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Pegasystems PEGAPCDS87V1 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Pega Decisioning and AI Integration | - Embedding predictive analytics in Pega applications - Adaptive models and decision strategies |
| Topic 2: Data Understanding | - Exploratory data analysis concepts - Data sources and data types in Pega |
| Topic 3: Data Preparation | - Feature engineering for predictive models - Data cleansing and transformation |
| Topic 4: Predictive Analytics | - Model training and evaluation - Predictive model types in Pega (classification, regression) |
| Topic 5: Data Sets and Integration | - External data integration with Pega platform - Data flows and dataset configuration |
Pegasystems Pega Certified Data Scientist (PCDS) 87V1 Sample Questions:
1. What is the key characteristic that Next-Best-Action must consider to satisfy customer needs?
A) Relevancy
B) Service
C) Mobility
D) Fraud
2. The Prediction Studio portal supports the creation of two distinct types of predictive Scoring models are used to__________________.
A) differentiate between good, better and best
B) score different propositions
C) predict continuous behavior
D) predict binary behavior
3. The Prioritize component always outputs
A) top 3 offers
B) on arbitrary number of offers
C) all eligible offers
D) top 1 offer
4. From two chum models with the similar performance, we choose the one with the________________.
A) most evidence
B) highest churn rate
C) fewest number of predictors
D) highest number of predictors
5. When defining outcomes for an Adaptive Model you must define_________________.
A) positive, negative and neutral behavior values
B) one or more positive behavior values
C) only negative behavior values
D) behavior values to be ignored
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: C |
