R Programming: The Stepping Stone for Data Science
Discussion of what language is best for learning Analysis to reach a position of Data Scientist.
Repeatedly, when discussing with people who are starting to learn Data Science, there’s a harshness that comes up which is:
“I don’t know which programming language to start with.”
And it’s not just about programming languages, it’s also about software tools like SAS, R, Rstudio, Minitab, Tableau, SPSS, JMP, etc. There is an ever widening range of tools and programming languages and it’s difficult to know which one to prefer. There are, innumerable material, numberless suggestions, numerous alternatives, and it becomes complex to be enlightened what to learn first as a first step. There’s a hill of content, and it’s difficult to get where to find the “gold treasure;” the articles to learn that will lead you to the lofty repay on time investment.
The reality is, your time is short. Intellection of a new programming language is a gigantic investment of time and efforts, so you need to be specific about which one you opt. To be analytical, some languages will generate a very supreme return on your investment (your investment of both money and time). Other languages are purely fallback tools that you might operate only a few times over a time period.
Let me make this effortless for you: learn R first.
Vogue of R has increased over the time, it is now becoming the most popular and most commonly used language over all because R developers tend to use it as a primary tool for data science projects, also it incorporates vectorized operations that are important to the linear algebra principles intrinsic in many machine learning algorithms.
Erudition the “skills of data science” is easiest in R
The admiration of R isn’t the only sense to learn R, however.
Ultimately, to really learn data science, one needs to have authority over “fundamental” skill areas: data visualization, data manipulation and machine learning. The language must be the one that has remarkable capabilities in each of these areas, accomplish each of these tasks with negligible complexity. Hence making command on these skills will be easier in R unlike other languages.
So to recapitulate, select one language. If you’re initializing, R is almost certainly the best choice, Devoting 100 hours on R will yield vastly better returns than spending 10 hours on 10 different tools. In the end, your time Rate of Investment will be higher by concentrating your efforts.
