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