Most CS undergraduate mathematics stops just short of proof-based courses, which is a shame.
A proof-based linear algebra course would be the next course that is typical in the progression. If you've already done that, then an introductory real analysis course.
If you want something a bit more practical then maybe a probabilistic modeling course? ( think Gaussian mixture models, bayesian networks, plate models).
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Most CS undergraduate mathematics stops just short of proof-based courses, which is a shame.
A proof-based linear algebra course would be the next course that is typical in the progression. If you've already done that, then an introductory real analysis course.
If you want something a bit more practical then maybe a probabilistic modeling course? ( think Gaussian mixture models, bayesian networks, plate models).
Solid suggestions, thanks.