Many universities are moving to Python for their engineering education. I believe there are two reasons: 1. the popularity of Python for ML in particular, many

Many universities are moving to Python for their engineering education. I believe there are two reasons: 1. the popularity of Python for ML in particular, many students want to learn general skills that are relevant beyond a narrow "engineering domain". 2. Somewhat surprisingly a push from industry, where licences make up a significant chunk of the budget. I know several R&D engineers who switched over to Python, because they got annoyed that licences where not available when they wanted to work. This has changed the overall perception of Python in these companies (who previously regarded Python as a "hobby" project). Regarding the toolboxes, in my experience quite a few are of extremely poor quality despite significant costs. To give you one example, the instrumentation toolbox is so buggy, that we essentially have to open and close instruments every time we want to send commands (otherwise we would get random freezes which often could only be fixed with a complete computer restart). This adds significant time, when we moved from matlab to python for our instrument control measurement time for a single measurement (of which we would often need >100 in one experiment) went from >5min to less than 30s.