I'd say ditch everything but math and start implementing your models in Pytorch and reading papers and blogs. Python can be learned by doing by someone with cs background. The field moves too fast, relevant stuff starts in ~2014 and is all on arxiv and github (both reference implementations and state-of-the-art code), there are no up to date textbooks. This

https://uvadlc-notebooks.readthedocs.io/en/latest/index.html

course is about the only one I encountered that teaches recent model architectures (it is helpful to read their implementations too). A lot of their models are mostly relevant for vision, but transformers and autoencoders are really useful in NLP. For stuff more specific to NLP ,HugginFace tutorials is a good starting point for digging

https://huggingface.co/course/chapter1/