Most programmers probably know "map" as being an operation takes a function and a list and returns a list of the results of the function applied to each element of the input list. However, the "map" operation can be generalized to generic types other than lists, where it has different behavior but shares certain properties. In functional programming, the idea of a functor gives a name to this pattern.
The idea is that if you have some generic type `T a` covariant in `a`, there is a function `map : (a -> b) -> T a -> T b` that can "lift" every function `f : a -> b` into a function `map f : T a -> T b`. The lifting operation respects function composition and identity.
However, what if the function has multiple arguments, e.g. `f : a -> (b -> c)`? Then, `map f : T a -> T (b -> c)` An applicative functor lets you convert that `T (b -> c)` into a `T b -> T c`. So, with applicative functors, you can individually map each parameter of a multi-parameter function.
A monad is a functor that can be "flattened." It has an operation `join : T (T a) -> T a`, as well as an operation `return : a -> T a`. A monad can be seen as generalizing the idea of flattening a list, or generalizing async/await.