes, there’s a certain criterion like using only particular music notes for the respective tunes. Describing data analysis is a difficult conundrum. Developing a framework involves considering the elements of the data and implementing it using programming language. Why should we use programming languages for data analysis? As we know, data is used in many streams

Data science requires mastering in various fields like machine learning, R programming, Python, deep learning and many more. Among all these, one of the basic key programming languages required for every data scientist is R programming. These programming languages helps a data scientist to collect data, create visualization, perform predictive and statistical analysis and to communicate the course of results with stakeholders. Basics of R programming language: It is a programming language developed by Robert Gentleman and Ross Ihaka. It deals with various concepts of graphical and statistical methods. It includes statistical interference, linear regression, and machine learning algorithm, time