Machine Learning and Deep Learning with PyTorch

Course overview

This intensive training includes Machine Learning and Deep Learning with PyTorch: tensors and automatic differentiation, training loops for classical and deep models, as well as the organization of your own PyTorch projects. Your competencies Process data as tensors in PyTorch and compute on graphics processors Define linear models and multilayer networks in PyTorch Write your own training loops with loss functions and optimizers Build datasets and data loaders for large amounts of data Save, load, and continue training trained models Basics of PyTorch Tensors and their operations Automatic differentiation as the basis of learning Modules and parameters as building blocks of a model From Classical Model to Deep Network Regression and classification as an introduction Multilayer models for more complex patterns Evaluation of model quality on validation data Training Process Training and validation loops Hyperparameters such as learning rate and batch size Logging of loss and accuracy Application in Professional Life Prototype research-related model ideas in PyTorch Adapt existing PyTorch models to your own data Compare and document training results within the team Professional Fields Development and research teams with a focus on PyTorch AI labs in companies and universities The comparison of two frameworks for deep networks is addressed in the offering "Deep Learning with TensorFlow and PyTorch", while the developer role with code tests, versioning, and code reviews is covered in the offering "AI Developer - Machine Learning, Deep Learning, and Python".

Upcoming dates

• 2026-10-29T23:00:00.000Z · 2027-03-16T23:00:00.000Z · Aachen · Combined Learning
• 2026-10-29T23:00:00.000Z · 2027-03-16T23:00:00.000Z · Zwickau · Combined Learning
• 2026-10-29T23:00:00.000Z · 2027-03-16T23:00:00.000Z · Zittau · Combined Learning
• 2026-10-29T23:00:00.000Z · 2027-03-16T23:00:00.000Z · Würzburg · Combined Learning
• 2026-10-29T23:00:00.000Z · 2027-03-16T23:00:00.000Z · Wuppertal · Combined Learning