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| Section | Objectives |
|---|---|
| Topic 1: Data Sets and Integration | - Data flows and dataset configuration - External data integration with Pega platform |
| Topic 2: Data Preparation | - Data cleansing and transformation - Feature engineering for predictive models |
| Topic 3: Data Understanding | - Exploratory data analysis concepts - Data sources and data types in Pega |
| Topic 4: Pega Decisioning and AI Integration | - Embedding predictive analytics in Pega applications - Adaptive models and decision strategies |
| Topic 5: Predictive Analytics | - Predictive model types in Pega (classification, regression) - Model training and evaluation |
1. 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) Use a Google ML model
C) Use Pega machine learning to build a model
D) Create a Text extraction model
E) Create an adaptive self-learning model
2. You are the Decisioning Consultant on an Al-powered one-to-one Customer Engagement implementation project. You are asked to design the Next-Best-Action prioritization expression that balances the customer needs with the business objectives.
What factors do you consider in the prioritization expression?
A) product compatibility rules
B) business levers
C) customer contact rules
D) product eligibility rules
3. Which business objective is best suited for the Next-Best-Action approach?
A) Change Management
B) Productivity
C) Growth
D) Employee satisfaction
4. A company wants to create a data set that includes mock-up customer add Which method is available to populate these fields?
A) Import
B) Monte Carlo
C) Bayesian
D) Propensity
5. To which property is the output of a PMML model automatically mapped?
A) pxSegment
B) pxPMMLOutputd
C) pxResult
D) pxOutcome
Solutions:
| Question # 1 Answer: A,C,D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: D |
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