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求问‌‌‍‍‌‍‍‌‍‌‍‍‌‌‌‌‍‌‍‍‍‍‍‌‌‍‌‌‌‍‍‍一下discrete structure / maths for DS选课

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两门课里面我得确定一门下来

一门叫discrete structure,课程介绍这么说的:

An introduction to Discrete Mathematics; propositional and predicate logic, first and second principle of mathematical induction, sets, counting, inclusion/exclusion principle, binomial theorem, relations and functions, introduction to matrix algebra, introductory graph theory.

另一门 Mathematics for Data Science,课程介绍:

This course is an introduction to the mathematical concepts that are essential to data science. Course content covers three fundamental areas of mathematics: probability, statistics, and linear algebra. Topics include probability spaces, conditional probability, independence, discrete and continuous random variables, multivariate random variables, expectation, descriptive statistics, Bayesian statistics, hypothesis testing and inference, set theory, binomial theory, vector spaces, inner product and norms, matrix operations, Eigenvalues, graph connectivity, and combinatorial space.

我数学这块儿蛮薄弱的,无论上哪门都能学到新东西。目前研究生专业是CS。

discrete structure的话我听说学了后能更了解计算机的计算原理。

math for DS的话是Machine learning的prerequisite之一,我未来有可能上一门ML,但不是很确定。

而且说实话我也不大懂这两门课还有别的什么区别和impact。。希望有相关了解的小伙伴可以跟我说说orz在此谢过
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