Accelerate Model Training with PyTorch 2.X
By External Provider
About this course
This course teaches you techniques to dramatically speed up model training using the latest features in PyTorch 2.X. Mastering these optimization strategies is essential for professionals building scalable, high-performance AI systems. You’ll learn how to refine your training workflow, improve computation efficiency, and achieve faster, more reliable model iterations. Each module translates performance concepts into practical techniques you can immediately apply. The course blends deep technical foundations with real-world optimization workflows, ensuring you understand both why each method works and how to execute it effectively. You’ll practice using compiled models, mixed precision, distributed strategies, and more. This course is ideal for developers, data scientists, and ML engineers with basic PyTorch experience who want to train models faster and scale training across hardware configurations.
What you will learn
- Optimize model training using PyTorch and performance tuning techniques.
- Leverage specialized libraries to enhance CPU-based training.
- Build efficient data pipelines to improve GPU utilization.