Course

Time-series Forecasting

This course enables learners to understand the various components of a time series and how various techniques use these components to generate a forecast. At the end of this course, learners will also be able to assess the accuracy of generated forecasts and understand areas where specific forecasting techniques can be applied.

4 Lessons
Outcomes

By the end of the course, learners will be able to:

  • Components of a time series and decomposition data into these components (using R)
  • Estimating seasonal indices
  • Smoothing techniques: Moving averages, exponential smoothing, etc.
  • Interpreting autocorrelation and partial auto-correlation plots
  • Stationary and non-stationary series and tests to ascertain such series
  • Forecasting time series through ARIMA, Holt Winters, etc. techniques

Reference book for Forecasting: Forecasting: Principles and Practice

 Level: 02
Duration: 05 Hours
Pre-requisites: Refer Topics on Mathematics
What’s next: NA