TLDR;

In short, what matters most as a beginner in Data Science is that you DO Data Science. So just go with either one of the languages and prioritize getting some projects done. That’s how you will learn the fastest.

While I may be tempted to just recommend Python straight-away (Python is my main, but I do have some working knowledge of R), I want to present an unbiased evaluation of the effectiveness of the two languages for a beginner. This is mainly because the right choice is most definitely going to depend on your own particular situation.

Why do you want to learn?

The first and probably the most important factor you must consider is the reason WHY you want to learn. If you are a trained biologist, for example, looking to pick up some programming skills so you can better understand your dataset, or you are familiar with other scientific programming languages like MATLAB, then you should consider watching some R tutorials on YouTube because it would be simpler and more intuitive for you than Python. Or if you are a software engineer proficient in other languages like C/C++ and Java and would like to pivot into Data Science, Python would be the one to go with as just like most other popular programming languages, Python is an Object-Oriented Programming (OOP) language and it would be much more intuitive to you than R. Or, maybe you have been reading up about the fascinating field of Data Science recently and would like to dabble into it. In that case, either would really be fine and it would depend more on the other factors than this one.

#data-analytics #data-science #python #r #developer