I went to MIT for my masters and undergrad in CS and took many of these types of classes. However, I've found that these courses were generally more theoretical and not applied enough to be immediately relevant to industry. And this makes sense to me because my Professors were researchers, not applied Self-Driving Car engineers. Some things I was lacking include:
- practical knowledge of libraries (such as OpenCV), and best practices for implementing a robust Computer Vision system.
- awareness of vehicle dynamics and the engineering behind cars.
- sensor fusion and the engineering behind collecting and processing the data a car needs.
- practical knowledge on how to implement a controller and all the required software on a car.
The general point is that these courses give the theoretical background you need but you still need the real practical skills that come with actually implementing these ideas on a real car. I think that's what makes the folks at CMU's robotics lab and Otto so valuable.
Full disclosure, I work at Udacity on the Self-Driving Car Nanodegree program and my knowledge around what skills are needed to be a self-driving car engineer come from talking to Sebastian and the heads of engineering at Otto, Mercedes Benz, and NVidia.
CS courses provide background and some training, but one must still put in the 10,000 hours of practice to really become "skilled" at something. Applied is best learnt applying!
$10M for a truly skilled self driving car engineer doesn't seem that weird in context, since training (well, more like nurturing) one up takes much more time than money.
It depends the discipline, I guess.. I turned to MIT courses from time to time when the ones (EE, Control Systems) at my University were too theoretical and I needed something more accessible (I wasn't the brightest).
Sure, we'd design RST controllers, on pages of paper, but I wanted to actually apply that knowledge.
I remember discovering OCW and the first image they showed was magnetic levitation and they had a lab where they had fun. In our lab, we'd crunch the numbers with pen and paper, then see how good our kung-fu was looking at how the system behaved on MATLAB.
Damn you, people with gear in their labs touching things and having fun!
Fun fact: our programming exams were with pen and paper where you'd write programs (x86-PIC ASM, C, Pascal) (you'd better debug it on another sheet before you turned it in).
>Doesn't every CS program everywhere have courses like that? My brother is finishing up a CS at an Ivy
LOLno, not unless you think all school are Ivies. I go to NC State, all of our CV classes (believe me, I've tried to get into some..) are limited to our ECE department, and even then they are on the graduate level. We do have some AI and data mining classes available to undergrads but none that would be sufficient for the sorts of techniques modern autonomous vehicles use. No robotics/mechatronics available for CS as well.
It's honestly kind of disheartening if you're interested in these sorts of things.
Maybe it is now but 10 years ago I don't think it was. My guess it it is very hard to find people with experience and probably easier to find new grads.
Doesn't every CS program everywhere have courses like that? My brother is finishing up a CS at an Ivy, and he's got a bunch of those types of courses.
Now if there's a bunch of courses, there's presumably a bunch of people qualified to teach them. Surely 10M is too high a number?