PEGACPDS23V1 Certified Pega Data Scientist 23 Exam Dumps

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PEGACPDS23V1 Certified Pega Data Scientist 23 exam is for developers and technical staff members who want to learn how to develop Pega applications. There are 60 questions in the real Pegasystems PEGACPDS23V1 exam, and you have 90 minutes to finish the test. The required passing score for the PEGACPDS23V1 exam is 65%. The available languages are English and Japanese. We provide the latest Certified Pega Data Scientist 23 PEGACPDS23V1 exam dumps, which can make sure you pass the test easily. Free Certified Pega Data Scientist 23 PEGACPDS23V1 exam dumps are available below.

Page 1 of 6

1. The Prioritize component always outputs __________.

on arbitrary number of offers

top 1 offer

top 3 offers

all eligible offers

2. An Adaptive model component in a decision strategy can output ____________.

an optimized strategy

the customer's propensity to accept an action

the number of customers eligible for an action

an action

3. A data scientist and an application developer must configure a chatbot to improve customer service response time. The application developer created the digital messaging channel.

What is the next step for the data scientist?

Create a new text prediction and associate it with the digital messaging channel that the application developer creates.

Create and train a new text prediction and inform the application developer.

Modify pySystemEntities model to meet business needs, and then associate it with the digital messaging channel that the application developer created.

Train the text prediction that the system generates.

4. A coffee company wants to create a data set that includes mock up customer address information and the likelihood to churn.

Which method is available to populate these fields?

Bayesian

Propensity

Expression

Import

5. What is entity extraction in NLP?

The process of identifying the subject of a sentence

The process of identifying the sentiment of a sentence

The process of identifying the action that a user intends to take based on their input

The process of identifying specific entities or objects mentioned in a sentence, such as people, places, and organizations

6. An application developer and a data scientist are working together on a chatbot project. They want the chatbot to detect that the customer wants to change the account home address.

To achieve this goal, the chatbot must:

- Detect the topic of the message

- Run the correct case type

- Extract 2 entities: new address and account number.

What main tasks must they do to achieve this business scenario? (Choose Three)

The application developer creates the digital messaging channel.

The application developer creates the case type and designs the conversation flow.

The data scientist uses the entity extraction model from pySystemEntities model and trains the topic detection model.

The data scientist creates the text prediction and builds one topic detection and two entity extraction models.

The data scientist trains the text prediction: One topic detection model and several entity extraction models.

7. U+ Bank introduces a new credit card that has no historical customer behavior data. U+ Bank wants to offer this credit card on the personalized web portal.

Given the scenario, which rule type must you use?

Adaptive model

Pega machine learning model

When rule

Decision table

8. As a data scientist, you want to export the model data and the predictor data for the Credit Cards group from the Grow business issue for further analysis. You are tasked to modify the data flow that selects the correct data. Match the data flow component to the function it achieves.

9. What is Adaptive Analytics?

A statistical technique for analyzing data

A machine learning algorithm for predicting future outcomes

A flexible approach to data analysis that can adapt to changing business needs and data environments

A software application for managing business workflows

10. You can use various data types in adaptive analytics. Some of these require preprocessing before being used as a potential predictor. Others can be used directly.

Which two data types require no preprocessing? (Choose Two)

Event stream data, such as recent transactions

Symbolic data with up to 200 distinct values, such as products bought previously

Text data such as Twitter messages

Dates with absolute time/date values, such as birthdays

Numeric data such as customer age and income

Page 2 of 6

11. U+ Bank wants to offer a 10% discount for customers whose CLV value is higher than 400.

Which strategy component should you use to meet the new requirement?

Group by

Prioritize

Filter

Set property

12. The purpose of regular inspection is to detect factors that negatively influence the performance of the adaptive models and the success rate of the actions.

Which two issues should be discussed with the business? (Choose Two)

Actions that are offered so often that they dominate other actions

Actions that have a low number of responses

Actions for which the model is not predictive

Predictors with a low performance_________

Predictors that are never used

13. What are the benefits of using Predictive Analytics?

Faster insights from data

More accurate predictions

Increased agility in responding to changing business needs

Improved customer service

14. You have created a predictive model using R and have exported it to Predictive Model Markup Language (PMML).

Which component in a decision strategy do you use to leverage the PMML model?

Third-party model

Predictive model

Scorecard model

Decision tree

15. The purpose of predictions is to______________

monitor the success rate of individual actions

add predictors to adaptive models

build adaptive models

add best data scientist practices to adaptive models

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

Priority

Propensity

Segment

Performance

17. U+ Bank, a retail bank, recently implemented a project in which credit card offers are presented to qualified customers when they log in to the web self-service portal. The bank does not want any bias except to satisfy the eligibility condition Age >=18.

As a decisioning consultant, how do you configure the ethical bias policy to allow a minimum bias on age?

0.7 Gini

0.1 Gini

No detection

0 Gini

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

The number of active predictors increases.

The correlation threshold decreases.

The performance of the model is increased.

The number of active predictors may decrease.

19. With the open-source GitHub repository Pega Data Scientist Tools, you can ______________.

visualize the performance of a predictor

analyze your data in SQL

build XGBoost models

upload predictive models to Prediction Studio

20. Which of the following is NOT a benefit of using Pega Process AI?

Increased efficiency and productivity

Improved customer satisfaction

Reduced costs

Enhanced data security

Page 3 of 6

21. Adaptive models can learn without historical evidence.

What is the starting propensity of every action?

0.25

0.5

22. What is data cleansing in Predictive Analytics?

Removing duplicate or inconsistent data

Removing irrelevant data

Removing confidential data

All of the above

23. U+ Bank presents a personalized credit card offer to its customers when they log in to their accounts on the website. The Predict Web Propensity prediction calculates the likelihood of a customer clicking on the credit card offer banner.

In Pega Customer Decision Hub™, what does the Clicked response label signify in this context?

The customer showed interest in the credit card offer.

The customer ignored the credit card offer.

The customer received an email with the credit card offer.

The customer did not respond to the offer.

24. What is provided as input to a predictive model component by the strategy?

Customer data

The strategy outcome

Performance data

Proposition identifier

25. Which decision component allows you to monitor the real-time performance of a third- party Churn Model?

PMML Model

Scorecard Model

Predictive Model

Adaptive Model

26. The Adaptive Model component in a strategy computes __________.

a propensity value for each action

a single accept rate for all actions

a unique accept rate for each action

a single propensity value for all actions

27. Drag and drop the answer to complete the sentence.

28. Which of the following is NOT a use case for Pega Process AI?

Fraud detection and prevention

Customer service automation

Sales forecasting and analysis

Supply chain optimization

29. Pega Customer Decision Hub™ uses the P*C*V*L arbitration formula to select the next best action for each customer.

Which description best describes the purpose of the formula?

To balance customer needs with business objectives.

To ensure that the customer is always given the best offer, regardless of the business objective.

To provide insight into business processes.

To ensure that every customer receives the same action.

30. Why is leaving the default settings of an adaptive model unchanged important?

Using the default settings is based on best practices.

Changing the settings is not a task for a data scientist.

Changing the settings does not effect on model performance.

Adaptive Decision Manager adjusts the settings automatically adjusted during adaptive learning.

Page 4 of 6

31. Which of the following is a technique used in NLP for text classification?

SVM (Support Vector Machines)

K-Means

Random Forest

Naive Bayes

32. What is predictor importance in the context of machine learning?

The importance of each predictor in calculating propensity.

The importance of each predictor to the business team.

The importance of each predictor across all models.

The importance of each decision in calculating propensity.

33. 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)

Create a Text extraction model

Use a Google ML model

Use Pega machine learning to build a model

Import a third party PMML model

Create an adaptive self-learning model

34. What is the importance of data normalization in Predictive Analytics?

It ensures that all data is in the same format

It ensures that all data is relevant to the model

It ensures that all data is accurate

It ensures that all data is on the same scale

35. What is the purpose of the Combiner function in the scorecard?

To create complex predictor field expressions.

To apply a data transform to run the scorecard for different customers.

To set the Cutoff value to distinguish potential churners from loyal customers.

To select a method to calculate the score.

36. The objective of Pega Process AI™ is to interpret the incoming data and then decide on the best action to take.

In which two ways can you better analyze the incoming data? (Choose Two)

Event processing

Predictive analytics

Text analytics

Decision strategies

Business rules

37. In a decision strategy, which component is required to enable access to primary customer properties?

None; customer properties are available.

Customer Import

Data Import

Set Property

38. In the delta view in Visual Business Director, what does the red colored cone indicate?

The source data value is too small

The source data value is smaller than the reference data value

The source data value is larger than the reference data value

The source data value is too large

39. An online store is interested in increasing its revenues from cross-selling and wants to predict the acceptance rate of the offers presented on their website.

A customer's propensity to accept an offer increases when ___________________.

similar offers were rejected by the customer

similar offers were accepted by the customer

the offer was rejected by similar customers

the offer was accepted by similar customers

40. Creating predictive models Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models: ____________ and ____________. (Choose Two)

adaptive models

continuous models

binary models

voice to text model

Page 5 of 6

41. What is the importance of data quality in Adaptive Analytics?

It ensures accurate and reliable insights

It speeds up the data analysis process

It makes it easier to implement machine learning algorithms

It allows for more complex data visualizations

42. When executing a decision strategy, the dotted line arrow in a decision strategy means data is __________.

copied to the component the arrow points to

referenced by the component the arrow points to

referenced by the component the arrow originates from

copied to the component the arrow originates from

43. A company wants to capture the sentiment of relevant Twitter messages to allow its customer service representatives to concentrate only on the negative messages.

Sentiment refers to the general attitude of the author towards a subject and can be ____________.

Defensive

Absent

Offensive

Positive

44. Which property is automatically recomputed for each decision component?

Order

Rank

Propensity

Priority

45. Drag the correct response to the blank space to complete the sentence.

46. To enable an assessment of its reliability the adaptive model produces four outputs: propensity, performance, evidence and positives. The Performance of an adaptive model that has not collected any evidence yet is______.

100

47. U+ Bank, a retail bank, offers the Standard card, the Rewards card and the Rewards Plus card to its customers. The bank wants to display the banner for the offer that each customer is most likely to click; therefore, their Arbitration uses Propensity from the AI models.

If you are debugging the Next-BestAction decision strategy, which strategy component will show you if the result of the Arbitration is correct?

Group By

Set Property

Prioritize

Filter

48. In a Prioritize component, the best action can be determined based on the value of __________.

Customer, Value

Propensity

Average Margin

Customer.Income

49. To implement eligibility criteria you can use a ____________ component.

Decision Table

Switch

Group by

Segment

50. In m decision strategy, in order to select the proposition with the highest propensity, you use a __________.

Priorities component, and sort propensity from highest to lowest

Priorities component, and sort propensity from lowest to highest

Switch component, and sort propensity from lowest to highest

Switch component, and sort propensity from highest to lowest

Page 6 of 6

51. U+ Telecom uses predictive analytics for case management. As a data scientist, you have created a predictive model based on recent historical company data and have placed the new model in shadow mode.

Which statement is true about the new predictive model?

The active model and the new model affect business outcomes.

The new model affects business outcomes.

The new model does not affect business outcomes.

The active model does not affect business outcomes.

52. U+ Air recently enabled a chatbot on its website to interact with customers. The airline asked a data scientist to configure the chatbot to recognize all ticket number patterns that the airline uses. The company wants the chatbot to be resistant to human error and detect also unusual ticket numbers.

Which combination of entity extraction methods can the data scientist implement to achieve this business requirement? (Choose Two)

Machine learning

Keywords

Ruta script

Topic detection

53. What is the key characteristic that Next-Best-Action must consider to satisfy customer needs?

Service

Fraud

Mobility

Relevancy

54. In Pega Customer Decision Hub™, adaptive models calculate propensities that support the optimization of customer interactions.

How does the system support explanations of the factors that drive a single propensity calculation?

By showing the current prioritization of next-best-action results.

By offering built-in support for calculating global predictor importance.

By exporting the ADM predictor importance report for further analysis.

By providing local explanations of the decisions made by Customer Decision Hub.

PEGACPDS23V1 Certified Pega Data Scientist 23 Exam Dumps

PEGACPDS23V1 Certified Pega Data Scientist 23 Exam Dumps

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