I'm a Statistics and CS double major and I must take two more math electives to complete my degree.

I have four choices for the Math courses I could take and I was wondering which of the two would be most beneficial for Machine Learning or Artificial Intelligence.

My choices are:

(1) Combinatorics 1 (2nd year course, also I've already taken Discrete Mathematics)

(2) Mathematical Modelling (2nd year course)

(3) Numerical Analysis 1 (2nd year course)

(4)Linear Algebra and Matrix Analysis (4th year course - this would be my 3rd Linear Algebra class)

Thanks for the advice!

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    $\begingroup$ @henry-l What is a soft-question? Perhaps the tag references would be more appropriate?! $\endgroup$ – Stefan Feb 25 '17 at 0:08
  • $\begingroup$ @Henry.L Indeed, why create a new tag without a Wiki etc.? $\endgroup$ – Richard Hardy Feb 25 '17 at 9:28
  • $\begingroup$ Hi, I mistakenly thought this tag already exists since it is a tag on mathoverflow, thanks for suggestions! $\endgroup$ – Henry.L Feb 25 '17 at 14:19

Ideally you should take all four (or at least three of them). Otherwise, in order,

  1. Numerical Analysis -- assuming that this doesn't mean real or complex analysis, but instead numerical computation
  2. Mathematical Modeling -- always a good skill to have; will possibly lean more towards PDEs than statistical modeling
  3. Linear Algebra and Matrix Analysis -- if you hadn't already taken two years this would be higher
  4. Combinatorics -- While knowing combinatorics is important, the full class might go in less important directions (I could be wrong here)
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  • $\begingroup$ Are these in order from least to most useful? $\endgroup$ – Aaron Feb 25 '17 at 1:05
  • $\begingroup$ The order is most to least useful $\endgroup$ – jwimberley Feb 25 '17 at 1:22

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