You definitely can. I only ever touched Matlab in a course on Signal Theory (wavelets, Radon transform, Fourier...) All other courses involving anything needing solving 'somehing, were programmed from the ground up in C (off the top of my head this included Numerical Methods, Numerical Analysis, Dynamical Systems). In more algebra focused classes we used gp/pari or Mathematica.

Call me silly, but implementing Numerical Methods/Analysis from the ground up in C sounds like something that would put me in a fetal position in a dark corner somewhere. Why would anyone do that to their students?

Did they also make you implement operating systems in assembler?

Well at Carnegie Mellon they did. That's why I wanna know how some punk got his Caltech paper stamped without even learning C.

He did seem sad that SpaceX wouldn't touch him. Apparently you need more than friends at the Jet Propulsion Laboratory and an ability to talk endlessly about Haskell to send shit to Mars. So that's good news at least.

I'm a mathematician, not CompSci (but I taught CS students and they had to also implement some things in C on their second semester.) So, no operating systems. Tough stuff was taken for granted when I was in the University.

There seems to be two schools of thought when it comes to teaching numerics. You either teach how to effectively implement the algorithms or you teach how to effectively select and apply the algorithms. It seems to be tied to if the computational science department comes out of the Computer or Math department.

I'm personally of the opinion that knowing how to select and apply the right algorithm is far more important to learn for undergraduates. Implementing numerical algorithms correctly and efficiently is serious high level PhD territory, and if you're not going to learn how to do it right you're much better off not doing it at all and leaving it to the experts.

If you've never implemented a bootloader and some trampolines or interrupt handlers in assembler, you didn't really learn about operating systems.

Only after we built the CPU pipeline using nand gates.

Applied math grad student here. C/C++ or Fortran was required for my computational/numerical courses. Part of this was because of the emphasis on numerical stability and complexity.

I was, however, surprised starting out to find out how many of my fellow students had never programmed in a compiled language before - different focuses during undergrad, I suppose.

Another applied math grad here. Our intro numerical course was taught in Matlab since it made it a lot easier to focus on stuff like numerical stability and complexity without getting stuck in the details of teaching people C. Everybody who ever uses a computer to do any sort of math needs to know about concepts like stability, truncation, accuracy and precision, not everybody needs to know C or Fortran. It seems unnecessary to me to tie the learning of the one to the learning of the other

It wasn't before the intermediate courses that Fortran (77 and 95),C and assembly where taught. And even there Matlab was used to illustrate most higher level concepts.

Well, I had some classes you mentioned (statistics, numerical methods, linear regressions) and never touched matlab.