Discrete math first comes to mind first: lists, trees, graphs, etc. Used in basic algorithms 101, but you need some more serious probability theory for probabilistic algorithms.![]()
Linear algebra is useful for computer graphics, but also for general "system thinking" concepts like inputs spaces, output spaces, transformations, and properties of transformations.
Basic differential calculus, meeeh, but multivariable calculus—specifically optimization—is really important in many programming contexts (e.g. machine learning).
Of course, the most important and most basic of all is the notion of a function f(x), its definition, inputs, outputs, properties, etc.