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How Good at Math Does a Programmer Need to Be?

I'm working my way to a CS degree and am currently slogging my way through an 8-week Trig course. I barely passed College Algebra and have another Algebra and two Calculus classes ahead of me.

How much of this will I need in a programming job? And, more importantly, if I suck at Math, should I just find another career path?

74 comments
  • As others have mentioned, how much and what kind of math you need depends heavily on what you do. And while I wholeheartedly encourage you to do what you enjoy, be it with or without maths, I would like to offer another perspective: A loveletter to maths.

    Math in general gets a lot easier and more fun the longer you do it and the more interest you can build. Often the people that teach math are extremely good at it, and maybe because of that they suck at explaining it. There is a lot to doing it right.

    First of all, I think you need to build excitement. Math strives to describe the world! Math is the foundation of science, math is history, and many of the concepts and techniques arose out of necessity... Or sometimes spite! There are many funny stories or interesting people behind the formulars and concepts you encounter. Learning why the hell some math was even invented and how the guy or gal got the idea is 1000x more interesting than just getting an example for the application of it. It helps you remember stuff.

    Then there are a dozen ways to explain every single concept and then some. You will find some much more intuitive than others and the sum of them will sharpen your understanding of them. Looking for different explanations for the same thing can be a great help. Did you know many things in maths where discovered multiple times? That happens a lot, because even brilliant mathematicians don't properly understand each other, or even themselves.

    Another thing you should do is to always develop your vocabulary for every domain/concept you encounter. People will throw around made-up words and symbols like no tomorrow. Often, there are simple concepts behind them, hence they are casually abstracted away. You need to understand the concept and then translate it into your own words and then draw a connection back to the made up stuff. Maths is a lot like programming. 1 + 1 is just a function, returning a result. So are integrals, formulas in vector algebra, and every single damn other thing in maths. Just follow the chain!

    And finally, there are also some amazing insights hidden in maths. Gödel's incompleteness theorems might send a chill down your spine once you grasp their implications. Computability and information theory will shape your view on the world and yourself.

    I went from getting Ds to Bs to advanced theoretical CS courses and you can do it too. You don't have to, but you can.

  • You'll encounter math eventually. It could be as simple as implementing linear interpolation for a custom type, or understanding why a type is not suited for a particular application (e.g. never use floating points to represent money). If you delve into low-level networking, you'll need a good understanding of binary/decimal/hexadecimal conversions and operations. If you go into game development or graphics, you won't survive without a deep understanding of vectors, matrices, and quaternions. Any kind of data science is just math translated to a machine-readable language.

    In my opinion, knowledge of the basic concepts is more important than being good at actually performing mathematics with pen and paper. For example, if you need to apply a transformation to a vector, nobody expects you to whip up a program that does the thing. Instead, you should immediately know:

    • what a transformation is (translation, rotation, scaling, projection, etc),
    • that each transformation has a corresponding transformation matrix,
    • that you'll have to deal with inhomogeneous and homogeneous coordinates, and
    • that you'll have to combine the transformation matrices and the original vector.

    That abstract knowledge will give you a starting point. Then you can look up the particulars -- the corresponding transformation matrices, the method to convert between inhomogeneous and homogeneous coordinates, and the process of matrix multiplication. I know because I failed calculus.

  • I agree with the other answers that it depends on the type of programming you end up doing..the nature of the program being developed, but having a background in discrete math is great to have just in case.

    From my experience, there can be unexpected problems where you will advantage from having grasp at discrete math. I worked on a project for a telecom company where they wanted a simulation to predict the impact on network coverage if a specific cell tower (BTS) was uninstalled. I ended up relying heavily on the cross-product formula and some ray-casting algorithms to model how coverage would shift in the area.

  • The field is incredibly broad. Choose a field or employer or project that's not doing that an you're fine.

74 comments