Applied Forecasting

The use of data to reduce uncertainty surrounding decision making is one of the goals of data analytics. Forecasting is the process of utilizing historical data and current events to make statements about the future. It is widely used by industry practitioners and policy makers for practical purposes ranging from data-driven decision making, scenario planning and budgeting. In this course, students will learn the key properties of time series such as seasonality and trends. They will learn to construct predictive models using time series regressions and forecasting workhorses such as the ARIMA model. The course targets industry practitioners who are interested in learning the applications and industry use cases of forecasting. At the end of the course, students will acquire skills in building forecasting models using both scripting and non-scripting-based computing programs and deploying forecasting results for decision making.

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