I’m a beginner in data science and I’m undecided between learning python or R… any solid advice?
This is the most common dilemma faced by Data Science beginners. I started coding using Python because prior to entering in this field, I had some experience working with Python. It is a multi purpose language that is used widely in many fields and not only in Data science. Whereas R is only limited to Data science. R contains some good libraries for coding purposes, and is easy to grasp. Therefore you can start with both Python and R for some time and then continue with the one you felt most comfortable with.
This is a black or white question that does not have a black or white answer.
I would consider my background to start (i.e. possibly, python is most popular in engineering and/or computing sciences whereas R is the lingua franca if you come from statistics). But, at the end, you must have knowledge and practice in both of them. Remember that when work for a (big?) company, possibly, they will not even allow you to use none of those tools, because the important thing is mastering the methods. Tools are just tools.
I learnt data science with R initially, and found it very simple to understand and had enough libraries for feature engineering and modeling. Within the organisation a year later, we realized that Python is more suitable for production purposes. Also moving into the field of AI, we are realizing python being used more and more. However I could be opinionated based on my learning curve. Given I had to start today fresh, I would prefer to learn Data Science using Python…just my 2 cents