Matlab is a categorical loss due to its proprietary character, R debatable, Julia, maybe yes. Octave, while at least not proprietary, still surely not, if the task is anything but some matrix multiplication or matrices using program.

julia has an unacceptable overhead when running small programs. it works well for longer running workloads or extended interactive sessions, but for learning you want to be able to write and execute small scripts without feeling the perceptible lag every time. google up "time to first plot" for more on this.

It' s quite acceptable with 1.10.

>At some point they'll have to learn about the file system, shell, network. Otherwise there is little point in learning Python.

Sure, but I would argue that overwhelming someone with all those topics at the beginning is counterproductive.

Well said. I am grateful that my employer licenses Matlab, Simulink, and a lot of toolboxes and blocksets. The IDE and especially the documentation help me get stuff done. We've had waves of Python as a Matlab killer first with Enthought and then Anaconda as the repository. I gave Python an honest try but was spending all my time searching for help on package after package with poor to no documentation and trying to debug code with substandard tools.

I think it's possible that learning programming could be the gateway to learning those other things, otherwise they're of little use. Many people don't even need to know the filesystem. They store their stuff in Google Docs or somewhere like that. If they use mostly canned software (such as EPIC or SAP) for their jobs, then their data are stored in some magical special unknown place.

I learned programming (in BASIC, in 1981) before I heard about the filesystem or shell. Making more complex programs do interesting work was my reason for learning more about the innards of computer systems.