[fantispug]

It covers a lot of the fundamentals in some detail (attention and transformers, decoding, transfer learning) that are underneath current cutting edge NLP; this is still a very good foundation likely to be good for several more years.

What might be missing is in-context learning, prompt engineering, novel forms of attention, RLHF, and LoRA (though it covers adaptors), but this is still changing rapidly and the details may be irrelevant in another year. If you have a look at a recent course like Stanford CS224N 2023 there's a lot of overlap.