That Gap in Data Science Teaching

I have a theory that others might not like.
And by others I mean data scientists with PhDs.

What I see is a disconnect between data science MOOCs and what hiring managers look for in hires. MOOCs spend months in theory with one project at the end, while hiring managers only care about results, i.e. projects. 

I talk to people trying to get into the data science field and see them fall into this trap over and over again. They spend months studying machine learning and stats theory only to retain a little since they haven't used it. I know this personally because this is what I did.

This is understandable because due to data science being such a new field, most data scientists today have PhD's. They were taught mostly with theory, so the online coursework is reflected accordingly. 
I predict however, that this will soon pass, and looking forward, the majority of data scientists will not have higher degrees. These data scientists would of learned everything by doing and this will be reflected in new curriculums. 

We are not there yet.

But this gap offers a great opportunity to anyone that can notice this trend and buck it. 
To anyone that builds one project after another, learning theory along the way. 
To anyone that creates a website and shows off all their projects - all annotated. 

That can be you.