I am sure Numericals are a core step in the computational finance pipeline.
Problem (e.g. Black Scholes, HW, XVA,...} -> {PDE, ODE, SDE} -> Numerics -> Software Design -> {C++, Python, C#}.
One issue worth noting is that there are two main strands associated with matrices
1. Pure maths linear analysis/algebra ... paper models. Kind of academic-only focus.
2. Numerical linear algebra .. algorithms and getting stuff into the computer. And knowing what, why and how. numpy/scipy...
This ODE/PDE course is on the UCB recommendation list
https://www.datasim.nl/onlinecourses/97/distance-learning-ordinary-and-partial-differential-equations
Random thoughts
1. Is prompt engineering clutching at straws? A cop-out for robust requirements analysis?
2. NLP is fraught with pot-holes. It won't work in general. Wittgenstein would have a lot to say.
3.Will ChatGPT ever be a requirements analyst? Probably not, because it is a name dropper...
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