Keep working through the course. The lesson 2 notebook (planet dataset) and the lesson 1-breeds notebook (dog breeds) show how to train a model using a csv. IIRC you’ll see those in the next lecture video.
Each epoch here is taking a lot of time (around 3-4 minutes per epoch). Is there a way in which this time can be reduced so that the accuracy will also not be affected? Any help on this will be appreciated.
3-4 minutes is actually pretty good for an epoch to run. A resnet is a big model with a lot of parameters which are all adjusted during the training. In later classes, these will take a lot longer so you need to get used to that.
Now, to answer your question, possible ways I see to reduce this time could be to play around with your hyperparameters (batch size, mostly) or to get a faster GPU to train on. Another method could be to fiddle with half precision floating point but I feel that is too advanced at this point.