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Pegasystems PEGACPDS88V1 Exam Questions
- Topic 1: AI for Customer Decision Hub: This PEGACPDS88V1 exam topic assesses the proficiency of data scientists in leveraging AI within the Customer Decision Hub. Data scientists will need to demonstrate their understanding of how to utilize predictions and insights to enhance decision-making processes.
- Topic 2: Adaptive Analytics: The knowledge of data scientists about Adaptive Analytics will be evaluated in this portion. It focuses on creating, monitoring, and exporting adaptive models. Expect questions on how to effectively implement and oversee these models to ensure accurate and actionable analytics for dynamic environments.
- Topic 3: Predictive Analytics: In this Pegasystems Certified Pega Data Scientist exam topic, data scientists will be tested on creating predictions, developing predictive models, and understanding MLOps practices. Their ability to harness predictive analytics to forecast outcomes and manage model lifecycles will be critical.
- Topic 4: Prediction Patterns: This PEGACPDS88V1 topic examines the skills of data scientists in creating and interpreting decision strategies and defining prediction patterns. They need to show their capability to develop and apply prediction patterns to optimize decision-making processes.
- Topic 5: Governance: Understanding the principles of governance within Pegasystems framework is the key in this topic. Aspiring data scientists will be tested on implementing and managing governance structures effectively.
- Topic 6: Pega NLP: This Pegasystems Certified Pega Data Scientist exam topic focuses on the ability of data scientists to use Pega Natural Language Processing tools. Data scientists will need to show expertise in text analytics for email routing and entity extraction with chatbots. This knowledge is essential for leveraging NLP to enhance customer interactions and automate processes.
- Topic 7: Pega Process AI: Here, the skills of data scientists in predicting fraud and case completion using Pega Process AI will be evaluated. Demonstrating the ability to apply AI for predicting these outcomes effectively will showcase the capacity of a data scientist to utilize AI for operational improvements and risk management.
Free Pegasystems PEGACPDS88V1 Exam Actual Questions
Note: Premium Questions for PEGACPDS88V1 were last updated On Aug. 18, 2025 (see below)
The adaptive model component in a decision strategy computes
The adaptive model component in a decision strategy computes a propensity value for each action. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100. Reference: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-adaptivemodel/main.htm
In a decision strategy, the Adaptive Model decision component belongs the
In a decision strategy, the Adaptive Model decision component belongs to the Decision Analytics category. This category contains components that use advanced analytics techniques, such as adaptive models, predictive models, text analytics models, etc., to make predictions or recommendations. Reference: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analytics-components
Which property is automatically recomputed for each decision component?
The rank property is automatically recomputed for each decision component. It indicates the order in which the actions are presented to the customer, based on their priority and propensity. Reference: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/ranking-actions
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?
to create a prediction that calculates the probability that a claim is fraudulent, you need to createa case management prediction. This type of prediction allows you to use predictive models built on external platforms such as H2O.ai and apply them to case types in Pega Process AI. You can then use the prediction outcome in a decision step to route claims based on their fraud risk.
https://academy.pega.com/challenge/creating-fraud-prediction/v3
Prediction Studio supports keyword-based topic detection, model-based topic detection and the combination of these. When using machine learning,
When using machine learning, the Must keywords function aspositive features.
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