Machine learning (ML) is an application of computational and statistical techniques to allow computers to learn and predict without explicit programming. In recent years, with the increasing availability of large scale and low-cost computing power, ML capacity has expanded vastly and has begun to change how many industries operate. The ability of machines to analyze large, complex datasets and to detect patterns beyond the scope of the human mind provides a powerful opportunity for application in a healthcare setting. ML has introduced new approaches to many dimensions of medicine including, but not limited to, Pathology, Radiology, drug development, enhancing existing clinical predictive tools, and the management of many diseases including cancer and autoimmune diseases. Currently, ML remains in its infancy but has already started to make an impact in various healthcare disciplines. This research project aimed to provide the foundational training and understanding of the modern approaches to ML and develop the skill set necessary to use available healthcare data to develop and deploy new ML models to assist in the delivery of future healthcare.