SPSS Modeler: time series and forecasting (0A028G)

• Anyone forecasting demand with an average of recent months who knows it is not enough.
• Teams with strong seasonality — campaigns, tourism, energy — handling it by eye.
• Analysts asked for a confidence interval on the forecast who do not know where it comes from.

• Introduction to time series analysis: what it is, how the models work and the principles behind forecasting
• Automatic forecasting with the Expert Modeler: fit, error, unexplained variation and how it picks the best model
• Measuring model performance: evaluation methods, ARIMA performance and validation with holdout samples
• Time series regression: trend, seasonality, predictors, autocorrelation and forecasting future values
• Exponential smoothing models: types, custom models, forecasting and validation
• ARIMA modeling: concepts, model types, sequence and autocorrelation charts, and checking against the Expert Modeler

• Labs on IBM SPSS Modeler with real data: streams built, run and fixed during the course.
• Taught directly by IBM Champion instructors from the SIXE team.
• Credly badges available: credly.com/organizations/sixe/badges
• Flexible format — online, classroom or onsite — in closed groups, priced per attendee, in the language of your choice (ES / EN / FR).

Is the Expert Modeler enough?
For many series, yes, and the course starts there. What the rest of the day adds is knowing why it chose that model and what to do when the series has a level shift or an intervention the automatic route cannot see.

Group size and language?
Closed groups of four to ten people, in Spanish, English or French. We run it with fewer than four as well, though it usually pays to wait and fill the group.

• 0A069G — Modeler foundations
• 0A079G — machine learning models
• 0A038G — advanced predictive modeling