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This course will build on the learning from the Statistical and Predictive Modelling I course and cover more advanced concepts such as regression analysis, clustering algorithms, conjoint measurement, and decision tree analysis. Students will be able to integrate and calibrate these model structures for evaluation and implementation purposes.