We touched a bit of that. As an aside, when I was a student, we also had an applications module called "Numerical Analysis". We went through a bunch of algorith

We touched a bit of that. As an aside, when I was a student, we also had an applications module called "Numerical Analysis". We went through a bunch of algorithms (Cholesky, Seidel, Newton-Raphson, Gauss, etc.) and ran them by hand. We basically were "human computers". The exams were also solving problems using these algorithms, and given the iterative nature of many of them, if you make a tiny mistake it'll ripple and ruin everything for you. As an aside, my background is in optimal control/control theory and instrumentation, and operational calculus, state space representations, and matrices were a huge part of the "Jiu-Jitsu" we did. Tinkering with RST control, robust systems, finding optimal systems and sequences (Hamilton-Jacobi-Bellman-Pontryagin) with matrices flying around on our exam papers solving these systems. It was a nice abstraction. Very, very, powerful tools that command immense respect for Laplace, Lagrange, and people like them who invented things to solve problems we're facing now.