I'm interested in learning programming purely for fun, starting from almost zero. My main interests are artificial intelligence, machine learning, data science, statistics, data visualization, and scientific computing—not getting a programming job or changing careers. R appeals to me because it is designed around statistics, data analysis, and visualization, but I'm unsure whether it is also a good language for learning general programming concepts. I've also considered Python and Julia. For someone learning mainly out of curiosity, would R provide a solid and enjoyable foundation, or would Python or Julia be a better place to begin? I'd especially appreciate perspectives from people who have learned or used R or Julia as hobbyists.
5 Answers
Python is the most practical starting point for your particular interests. It is relatively approachable, has a huge amount of learning material, and is widely used for AI, machine learning, scientific computing, and data analysis. It also gives you a broader foundation in functions, control flow, data structures, and general programming before you move into specialized tools. R can still be worth learning later, especially if you prefer its statistical and visualization workflow.
There is no rule that says you have to pick the theoretically best language. Since this is a hobby, motivation matters more than convention. If R makes you excited to explore data, start there and build a small project. You can always add Python later; the core ideas—variables, functions, loops, conditionals, and data structures—will transfer. A general-purpose language such as Python simply gives you more possible directions afterward.
Some people recommend C or C++ because they expose memory and lower-level machine details, but that is not necessary for your goals and may add frustration without helping you reach AI, statistics, or visualization projects sooner. Start with the language that lets you make things you care about, then study lower-level topics later if curiosity takes you there.
R is excellent for statistics, data frames, visualization, and modeling, so it matches your interests well. However, it is more specialized than general-purpose languages, and some of its syntax and behaviors can be unusual. It may teach you habits that do not transfer as directly to other languages. If your main goal is analyzing data, starting with R is completely reasonable; if you want a broader programming foundation, Python is probably the safer first choice.
That makes sense. I’m leaning toward Python first, then trying R once I have the basic concepts down.
R is not a bad choice if the projects you want to make are statistical analyses or visualizations. You could learn by importing a small dataset, cleaning it, calculating a few summaries, and creating plots. Just be aware that R’s data-analysis style can hide some lower-level programming concepts, and its ecosystem is more niche. Julia is interesting for numerical and scientific work, but it has fewer beginner resources and a smaller ecosystem, so I would not choose it as the first language unless you are especially excited by it.
Python has quirks too, but the abundance of examples and libraries makes it much easier to get unstuck as a beginner.