I am currently working on the Machine Learning and Math for Machine Learning specializations.
I am interested to take both Deep Learning as well as NLP specializations. (And possibly the GAN specialization.) Is there an advantage to taking one of them before the other? (IE does one build on the other in any way?)
My recommendation would be to do the DLS specialization next after MLS and M4ML. DLS gives you an in depth introduction to all the major types of Neural Networks: fully connected nets in C1 and C2, convolutional nets (C4) and sequence models (RNNs) in C5. C3 is also valuable, but it deals more with how to structure ML projects and deal with data.
Once you’ve completed DLS, then you can do either NLP or GANs next. Those are independent of each other, but both will benefit from having the knowledge of Neural Networks from DLS.