Foundation Course 
Business Forecasting

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Program Objective

This program is designed to equip professionals with the knowledge on various time series and regression methods for developing forecasting models 

Program Benefits

On completion of the course, the participants will be able to 

  • Develop forecasting models using time series and regression techniques 
  • Interpret and evaluate various models for forecasting
  • Hands-on experience on the usage of open source packages like R, R Studio, Python, etc 


  • Any science, commerce or engineering graduate can participate in the program
  • The knowledge of a programming language is desirable but not necessary
  • Elementary knowledge of statistical techniques like descriptive statistics, test of hypothesis, etc is preferable
  • The examination will be conducted at the end of the course and successful candidates will be issued the certificate

Course Content

  1.  Introduction to time series
  2. Understanding of trends and patterns in time series data
  3. Time series decomposition
  4. Stationary series and unit root tests
  5. Importance of differencing
  6. Exponential smoothing
  7. Holt Winter methods
  8. Linear regression
  9. Autocorrelation (ACF) and partial autocorrelation functions (PACF) functions
  10. Box Jenkins methods (ARIMA models)
  11. Model diagnostics and residual analysis
  12. Intervention models
  13. Dynamic regression
  14. Multivariate forecasting techniques