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Contents: Introduction to business forecasting and predictive analytics; the forecast process. data considerations, and model selection; extrapolation 1. Moving a verages and exponential smoothing; extrapolation 2. Introduction to forecasting with regression trend models; explanatory models 1. Forecasting with multiple regression causual models; explanatory models 2. Time - series decomposition; explanatory models3. ARIMA (Box - Jenkins) - Type forecasting models; predictive analytics: Helping to make sense of Big Data; classifification models: The most used models in analytics; ensemble models and clustering; text mining; forecast/analytics implementation.