A really core question(/assumption in many comments) is "is a computer science education only for SV job prep?" As usual, we could stand to remember that the world doesn't revolve around us. People learn to program for a lot of other reasons too.
If you want the quickest path to a SV job, you learn the most modern frameworks and drill them until you scrawl the boiler plate in your sleep. Project-based learning is extremely appropriate for this. You absolutely don't need four years of education to crank out a comfortable 6 figure salary off this knowledge. (In fact, it might be a liability if your pet framework ages out). You only have to be able to fill a need (even one will do) which a lot of companies have.
If you're looking for anything else, a diet of only back-to-back projects might not be the best way. If you're jumping head first from javascript into kernel modules you might consider a book. If you're looking to automate some bio or physics lab equipment, you can't expect getting good at a few popular frameworks to carry you. If you're learning math there are advantages to having people grade your work and offer office hours.
And if we're being really honest, this non-project-based stuff is pretty useful as SV job prep too. Not knowing things like linear algebra, statistics, and discrete math can be career limiting. I mean, how many of us are really ready to jump the gap to doing serious ML work?
If you want the quickest path to a SV job, you learn the most modern frameworks and drill them until you scrawl the boiler plate in your sleep. Project-based learning is extremely appropriate for this. You absolutely don't need four years of education to crank out a comfortable 6 figure salary off this knowledge. (In fact, it might be a liability if your pet framework ages out). You only have to be able to fill a need (even one will do) which a lot of companies have.
If you're looking for anything else, a diet of only back-to-back projects might not be the best way. If you're jumping head first from javascript into kernel modules you might consider a book. If you're looking to automate some bio or physics lab equipment, you can't expect getting good at a few popular frameworks to carry you. If you're learning math there are advantages to having people grade your work and offer office hours.
And if we're being really honest, this non-project-based stuff is pretty useful as SV job prep too. Not knowing things like linear algebra, statistics, and discrete math can be career limiting. I mean, how many of us are really ready to jump the gap to doing serious ML work?