C2090-930: IBM Certified Specialist – SPSS Modeler Professional v3

Exam Name: IBM Certified Specialist – SPSS Modeler Professional v3

Exam Code: C2090-930

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IBM C2090-930 Exam Summary:

Exam Name IBM Certified Specialist – SPSS Modeler Professional v3
Exam Code  C2090-930
Exam Duration  90 minutes
Exam Questions  60
Passing Score  67% 
Exam Price   $200 (USD)
Sample Questions   IBM SPSS Modeler Professional Certification Sample Question
Practice Exam   IBM SPSS Modeler Professional Certification Practice Exam

IBM C2090-930 Exam Topics:

Objective Details 
SPSS Modeler Professional Functionality (10%)  – Identify the purpose of each palette
– Describe the use of SuperNodes
– Describe the advantages of SPSS Modeler scripting
Business Understanding and Planning (10%)  – Describe the CRISP-DM process
– Describe how to map business objectives to data mining goals 
Data Understanding (15%)  – Describe appropriate nodes for summary statistics, distributions, and visualizations (for example, graph nodes, output nodes)
– Describe data quality issues (for example, outliers and missing data) 
Data Preparation (20%)  – Describe methods for data transformation (for example, Derive node, Auto Data Prep node, Data Audit node and Filler node)
– Describe how to integrate data (for example, Merge node and Append node)
– Describe sampling, partitioning, and balancing data (for example, Sample node, Balance node and Partition node)
– Describe methods for refining data (for example, Select node, Filter node and Aggregate node) 
Modeling (20%)  – Describe classification models (including GLM and regression)
– Describe segmentation models
– Describe association models
– Describe auto modeling nodes
– Demonstrate how to combine models using the Ensemble node 
Evaluation and Analysis (15%)  – Demonstrate how to interpret SPSS Modeler results (for example, using Evaluation node, Analysis node, and data visualizations)
– Describe how to use model nugget interfaces 
Deployment (10%)  – Describe how to use Export nodes (tools for exporting data)
– Identify how to score new data using models
– Identify SPSS Modeler reporting methods