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IBM SPS-200 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Preparation | 25% | - Integrate and merge data sources - Sample, partition, and balance datasets - Clean and transform data - Handle missing values and outliers |
| Deployment and Interpretation | 10% | - Score new data - Export and deploy models - Interpret model results and outputs |
| SPSS Modeler Professional Functionality | 10% | - Use SuperNodes and scripting - Customize nodes and outputs - Optimize workflow performance |
| Business Understanding and Planning | 10% | - Align business objectives with analytics goals - Apply CRISP-DM framework |
| Modeling | 30% | - Classification models (Decision Trees, Logistic Regression) - Association and sequence analysis - Model evaluation and comparison - Auto modeling and ensemble techniques - Segmentation models (Clustering, TwoStep) |
| Data Understanding | 15% | - Generate summary statistics - Explore data characteristics - Identify data quality issues |
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