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Pegasystems PEGAPCDS87V1 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Adaptive Analytics | 28% | - Model performance monitoring and diagnostics - Configuring and tuning predictors - Adaptive Decision Manager (ADM) concepts |
| Topic 2: AI & Natural Language Processing | 12% | - Sentiment analysis and text processing - Pega NLP fundamentals |
| Topic 3: Model Governance & Ethics | 5% | - Bias detection and compliance - AI governance framework |
| Topic 4: Pega Process AI | 10% | - Predictive case completion - Fraud and risk detection models |
| Topic 5: Predictive Analytics | 25% | - Model evaluation metrics (AUC, lift, propensity) - Importing and validating PMML/external models - Prediction Studio usage |
| Topic 6: Decision Strategies & Next-Best-Action | 20% | - Arbitration and prioritization logic - Designing and testing decision strategies - Core decisioning principles |
Pegasystems Pega Certified Data Scientist (PCDS) 87V1 Sample Questions:
In a strategy defined in the "Retention" issue and the "X-Sell" group, you can import
- A. propositions from the Sales issue
- B. propositions from all groups under the "Retention" issue
- C. propositions from "X-Sell" group
- D. all propositions from the system
From two chum models with the similar performance, we choose the one with the________________.
- A. highest number of predictors
- B. highest churn rate
- C. fewest number of predictors
- D. most evidence
You can save a regression model as a______________.
- A. Regression Model rule
- B. Decision Tree rule
- C. Scorecard rule
- D. Predictive Model rule
A company wants to capture the sentiment of relevant Twitter messages to allow its customer service representatives to concentrate only on the negative messages.
Sentiment refers to the general attitude of the author towards a subject and can be____________.
- A. Offensive
- B. Absent
- C. Defensive
- D. Positive
evidence an assessment of its viability, the Adaptive Model produces three outputs:
Propensity, Performance and
What is evidence in the context of an Adaptive Model?
- A. The number of customers who have responded to the modeled offer
- B. The number of customers who exhibited statistically similar behavior
- C. The likelihood of a statistically similar behavior
- D. The number of statistical bins used to evaluate the response
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