**DataScience+**, and kindly contributed to R-bloggers)

R is an open source programming language with a lot of facilities for problem solving through statistical computing. At the time of writing this, there are more than 6K packages available in CRAN repository.

R is a language and an environment for everything related to data analysis. That includes statistical computing, data mining, data analysis, machine learning, predictive modelling, quantitative analysis, optimization and operations research etc – all of which are somewhat inter-related terms. Data scientists, analysts, statisticians, quantitative analysts, forecasters, bio-statisticians, financial analysts, research scientists. These are some of the professions where R is commonly used. But, is R limited to these guys? NO, and not necessary!

But before you get to the machine learning part, you need to first nail the basic R language, which is what this whole tutorial is all about. Besides, R is the best platform to master this vast spectrum of knowledge. This tutorial below is the first part of the planned 3 part video tutorial series that explains the core concepts in the simplest terms. So, Lets begin.

## Course Content

Find below all the video tutorials for this course.

That is! If you have questions or feedback, feel free to leave a comment.

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**DataScience+**.

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