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Pegasystems PEGAPCDS87V1 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Understanding | - Data sources and data types in Pega - Exploratory data analysis concepts |
| Topic 2: Data Preparation | - Feature engineering for predictive models - Data cleansing and transformation |
| Topic 3: Pega Decisioning and AI Integration | - Adaptive models and decision strategies - Embedding predictive analytics in Pega applications |
| Topic 4: Predictive Analytics | - Model training and evaluation - Predictive model types in Pega (classification, regression) |
| Topic 5: Data Sets and Integration | - External data integration with Pega platform - Data flows and dataset configuration |
Pegasystems Pega Certified Data Scientist (PCDS) 87V1 Sample Questions:
The Adaptive Model component in a strategy computes
- A. a propensity value for each action
- B. a unique accept rate for each action
- C. a single propensity value for all actions
- D. a single accept rate for all actions
A company wants to simulate decisions that requires large amounts of data. However, the organisation's live data is inaccessible. Your advice is to use a Monte Carlo data set.
The Monte Carlo method________________
- A. makes the organisation's live data accessible
- B. combines external data sets into a larger data set
- C. generates data that the company can use as input for adaptive decisioning
- D. enables the company to generate random data for most of its application needs
The Prioritize component always outputs
- A. top 1 offer
- B. all eligible offers
- C. top 3 offers
- D. on arbitrary number of offers
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
A telecom company is interested in improving customer engagement on social media. However, there are hundreds of relevant messages posted every day, and it is not practical for customer service representatives (CSRs) to review and respond to all messages. Instead, CSRs should focus on negative messages.
What do you need to analyze the incoming messages?
- A. Adaptive model
- B. Text categorization model
- C. Text extraction model
- D. Predictive model
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