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In tihs course, you will :
- Learn about the most important time series properties.
- Discover the importance of stationarity in ARMA models.
- how to check for stationarity visually and using a standard statistical test
- Learn the fundamental structure of ARMA models and apply it to generate ARMA data and fit an ARMA model.
- how to fit ARMA, ARIMA, and ARMAX models using the elegant statsmodels package
- You will learn how to identify promising model orders from the data itself, and then, once the most promising models have been trained, you will learn how to select the best model from this fitted selection.
- Discover a fantastic framework for organising your time series projects.
- Learn how to fit more complex data with seasonal ARIMA models.
- Learn how to decompose this data into seasonal and non-seasonal components, and then apply all of your ARIMA tools to one final global forecast challenge.
Syllabus :
- ARMA Models
- Fitting the Future
- The Best of the Best Models
- Seasonal ARIMA Models
