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| Section | Weight | Objectives |
|---|---|---|
| Predictive Analytics on Big Data | 40% | - High-performance modeling techniques - SAS LASR Analytic Server and SAS Visual Analytics - Working with distributed and in-memory data - Scaling models for large datasets |
| Logistic Regression | 30% | - Model building and variable selection - Interpretation of results - Model assessment and validation - Using SAS/STAT and SAS Enterprise Miner |
| Neural Networks | 20% | - Implementation in SAS Enterprise Miner - Neural network architecture design - Training and tuning neural models - Model evaluation and performance |
| Open Source Models in SAS | 10% | - Productionalization of hybrid models - Deploying Python/R models in SAS environment - Integrating open source code with SAS |
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