conda in windows is not very stable with Pytorch and specially when we needed to use GPUs, which is going to be the case for the next lectures. It has numerous compatibility issues with the cuda libraries necessary to make it work.
May I suggest you guys not to run things locally, otherwise you can spend a lot of time trying to configure and make things work instead of focusing on the code and the concepts from the lecture. I just forked the notebooks and I am running the notebooks right here on Jovian, which uses Binder as a kernel where things are already configured.
Just a suggestion from having spend numerous hours trying to run things on Windows.