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Pegasystems Pega Certified Data Scientist (PCDS) 87V1 Sample Questions:

1. 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) business levers
B) customer contact rules
C) product eligibility rules
D) product compatibility rules

2. When selecting the list of predictors for an adaptive model you should

A) consider a wide range of properties
B) select at least one date property
C) select up to a maximum of 500 predictors
D) always use numeric type for integer properties

3. A Scoring Model allows you to differentiate between

A) Accept, Reject, Maybe Later
B) Good, Bad
C) Good, Bad, Unknown
D) Good, Better, Best

4. A Text Analyzer performs natural language processing on a piece of text. It then produces a structured output, which can be analyzed using reports.
What type of text analysis does the text analyzer perform?

A) Word analysis
B) Classification
C) Word count
D) Cross reference analysis

5. U+ Bank has a chat bot to service its customers. When customers initiate a chat, they are asked to describe the issue they would like to resolve. U+ Bank wants to increase customer satisfaction by assigning the support agent from the correct department to help the customer.
As a data scientist, you need to create a model which will predict the correct department based on the customer's input. To do this you build a_______________.

A) Text extraction model
B) Pegs machine learning model
C) Text categorization model
D) Adaptive model

Solutions: