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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Open Source Models in SAS | 10% | - Integrating open source code with SAS - Deploying Python/R models in SAS environment - Productionalization of hybrid models |
| Topic 2: Neural Networks | 20% | - Training and tuning neural models - Implementation in SAS Enterprise Miner - Model evaluation and performance - Neural network architecture design |
| Topic 3: Logistic Regression | 30% | - Using SAS/STAT and SAS Enterprise Miner - Model building and variable selection - Interpretation of results - Model assessment and validation |
| Topic 4: Predictive Analytics on Big Data | 40% | - High-performance modeling techniques - SAS LASR Analytic Server and SAS Visual Analytics - Scaling models for large datasets - Working with distributed and in-memory data |
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