How does Numpy sample random numbers from a non-uniform distribution?

I have been learning about random sampling methods and am aware that Numpy uses Mersenne-Twister to generate uniform random numbers, how does it then pass these to generate non-uniform distributions?

For example:

np.random.normal(mu,sigma,n)

What algorithm is used here to sample normally distributed numbers? Thanks.