SAS Certified Predictive Modeler 

offered by SAS Institute Of Management Studies

Use the Basic Metadata Advisor

Use the Advanced Metadata Advisor

Customize the Advanced Metadata Advisor

Set Role and Level meta data for data source variables

Set the Role of the table (raw, scoring, transactional, etc)

Create and interpret plots, including Histograms, Pie charts, Scatter plot, Time series, Box plot

Identify distributions

Find outlying observations

Find number (or percent) of missing observations

Replace zero values with missing indicators using the REPLACEMENT node

Use the TRANFORMATION node to be able to correct problems with input data sources, such as variable distribution or outliers

Select a portion of a data set using the SAMPLE node

Partition data with the PARTITION Node

Use the VARIABLE SELECTION node to identify important variables to be included in a predictive model

Data partitioning: training, validation, test data sets

Observations (cases), independent (input) variables, dependent (target) variables

Explain how decision trees identify split points

Build decision trees in interactive mode

Change splitting rules

Explain the relationship between target variable and regression technique

Explain linear regression