Data Science with Actuarial Applications

This course provides a comprehensive treatment of various techniques from statistics, predictive analytics and machine learning that can be used to analyze data sets relevant for actuarial applications. Specific topics covered include: modeling principles and practice, analysis and estimation of survival and multiple-state models, insurance pricing using generalized linear models, classification and tree-based methods, and Monte Carlo simulation of time series.