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SAP C-PAII10-35 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Basics of Automated Analytics | <8% | - Operational workflows - Automated analytics core capabilities |
| Topic 2: Time Series with Modeler | 8% - 12% | - Time series model creation - Forecast analysis |
| Topic 3: Introduction to Predictive Analytics | 12% | - Key features of SAP Predictive Analytics - Fundamental predictive analytics concepts |
| Topic 4: Data Manager | <8% | - Data manipulation and dataset creation - Scheduling and task management |
| Topic 5: Classification Modeling with Modeler | 12% | - Classification model building - Model evaluation and application |
| Topic 6: Data Science Supporting Automated Analytics | 8% - 12% | - Data pre-processing - Role of data science in predictive analytics |
| Topic 7: Clustering with Automated Analytics | 8% - 12% | - Analyzing cluster results - Clustering techniques and application |
| Topic 8: Social and Recommendation | <8% | - Recommendation model usage - Social data analysis concepts |
| Topic 9: Predictive Factory | 12% | - Model deployment and management - Predictive Factory architecture and components |
| Topic 10: Regression Modeling with Modeler | <8% | - Regression model development - Validation and application of regression models |
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