“Just add a bunch of green up arrows and red down arrows, your manager will love it” was advice from a co-worker of mine. Sadly, she was right.
It didn't actually give correct results, I'm not sure it could have worked (I needed to do two updates on the same cycle and never did figure out how), and I documented that it was buggy.
But it looked cool and I got good marks. So my experience pretty much agrees with yours.
After you have given a university hundreds of thousands of dollars and a decade-plus of your life, you will then be ready to teach the next crop of students.
1. You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs? No. Not only can 100% of successful top-tier PhD applicants find jobs, 100% of them are strong candidates for the top echelon on entry-level jobs.
If you disagree, go look up the people in Berkeley's CS PhD program. Point out a single person you think didn't turn down mid-100s job offers to attend Berkeley.
Getting into one of these top-5-to-10 PhD programs is no small thing...
2. MOOCs aren't PhD programs and in nearly all cases aren't designed to feed into PhD programs.
3. Finally, at least in CS, at least for the moment, educators are in extremely high demand. And again, at least for CS, that demand isn't being manufactured by the academy.
It is well known that PhD programmes churn out far more PhDs than can reasonably be employed in their field.
I mean, including friends and former colleagues I probably know maybe 300 people with PhDs. Of those I can count on my fingers those actually doing research in academia, probably one hand those on tenure track. But do you really think any of them slogged through the programme in Physics or Biology just to get a software job writing CRUD apps, or prettying up BI reports?
a) didn't bother applying but would've been shoe-ins, or else
b) knew very early (freshman year) they were research-bound and optimized for a non-industry objective function (but could've skated into an industry job of their choice given a shift in undergraduate career focus). E.g., couldn't pass a coding interview and no industry internships but have one or more top-tier publication in a hot subfield.
But (b) is kind of stupid to think about. It's like saying a successful lawyer would not make captain in the military. This may or may not be the case, but either way, who cares?
So (b) is slightly less trivial than saying a successful lawyer would not make captain in the military because most lawyers are one conversation, a few signatures, and one oath away from being a captain.
So don't delay lawyers, join today!
> ...So (b) is slightly less trivial
I'd argue not. In both cases, a fully capable and prepared person has to jump through a couple of relatively trivial hoops. And when those hoops aren't possible to jump through it's a weird case. We can split that hair, but it's silly.
They are mostly economics or (I’m not sure what it’s called in English, but it’s a degree in societal administration), but they really ought to be data scientists because everything they do is based on huge sql data sets.
We pay private contractors a lot of money to turn our data into cubes and manageable models because none of our analytics know how.
In 10 years I suspect anyone with that job title will need data science on their resume. Not just to manage the data, but also to start doing machine learning on it.
By comparison we have one network guy to run the network for 10.000 employees and 5000 students, with a backup guy who knows everything the first guy does but works with something else, you know, in case the first guy quits.
Do you propose that they should take a MOOC like this one, or that they should be replaced by MOOC graduates?