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Topics include generalized linear models such as logistic and Poissonregression, among many others. Random effects will be introduced, with emphasison linear and generalized linear mixed models, repeated measures, and longitudi-nal data. These models will extend to general models for dependent data, suchas spatial data and time series models. Lastly, nonlinear models through neuralnetworks and deep learning will be discussed.