Health Analytics Graduate Courses, Northwestern University School of Professional Studies - Northwestern School of Professional Studies

Course Schedule

Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.

Online Sync Sessions are an integral part of the online learning experience. Additional information about learning concepts and assignments may be discussed and sync sessions offer valuable opportunities for students to interact with their faculty and peers during the term. We encourage all students to attend live, but if they are unable to, sync sessions will be recorded and posted within Canvas to allow for an asynchronous model of success as well.

MSHA 422-DL : Artificial Intelligence and Practical Machine Learning

Description

The course introduces machine learning and its applications to problems in health care. It surveys machine learning techniques, including resampling techniques, model selection and regularization, tree-based methods, principal components analysis, cluster analysis, ensemble methods, and artificial neural networks. Students will implement machine learning models with open-source software for data science. They will explore and learn from data, finding underlying patterns useful for data reduction, feature analysis, prediction, and classification.

Prerequisites: MSHA 409 and MSHA 410