I like the fastai pedagogical approach. It follows the 'tutorial style', where everyone should be able to make it to the end, and you should get a reward to mot

I like the fastai pedagogical approach. It follows the 'tutorial style', where everyone should be able to make it to the end, and you should get a reward to motivate you to continue. They can't do everything, but what is most obviously missing is the "80% of data science" - data preparation/feature-engineering. The data scientists we encounter that are self-trained with courses like fastai are mostly wholly unprepared for dealing with enterprise data platforms, and, in particular, engineering data at scale.