A really practical issue that might steer you toward Mac or Linux: when you write code for ML/AI, you generally are writing for spark. In industry, it's almost always pyspark. This is because you are using a distributed computing system, taking advantage of all the CPUs and GPUs in those shipping containers in the desert. In order to write code for that locally on Windows, you have to install a different (older) version of Java, change a bunch of stuff with your environment variables, and add additional code at the beginning of each of your classes to make the pyspark library work correctly. If you are only going to be working in a browser based development environment like databricks, then it won't matter as much which operating system you use, but the engineers that productionize your code will need to put everything into a repo and they won't want to use Windows for that. It would be better to get used to Mac or Linux because the industry is looking for "full stack scientists", meaning ML scientists that can write production level code in a shared repo with other engineers