Quick answer: Tensors, autograd, training loops — build neural nets from scratch.
PyTorch Fundamentals is the foundation for building neural networks from scratch. It teaches you how to work with tensors (multidimensional arrays), understand automatic differentiation (autograd), and write training loops that teach models to learn from data. With PyTorch, you'll move beyond high-level APIs to understand how deep learning actually works — how gradients flow backward through networks, how optimizers update weights, and how to debug models when they don't converge.
You'll build image classifiers, train language models, and implement custom layers. This isn't theoretical — you'll write real code that trains real models on real datasets, giving you the control and understanding that separates practitioners from engineers.