Artificial Intelligence and Practical Machine Learning

1 Unit · Graduate

The course introduces machine learning and 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 implement machine learning models with open-source software for data science. They explore data and learn from data, finding underlying patterns useful for data reduction, feature analysis, prediction, and classification. (Required: MSHA 409-DL and MSHA 410-DL .)