Machine learning techniques such as deep learning are becoming increasingly popular tools for surrogate modeling of complex problems in computational science and engineering. Such methods are broadly encompassed in the field of Scientific Machine Learning and are in their infancy. In this workshop we aim to provide the participants with a brief introduction to Scientific Machine Learning, followed by a hands-on session for implementing one of the techniques in generating a surrogate model for a dynamical system. In addition, Dr. Peetak Mitra an award-winning technologist and researcher primarily focused in the area of Scientific Machine Learning will be presenting a talk on challenges and opportunities in the field.