Speaking as a CS educator, I agree, with a caveat: In my free time, I took the big Coursera course, and it is (was?) also tied into a proprietary toolset, Grap

Speaking as a CS educator, I agree, with a caveat: In my free time, I took the big Coursera course, and it is (was?) also tied into a proprietary toolset, GraphLab. They have "you can also do this in pandas" instructions on lab assignments, but the instruction and tools are aligned to GraphLab. I imagine the vast majority of students will not even consider using pandas. Graphlab Create has since been open-sourced (as Turi Create) by its new owner, Apple. I didn't have a problem with the setup back then. Stressing over toolsets is like stressing over your first programming language. It's counterproductive. You will do a lot better by finding a source of instruction you trust and a toolset you can work with, and then actually making something. Quality instruction vastly outweighs the tradeoffs with learning a new language/api/etc. From having skimmed the Microsoft course's offering, it looks like it would prepare a good student to understand and apply the algorithms to make models, but not to implement the algorithms themselves (which the Coursera course does do). Which is fine! I could tell you how to implement elliptic curve cryptography and prove most of the mathematical underpinnings, but I have no intention of ever writing an implementation myself.