This workshop provides an introduction to Quantum Machine Learning using PennyLane and PyTorch, with hands-on exercises and take-home challenges. The workshop includes four practical sessions that cover the QML concepts, models, and techniques. The sessions explore the development of quantum estimators and classifiers, their training with various optimisers, loss and cost functions, as well as model testing and scoring using variety of metrics. It finally, explains how to create hybrid quantum-classical QML models.