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I study computer science at the Charles University. The undergraduate study (baccalaureate) in "general computer science" programme provides several focus areas, which are followed by corresponding programmes in the graduate study (master). I chose to go for mathematical linguistics in the undergraduate and artificial intelligence (Probably with machine learning focus, but I'm not sure yet.) in the graduate study.

My problem is: There are some mandatory maths courses and some optional. Some of the optional ones are recommended, but not for specific focus areas. So I wanted to ask for some advice on which areas of mathematics are recommended for this area.

Most courses are split into multiple semesters and completing only the first few is usually mandatory, continuation of the other ones is optional. So far (first year of undergraduate), I have completed these mandatory courses:

  • Mathematical analysis I, II
  • Discrete mathematics (Continues as Combinatorics and Graphs.)
  • Combinatorics and Graphs I
  • Linear algebra I, II (No more courses available, only applications in computer graphics etc.)

Mandatory courses for next years:

  • Probability and Statistics
  • Propositional & Predicate logic
  • Algebra I

List of some available optional courses:

  • Mathematical analysis III
  • Combinatorics and Graphs II
  • Set theory
  • Numerical mathematics
  • Algebra II

closed as off-topic by Bryan Krause, Richard Erickson, scaaahu, Buzz, gman Sep 12 '18 at 16:57

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  • You really need to find a way to add probability and statistics to that list of course you plan on taking. That or self educate. That said, picking up set theory will let you at least let you learn the language of probability and machine learning. Learning statitistics and a programming language of your choice is a strong start to understanding where all that math you are learning is applied. – JWH2006 Sep 11 '18 at 11:38
  • Yeah, sorry I forgot to mention the statistics, they are mandatory. – McSim Sep 11 '18 at 12:19
  • I did not intend to ask about CS related courses, as I had those figured out mostly. But based on what you are saying, is a Probabilistic Algorithms course a good choice? – McSim Sep 11 '18 at 12:23
  • And are statistics that important, or is it more about the probability? (I love mathematics, but unfortunately, statistics is the only area I still have problems with, so I just want to know if it's worth changing my view on statistics as something important to my future interests, rather than something I just need to know, but don't really want to.) – McSim Sep 11 '18 at 12:32
  • statistics is a core portion of machine learning. I think a better question on deciding what you want to take is what you plan to do with machine learning? Do you plan on participating in the exploding field of machine learning applications? If so, that is, at its core, stats/programming. – JWH2006 Sep 11 '18 at 12:56
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  • Mathematical analysis III

Probably overkill, but it depends on the actual content. You will need some multivariate analysis (partial derivatives, Jacobians, Hessians), but I suspect it's already in the first two courses.

  • Combinatorics and Graphs II

Maybe not specifically for AI, but in general it should be a useful course for a computer scientist. Again, it may depend on the actual program; if it is set up as a very abstract course then it may be overkill.

  • Set theory

Not so useful. Probably more abstract stuff that you'll ever need as a computer scientist.

  • Numerical mathematics

Very useful. Matrix computations, stability and the floating point model, basic root-finding and optimization algorithms... That's all stuff that you will probably need. I'm surprised that it is not mandatory for a computer scientist (but I work in that area, so maybe I'm biased).

  • Algebra II

Not so useful. Probably more abstract stuff that you'll ever need as a computer scientist.

Other courses: look out for a course on optimization (it might also fall in the "numerical mathematics" category). Neural networks are based on optimization/fitting algorithms.

  • There are several courses on optimization. I only needed someone else's view on the more general maths areas, as I was getting biased by my personal preferences in the areas, which is not very useful, when using mathematics as a tool rather than just exploring what I like. – McSim Sep 12 '18 at 9:34
  • I thought about your list as well and have taken those courses. My internal question was "Which of these will help the OP build models". I thought that Abstract Algebra probably does this best of the ones you mention, but it is a jump from theory to practice. – Buffy Sep 12 '18 at 10:26

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