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SAP C-PAII10-35 Exam Description:
This certification exam validates that the candidate possesses the fundamental and core knowledge required of the consultant profile. This certification proves that the candidate has an overall understanding and in‐depth technical skills to participate as a member of a project team in a mentored role. This certification exam is recommended as an entry level qualification to allow consultants to get acquainted with the fundamentals of SAP Predictive Analytics including how the various capabilities of SAP Predictive Analytics provide insights into specific business predictive analytics challenges.
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C-PAII10-35 Exam Certification Details:
| Level: | Associate |
| Cut Score: | 68% |
| Duration: | 180 mins |
| Languages: | English |
| Exam: | 80 questions |
| Sample Questions: | SAP C-PAII10-35 Exam Sample Question |
SAP C-PAII10-35 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Classification Modeling with Modeler | 12% | - Model evaluation and application - Classification model building |
| Topic 2: Time Series with Modeler | 8% - 12% | - Forecast analysis - Time series model creation |
| Topic 3: Data Science Supporting Automated Analytics | 8% - 12% | - Data pre-processing - Role of data science in predictive analytics |
| Topic 4: Basics of Automated Analytics | <8% | - Automated analytics core capabilities - Operational workflows |
| Topic 5: Introduction to Predictive Analytics | 12% | - Key features of SAP Predictive Analytics - Fundamental predictive analytics concepts |
| Topic 6: Clustering with Automated Analytics | 8% - 12% | - Clustering techniques and application - Analyzing cluster results |
| Topic 7: Regression Modeling with Modeler | <8% | - Regression model development - Validation and application of regression models |
| Topic 8: Social and Recommendation | <8% | - Recommendation model usage - Social data analysis concepts |
| Topic 9: Data Manager | <8% | - Scheduling and task management - Data manipulation and dataset creation |
| Topic 10: Predictive Factory | 12% | - Predictive Factory architecture and components - Model deployment and management |
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