All levels of companies need to make predictions ranging from the mundane sales forecast to the more sophisticated cases that may have limited data such as predicting competitive responses. This course will cover both the art (modelling) and science of prediction. Topics will include exploratory data analysis techniques and visualization of data, multiple linear regression and model building, machine learning (with a focus on classification and clustering), probabilistic inference models, diagnostics and model validation. Practical applications of these topics as well as the use of up to date software tools will be emphasized.
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