Deep learning (DL) tools are increasingly integral to medical image analysis, particularly for shape representation. With rapid advancements in methodologies and network architectures, these tools leverage datasets to deliver cutting-edge results across a range of tasks. In this workshop, we will introduce participants to the fundamentals of shape representation using DL-based techniques through a mix of lectures and hands-on exercise. Additionally, we will cover Git version control to ensure that the developed DL-based models are traceable, reproducible, and aligned with the principles of open science.