This was the course I took after having completed the 'AI Programming with Python' Nanodegree. It helped me dive deeper into PyTorch and learn some additional cool stuff one can do with it.
Check out the course detailes here.
Udacity have built this course as an introduction to deep learning. Deep learning is a field of machine learning utilizing massive neural networks, massive datasets, and accelerated computing on GPUs. Many of the advancements we've seen in AI recently are due to the power of deep learning. This revolution is impacting a wide range of industries already with applications such as personal voice assistants, medical imaging, automated vehicles, video game AI, and more.
In this course, we'll be covering the concepts behind deep learning and how to build deep learning models using PyTorch. We've included a lot of hands-on exercises so by the end of the course, you'll be defining and training your own state-of-the-art deep learning models.
PyTorch is an open-source Python framework from the Facebook AI Research team used for developing deep neural networks. PyTorch can be thought of as an extension of NumPy that has some convenience classes for defining neural networks and accelerated computations using GPUs. PyTorch is designed with a Python-first philosophy, it follows Python conventions and idioms, and works perfectly alongside popular Python packages.