Because then students start using 3 or 4 different languages, can't figure something out, and come bitching to the TA to tell them what they did wrong, and now

Because then students start using 3 or 4 different languages, can't figure something out, and come bitching to the TA to tell them what they did wrong, and now the TA needs to know 5 different ways to implement the same thing. Ironically, you complain about wanting to learn statistical concepts, and not a language, but by focusing on a single language, they can minimize the amount of time spent on agonizing over lines of code trying to get to the same answer, and instead focus on the actual statistical problem. Its also important to note that there are lots of potential pitfalls for people who don't know about them. For example, scikit-learn is the most popular python package out there for most data analysis work. But I would bet my ass that at least 50+% of its users don't realize that the logistic regression implementation implements L2 regularization by default, and in fact there is no (non-hackish) way of implementing non-penalized logistic regression. So you will be getting completely different answers than someone who would be using R, SAS, SPSS, etc. And the only way for someone to know this is for someone to understand the implementation of the function in all possible languages.