In short you need to understand: vector, linear combination, cross product, partial derivative, chain rule and finding global minimum. If you have basics of linear algebra it’s easy to grok this video.
This is the equation of a neuron is you squint.
So if you chain a bunch of neurons, you are basically drawing a bunch of lines to test whether points belong or not.
With enough lines you can approximate any shape, like a circle.
What neural network do is given enough examples, it finds the lines that are needed to separate the points to give the appropriate label.
It builds a simple CNN and ends with a simple example of how multiple ReLU activation functions can approximate arbitrary curves.