is a few semesters, not a month. There is deep intuition behind the concepts, and it takes a lot of time to pick up. The core problem is there are no short-term gains. Dabbling in linear algebra is not a skillset which improves your employability, or broadens projects you can work on.
Being able to develop TensorFlow, optimize 3d rendering for NVidia, process images for Adobe, or design a control system for a robot IS an employable skillset, and makes for much more interesting work. Picking that up is why I'd send my kid to a school like CMU.
Similarly for precalc and calc. It's not hard to know what a derivative and integral is. There is mathematical depth to being able to do something interesting with that.
If college gets you that background, you can pick up Agile and test infrastructure on-the-job.
> It's not hard to know what a derivative and integral is. There is mathematical depth to being able to do something interesting with that.
That's a very good point. In some sense learning of the material at level N, is only done when you use and consolidate the knowledge at the subsequent level N+1, and maybe even N+2.
Indeed, it would be fair to say that a student passing the final exam on topic X—even with a good grade—only truly understands 30-40% of the material. Only when the student has to apply this knowledge in later courses is the understanding complete.
Perhaps the best strategy for the independent learner is to learn topic X and immediately follow up with applications of X. I mean that's what people recommend anyway, but I always thought of it as a suggestion or a nice to have, but in the light of your comment I'm thinking maybe it's a requirement.
* competent ML engineer;
* competent at doing statistical analysis;
* competent at 3d graphics;
* competent at graph theory / SNA;
* competent at signal processing; or
* competent at control systems
is a few semesters, not a month. There is deep intuition behind the concepts, and it takes a lot of time to pick up. The core problem is there are no short-term gains. Dabbling in linear algebra is not a skillset which improves your employability, or broadens projects you can work on.
Being able to develop TensorFlow, optimize 3d rendering for NVidia, process images for Adobe, or design a control system for a robot IS an employable skillset, and makes for much more interesting work. Picking that up is why I'd send my kid to a school like CMU.
Similarly for precalc and calc. It's not hard to know what a derivative and integral is. There is mathematical depth to being able to do something interesting with that.
If college gets you that background, you can pick up Agile and test infrastructure on-the-job.