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IBM Certified Specialist - SPSS Modeler Professional v2

This certification is for individuals with a working knowledge of IBM SPSS Modeler version 14 or higher working in government, academia, or business who use the IBM SPSS Modeler product to perform data mining activities including data preparation, data understanding, and modeling

Recommended Training and Required Exam(s)

 Required Exam Recommended Training 
BAS-010: IBM SPSS Modeler Professional v2
  • Introduction to IBM SPSS Modeler and Data Mining (V14.2) (0A003G)
  • Introduction to IBM SPSS Modeler and Data Mining (V15) (0A004G)
  • Predictive Modeling with IBM SPSS Modeler (0A032G)
  • Clustering and Association Models with IBM SPSS Modeler (0A042G)
  • Advanced Data Preparation Using IBM SPSS Modeler (V15) (0A054G)

Skills acquired during recommended training

Business Understanding

  • CRISP-DM process methodology
  • Identifying business objectives
  • Translating business objectives to data mining goals

Data Understanding

  • Read data from various sources - Source nodes
  • Use data visualization - Graph nodes
  • Understand distributions and summary statistics
  • Identify data quality issues
  • Identify and understand outliers
  • Identify anomalies - Anomaly node
  • Understand relationships among variables

Data Preparation

  • Combine datasets using the Merge and Append nodes
  • Derive new fields - Fields Pallet nodes
  • Aggregate and restructure datasets
  • Use the Select node
  • Sampling and balancing datasets
  • Methods for reducing the dimensionality of the dataset
  • Understand SQL pushback
  • Understand use of data caching
  • Methods for missing value replacement

Modeling

  • Partition the dataset
  • Understand which models to use for sets or binary outcomes
  • Understand which models to use for numeric outcomes
  • Understand model types and basic operations
  • Combine models using the Ensemble node
  • Auto modeling nodes

Evaluation of Results

  • Use the Analysis node
  • Produce and interpret Evaluation charts
  • Interpret model results using data visualizations (charts) and classification tables
  • Interpret Generated Model Nuggets

Deployment of Results

  • Use the Export nodes
  • Score new data using generated models
  • Understand monitoring of deployed models