I completed my Masters in Data Science in 2017. Your arguments resonate a lot with my experience. At the time, DL was in its infancy and I had no coursework on the topic. All my DL knowledge has been acquired outside of the classroom. At the time, R and python were close competitors and I did most ML coursework in R. Now, R is slowly becoming obsolete outside of academia.

The field of AI has moved forward so quickly since I completed my degree. I wouldn't call the knowledge obsolete since the foundational knowledge is still highly relevant (linear regressions, good coding, databases, for example). Rather, the education was incomplete given the state of the field at the time.

Data scientist working in the financial services industry