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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Predictive Analytics | 20% | - External model integration (PMML, H2O) - Creating and importing predictions - MLOps and model lifecycle - Model evaluation metrics (AUC, Lift) |
| Topic 2: AI for Customer Decision Hub | 6% | - Customer Decision Hub overview - Next-Best-Action framework - Predictions in decisioning |
| Topic 3: Model Governance & Ethics | 4% | - Lifecycle governance - Model monitoring and compliance - Fairness and explainability |
| Topic 4: Prediction Patterns & Decision Strategies | 18% | - Using prediction patterns - Arbitration and prioritization - Designing decision strategies - Combining predictions in strategies |
| Topic 5: Pega Process AI | 10% | - Embedding AI in case management - Predicting SLA and risk outcomes - Predictive models for operational processes |
| Topic 6: Pega NLP & Text Analytics | 14% | - Processing unstructured text data - Text prediction configuration - Sentiment and intent analysis |
| Topic 7: Adaptive Analytics | 28% | - Model performance monitoring - Learning and outcome tracking - Predictor setup and management - Adaptive model design and configuration |
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