Data Science for Actuaries

This course explores advanced regression techniques, generalized linear models, treebased methods, deep learning, and unsupervised learning, with applications to actuarial science and insurance. Topics include logistic and Poisson regression, decision trees, random forests, neural networks, and clustering methods, alongside hands-on labs using appropriate software to illustrate key concepts.