SPSS

This course provides the fundamentals of using IBM SPSS Modeler and introduces the participant to data science.

This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project.

This course gets you up and running with a set of procedures for analyzing time series data. Learn how to forecast using a variety of models, including regression, exponential smoothing, and ARIMA, which take into account different combinations of trend and seasonality.

This course presents advanced models to predict categorical and continuous targets. Before reviewing the models, data preparation issues are addressed such as partitioning, detecting anomalies, and balancing data.

Clustering and Association Modeling Using IBM SPSS Modeler (v18.1.1) introduces modelers to two specific classes of modeling that are available in IBM SPSS Modeler: clustering and associations.

This course covers advanced topics to aid in the preparation of data for a successful data science project.

This course provides an introduction to supervised models, unsupervised models, and association models.