Nowadays, wearable sensors have become ubiquitous in our daily lives, from fitness trackers to smartwatches and health monitoring devices. However, analyzing the data and getting meaningful insights can be challenging. In this workshop, we will investigate the use of supervised machine learning methods, such as Support Vector Machine, Decision Trees, and Artificial Neural Networks, in understanding data from wearable sensors. The workshop will include a hands-on project that will require data collection, data processing, feature extraction and selection and training and evaluation machine learning models.