What is the branch of data science that deals with generating data? Looking for tutorials
This is known as generative models, they basically infer the probability of the data based on the training examples. Algorithms usually are discriminative, i.e they perform prediction by estimating:

$$
p(Y|X) 
$$

so given your data they are able to predict a label. 

Generative models are interested in $p(X)$ i.e. how is the data generated. Once the model learns this, it can produce "fake" images that look like your inputs.

You can look at:


Generative Adversarial Nets (which have had a lot of attention lately)
Variational Autoencoders (were in vogue before GANS were introduced)