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I think pre-university math should focus on algebra and univariate calculus. Also sophisticated freshman programs focus on linear algebra and multivariate calculus and analysis. See e.g. Math 55a/b at Harvard.

You do need calculus for non-trivial statistics and even for some topics of discrete mathematics where continuous approximations are useful. For example Stirling's approximation [1] which if I recall well is on the first page of McKay's Information Theory, Inference, and Learning Algorithms.

I think that if we talk about more modern approaches for mathematics, logic, type theory and interactive theorem proving could be great. I've been toying with this idea for teaching a course, but I haven't found suitable materials.

[1] https://en.wikipedia.org/wiki/Stirling%27s_approximation



There's a discrete math course that uses types/proving in ML https://cs.wheaton.edu/~tvandrun/dmfp/




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