PUBH 8301 - Biostatistical Machine Learning in Public Health

This is an introductory course on machine learning algorithm with application to public health data. Topics include linear model selection and regularization, tree-based methods, support vector machines, unsupervised leaning, and deep learning, along with other machine learning approaches that can be used to effectively and efficiently analyze potentially large public health data. Up-to-date machine learning techniques and analysis procedures will be introduced and corresponding R programs will be discussed. It is intended for advanced students in public health, data science, or other related area pursuing a career in research or analytics. Statistical models covered in this course can readily be applied to analyses in other disciplines such as biology and health administration.   PREREQUISITE(S): PUBH 7-8152 (Biostatistics II) or equivalent. Students outside of UoM’s Public Health program are welcome but must obtain permission from the course instructor.