A second course in statistical modeling with a focus on modern methods. The first part of the course focuses on regression methods, including linear and nonlinear regression, and regression trees, with a short introduction to predictive modeling: training vs. validation data sets, over-fitting and model tuning, and methods to measure performance of regression models. The second portion of the course emphasizes classification modeling techniques such as discriminant analysis, classification trees, and neural networks.