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SASInstitute A00-225 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Exploration and Preparation | - Data cleaning, missing value handling, and transformations - Feature selection and variable reduction techniques |
| Topic 2: SEMMA Methodology and Enterprise Miner Environment | - Understanding SEMMA process (Sample, Explore, Modify, Model, Assess) - SAS Enterprise Miner project workflow and nodes |
| Topic 3: Predictive Modeling Techniques | - Decision trees and rule-based models - Regression models (linear and logistic regression) - Neural networks and ensemble methods |
| Topic 4: Clustering and Segmentation | - K-means clustering and hierarchical clustering |
| Topic 5: Model Deployment Concepts | - Scoring data and operationalizing models |
| Topic 6: Model Assessment and Validation | - Lift charts, ROC curves, and confusion matrix - Model comparison and selection strategies |
