Yep. I haven't really had much need for the techniques I learned in my graduate linear algebra course and found the in-class examples to really lack specific us

Yep. I haven't really had much need for the techniques I learned in my graduate linear algebra course and found the in-class examples to really lack specific usefulness in the real world. I just looked up my old class: linear algebra basics; Gaussian/LU/Choleski decomp; determinants; normed spaces; condition number; iterative methods; Euclidean spaces; QR decomp; Hermitian geometry; Eigenscheissen; spectral theorems; finite elements method; SVD and pseudoinverses; quadratic optimization. Can confirm, totally useless in the non-research world. The most applicable task was computing spline curves. Even the Google Images result for "hermitian geometry" is mostly images of research papers. How is that real-world relevant? The useful robotics stuff for me is either already written as a library I can call or pseudocode I can find in AIMA. Then again, all of that stuff had to come from somewhere and receive the optimization treatment. I'd liken that entire Michigan mathematics course to the first week of my FEA course. "Here's how to calculate, by hand, a basic example of stress and strain in a very simple geometry using matrix operations. Cool, now that you see how much of a real hassle that is, never do it again because we have Ansys and Solidworks." ----- On the other hand, a paper such as http://ras.papercept.net/images/temp/IROS/files/3131.pdf http://ras.papercept.net/images/temp/IROS/files/3131.pdf would seem totally inaccessible without a class like this Robotics 501. Maybe that constains good examples of the math being instructed. (Disclaimer: I didn't do more than glance at the course material and watch a few moments from the lectures.)