Scalable AI Models with PyTorch Lightning

Training programme overview

Deepening best practices for training and optimizing large-scale models with PyTorch Lightning. Covers code structuring, distributed training strategies, robust validation and hyperparameter tuning for reproducible model development.

Structuring code and Lightning modules for clarity and reusability.

Distributed training strategies and handling large-scale datasets.

Validation protocols, metrics and logging to monitor performance.

Optimization approaches, schedulers, regularization and hyperparameter search.

Integration of experiment-tracking tools for audit and training debugging.

Training · Intermediate