Machine Learning and Data Mining
Machine learning and data mining bring together methods coming from statistics and computer science and apply these to databases both large and small. They use a powerful and diverse set of techniques and algorithms to discover patterns and relationships in data with the final goal of creating knowledge from these data. These methods are increasingly being applied to the vast amounts of health data that are generated through sources including electronic medical records, medical and pharmaceutical claims, medical imaging, wearable and implantable devices and social media.
This course provides an introduction to data mining and machine learning, including both supervised and unsupervised techniques. You will learn about the underlying theory, as well as gain the practical know-how required to effectively apply these techniques to real-world health datasets to answer new health data science problems. The widely-used, open-source Python programming language is used to teach the course.