[jszymborski]

No, we don't teach HMMs (although that would be super cool). It's strictly a neural networks class.

A lot of my research has focused on LSTMs, and so I am partial to them. I think they are super useful and have a lot of properties, but frankly speaking if you had to choose one architectures of the ones you mentioned, LSTMs/RNNs are probably the most OK to skip.

That said, if you just look at a simple RNN like the Jordan RNNs and focus on understanding that, then LSTMs just become fancy RNNs with some forgetting and remembering logic.