Google colaboratory now has GPU support meaning you can run your jupyter notebooks on google drive with GPU support.
Here is a tutorial how to get started.
Last year the 2017 course of fast.ai was amazing, which taught state of the art deep learning to coders. There are so many goodies in the blog post about the Fast.ai 2018 launch which is available now. This year they held the course using Pytorch instead of Keras and wrote their own library for speeding up development and were the first to add several implementations from papers to the library such as Learning Rate Finder (Smith 2015) and Stochastic Gradient Descent with Restarts (SGDR). With one line of code, you can also get the images that the classifier gets wrong.
17 of the 20 top participants in a kaggle competitors were students in the preview course.
I recommend reading the blog post and taking the course.