Linux Foundation Education has launched the new PyTorch Certified Associate (PTCA) Certification Pathway, bringing focused learning modules and the PyTorch Certified Associate (PTCA) certification exam together in one structured experience.

The Certification Pathway is designed to help you build the foundational PyTorch skills validated by PTCA through learning that more closely aligns with the certification’s domains and competencies.

For $299, the pathway includes four self-paced learning modules plus the PTCA certification exam:

Together, the modules cover core skills across the same key areas measured by the PTCA certification, from working with tensors and devices to preparing data, building neural networks, and improving model performance.

Throughout the pathway, you’ll build skills to:

Work with tensors and devices across the model lifecycle, from training through prediction

Prepare and manage data using Datasets, DataLoaders, and transforms

Build neural networks using PyTorch layers, activations, loss functions, and optimizers

Measure and optimize performance using tools and techniques including torch.compile, Automatic Mixed Precision, the PyTorch Profiler, and distributed training concepts

The full pathway includes 15–17 hours of self-paced learning and hands-on labs designed to help you build a strong foundation. Certification readiness takes more than completing coursework, so additional hands-on practice and real-world experience with PyTorch are recommended as you prepare for the PTCA exam.

PTCA is designed for early-stage practitioners with Python and machine learning experience who are beginning to work with PyTorch. The certification validates your understanding of the core concepts and workflows used by engineers and researchers to design, train, optimize, and work with machine learning models.

With the new PTCA Certification Pathway, you can build those skills through focused learning and then validate what you know with the included certification exam, all in one product.