The problem is that when you put people without formal training in charge of building and training models, you get also results that match - models with horribl

The problem is that when you put people without formal training in charge of building and training models, you get also results that match - models with horrible biases, models that don't reflect the reality at all, models that are worse than taking random guesses. Running through a bunch of tutorials and then taking a deep learning toolkit (e.g. Tensorflow or Keras) and starting to feed data into it won't teach you squat about the importance of having a representative sample, about removing biases from the data, about correctly handling outliers, about doing some basic statistical analysis on the data to see whether they are even relevant to the problem at hand and so on and so forth. Or even how to build a questionnaire/experiment so that you don't get only a load of expensive garbage instead of data out of it. This is what a doctorate and the associated research training generally give you. Of course, it is not anything that couldn't be learned without doing a formal PhD, publishing research papers and defending a thesis but it is typically the background you won't get from these MOOCs or various online (and offline) "data science" trainings.