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SASInstitute A00-401 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Pipelines in SAS Viya | - Pipeline creation in SAS Model Studio - Data preprocessing nodes - Model training and comparison |
| Topic 2: Data Preparation and Exploration | - Feature engineering basics in SAS Viya - Handling missing values and outliers - Data understanding and quality assessment |
| Topic 3: Supervised Machine Learning Concepts | - Regression and classification fundamentals - Model selection principles - Bias-variance tradeoff |
| Topic 4: Model Deployment and Scoring | - Scoring models in SAS Viya - Model governance and lifecycle concepts |
| Topic 5: Model Evaluation and Optimization | - Cross-validation techniques - Hyperparameter tuning - Performance metrics (AUC, accuracy, RMSE) |
