Basics of machine learning, supervised and unsupervised learning, machine learning techniques including neural networks, support vector machines, regression models, Bayesian models, and classification trees. introduction to deep learning. Examples of artificial intelligence for computational medicine (oncology, pathology, physiology, anatomy of diseases) and discussion of the interpretability and ethics of machine learning for medical applications.