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The PEGACPDS88V1 certification is an excellent way for data scientists to demonstrate their expertise in the Pega platform. The certification is recognized globally and can help individuals advance their careers. Moreover, the certification can help organizations identify individuals with the skills and knowledge necessary to tackle complex data science problems and provide them with the tools to make data-driven decisions.
Pegasystems PEGACPDS88V1: Certified Pega Data Scientist 88V1 is an exam that has been designed for professionals who want to prove their expertise in data science for Pega applications. The exam is intended for data scientists who work with Pega applications to analyze, predict, and optimize business outcomes. Passing the exam demonstrates the candidate's proficiency in Pega's data science capabilities and their ability to use these capabilities to deliver value to businesses.
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The Pegasystems PEGACPDS88V1 exam is designed for individuals who want to become certified Pega Data Scientists. Pega is a leading provider of business process management (BPM) software solutions that help organizations streamline their operations and improve customer engagement. The PEGACPDS88V1 exam tests candidates on their ability to use Pega's data science tools and techniques to solve real-world business problems.
Pegasystems Certified Pega Data Scientist 88V1 Sample Questions (Q125-Q130):NEW QUESTION # 125
Pega machine learning supports the creation of which two distinct types of predictive models? (Choose Two)
Answer: B,C
Explanation:
Explanation
Pega machine learning supports the creation of two distinct types of predictive models: categorical and binary.
Categorical models predict the outcome of a variable that can have multiple values, such as product category or customer segment. Binary models predict the outcome of a variable that can have only two values, such as yes or no, accept or reject, etc. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 126
Two results of an adaptive model are
Answer: B
Explanation:
Explanation
Two results of an adaptive model are propensity and performance. Propensity is the probability that the customer will accept or respond to an offer. Performance is a measure of how well the adaptive model predicts customer behavior over time. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 127
In a decision strategy, the Adaptive Model decision component belongs the
Answer: B
Explanation:
Explanation
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. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analyt
NEW QUESTION # 128
Which statement about predictive models is true?
Answer: C
Explanation:
Explanation
Predictive models need historical data to be created. Predictive models are statistical models that use historical data to learn patterns and trends and make predictions for future outcomes. Predictive models can be built with Pega machine learning or imported from third-party tools such as PMML or H2O. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 129
A best practice in data science is to use a control group. What business metric is supported by this practice?
Answer: B
Explanation:
Explanation
The lift that the prediction generates Reference:
Using a control group is a best practice in data science that supports the business metric of the lift that the prediction generates.
NEW QUESTION # 130
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