MSDS 604 - Time Series Analysis

Unit(s): 1

This course is an intensive introduction to the existing methods for time series forecasting. The topics include decomposition, moving average smoothing, forecasting with ARIMA, exponential smoothing, model selection methods including train-test split and cross-validation, and a broad introduction to more advanced developments. The primary language used in this course will be Python.

Restriction: Level Restricted to Graduate; Field of study restricted to Data Science Major
College of Arts and Sciences