Scalable AI Models with PyTorch Lightning

You’ll learn to build modular neural networks with PyTorch Lightning, engineer robust data pipelines for efficient training, apply advanced optimization strategies such as quantization, and save your models in a production-ready format.

A solid understanding of Python and intermediate deep learning concepts (e.g., neural network fundamentals, setting up a PyTorch training loop) is required.

Absolutely! Hands-on exercises will guide you through building and optimizing AI models step by step, from dataset preparation to model training. You'll be coding in Python and using the PyTorch Lightning library and other Torch modules.

While “Deep Learning with PyTorch” focuses on core model architectures and training fundamentals, this course introduces scaling techniques and modular components to train more efficiently using PyTorch Lightning.