There are many great things about the R programming language. R is used by data scientists and programmers for statistical computing. In part because of the increasing amounts of data collected by software systems, and the need to analyze that data, R is one of the fastest-growing technologies among my colleagues who use C#.
The easiest way to learn R is to understand the basics. Doing this is simple. Because R has become so popular, the online resources are too numerous to mention. But there is a great resource to get started. Go ahead, do it now. If you have never programmed a line of code in you rlife - it is OK. This site will get you through it. If you are a programmer then very little will be new to you (and you will quickly recognize the ease and elegance R brings to big data operations.)
OK, once you have the basics, it is time to learn. I made a huge mistake in my exploration of R. I tried to learn everything. The relaity is R is too big to learn everything. Sure, you can try - and I still do - attempt to master anything and everything R, but it will drain you. This is a case of do as I say, not as I do. You might enjoy your R journey by picking out specific features and master those. For instance, visualizations in R are inspiring. Ever see a USA Today or Wall Street Journal graphic that was rich, dynamic and informative? The kind of visualization that tells a story effectively? Guess what - it was likely produced using R packages!