Certified Pega Data Scientist PEGACPDS23V1 Exam Preparation

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Certified Pega Data Scientist PEGACPDS23V1 Dumps

Certified Pega Data Scientist

The Certified Pega Data Scientist certification exam is for data scientists who wish to acquaint themselves with the skills and knowledge needed to successfully apply AI in Pega Process AI, Pega Customer Decision Hub and Pega Customer Service. The certification ensures you become familiar with Pega's next-best-action paradigm, have the skills to build predictions that use predictive, adaptive, and text analytics models. You will also gain experience in leveraging the predictions in case management as well as in a 1:1 customer engagement context.

Exam Information

Exam Code: PEGACPDS23V1

Number of Questions: 50 Questions

Duration: 90 Minutes

Passing Score: 70%

Language: English

Prerequisites: Data Scientist

Exam Topics

AI for Customer Decision Hub (8%)

Customer Decision Hub overview

Customer Decision Hub predictions

Adaptive Analytics (22%)

Adaptive models

Monitoring adaptive models

Exporting adaptive model data

Predictive Analytics (26%)

Creating predictions

MLOps

Prediction Patterns (20%)

Creating and understanding decision strategies

Defining prediction patterns

Governance (2%)

Governance

Pega Process AI (8%)

Pega Process AI overview

Predicting fraud

Predicting missing the Service-Level-Agreement

Pega NLP (14%)

Pega NLP overview

Text analytics for email routing

Using entity extraction with chatbot channel

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1. In a decision strategy, the Adaptive Model decision component belongs the

A. Decision Analytics category

B. Business Rules category

C. Arbitration category

D. Predictive Model category

Answer: A

2. As a data scientist, you are tasked with configuring two predictions that are driven by an adaptive model: one for an inbound channel and one for an outbound channel.

To which setting do you need to pay extra attention?

A. Response timeout

B. Adaptive model

C. Predictor fields

D. Control group

Answer: B

3. Which of the following is NOT a use case for NLP in Pega?

A. Sentiment analysis

B. Text classification

C. Speech recognition

D. Entity extraction

Answer: C

4. U+ Insurance uses Pega Process AI? and wants straight-through processing of claims with a low fraud risk. As a data scientist, you create a prediction that calculates the probability that a claim is fraudulent.

What type of prediction do you create to meet this requirement?

A. A case management prediction.

B. A text analytics prediction.

C. A Customer Decision Hub prediction.

D. A fraud detection prediction

Answer: D

5. What are two results of an Adaptive Model? (Choose Two)

A. Priority

B. Propensity

C. Segment

D. Performance

Answer: C, D

6. How can Adaptive Analytics models be deployed in production environments?

A. Manually copying and pasting the code into a production system

B. Ignoring production deployment and only using models for offline analysis

C. Only deploying models in a sandbox environment

D. Using a software development process to test and deploy models

Answer: D

7. The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a new one.

Which feature of MLOps lets you monitor the new model in the production environment without affecting the business outcomes?

A. Change request

B. Shadow mode

C. Historical data capture

D. Connection to machine learning services

Answer: B

8. What is the difference between predictive and adaptive analytics?

A. Predictive models can predict a continuous value.

B. Predictive models predict customer behavior.

C. Adaptive models use the customer data as predict*

D. Predictive models have evidence.

Answer: C

9. What happens when you increase the performance threshold setting of an Adaptive Model rule?

A. The number of active predictors increases.

B. The correlation threshold decreases.

C. The performance of the model is increased.

D. The number of active predictors may decrease.

Answer: B

10. U+ Telecom wants to engage in proactive retention to reduce churn. As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription.

What type of prediction do you create?

A. Case management_____

B. Customer Decision Hub

C. Text analytics

Answer: B