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Pegasystems PEGAPCDS87V1 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Sets and Integration | - Data flows and dataset configuration - External data integration with Pega platform |
| Predictive Analytics | - Model training and evaluation - Predictive model types in Pega (classification, regression) |
| Pega Decisioning and AI Integration | - Embedding predictive analytics in Pega applications - Adaptive models and decision strategies |
| Data Preparation | - Data cleansing and transformation - Feature engineering for predictive models |
| Data Understanding | - Data sources and data types in Pega - Exploratory data analysis concepts |
Pegasystems Pega Certified Data Scientist (PCDS) 87V1 Sample Questions:
A legal firm wants to use text analytics for easier and faster access to information to help with compliance related issues. The legal firm needs a taxonomy of legal concepts.
What is a taxonomy?
- A. The output of an expert survey
- B. A list of business rules
- C. A sentiment analysis model
- D. A list of valid categories
As a Data Scientist you want to use a predictive model to detect potential churn for a telco company .
Which three options do you have? (Choose Three)
- A. Import a third party PMML model
- B. Create an adaptive self-learning model
- C. Use a Google ML model
- D. Create a Text extraction model
- E. Use Pega machine learning to build a model
Which property is automatically recomputed for each decision component?
- A. Priority
- B. Propensity
- C. Rank
- D. Order
Which data is usually not appropriate to be used as a predictor?
- A. Usage data
- B. Historical interaction data
- C. Customer name
- D. Customer zip code
A company wants to create a data set that includes mock-up customer add Which method is available to populate these fields?
- A. Bayesian
- B. Propensity
- C. Import
- D. Monte Carlo
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