This advanced PyTorch course focuses on production-ready AI workflows, large-scale distributed training, and mobile deployment. Designed for experienced engineers, researchers, and AI practitioners, it showcases practical implementations from PyTorch Conference 2022 breakout sessions.

You will learn how to deploy PyTorch models on mobile devices, including Android using C++ integration. The course explores operationalizing distributed training on Google Cloud, scaling foundation models with Fully Sharded Data Parallel (FSDP) on IBM Cloud, and optimizing large-scale AI workloads with Azure PyTorch containers.

In addition, you will gain insights into Lightning for taking models from research to production, Intel Extensions for PyTorch to improve performance, and real-world deployment strategies used at Amazon scale. Each session emphasizes best practices for scalability, performance, and maintainability in professional AI systems.

By the end of this course, learners will be equipped to implement enterprise-level PyTorch solutions, manage distributed training for foundation models, deploy AI applications on mobile and cloud platforms, and operationalize models from research to production efficiently.