PEGAPCDS80V1_2019 exam dumps

Pegasystems PEGAPCDS80V1_2019 Value Package

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  • Exam Code: PEGAPCDS80V1_2019
  • Exam Name: Pega Certified Data Scientist (PCDS) 80V1 2019
  • No. of Questions: 0 Questions and Answers
  • Updated: Sep 01, 2026

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To prepare for the Pega Certified Data Scientist (PCDS) 80V1 2019 certification exam, candidates are encouraged to attend Pega's official training courses, which provide a comprehensive overview of Pega's data analytics framework and cover all the topics included in the exam. Additionally, candidates can access a range of online resources, such as practice exams, study guides, and forums, to help them prepare for the exam and gain a deeper understanding of Pega's data analytics tools and techniques.

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Pegasystems PEGAPCDS80V1_2019 (Pega Certified Data Scientist (PCDS) 80V1 2019) Certification Exam is designed to test individuals on their expertise in the Pega Platform's data science capabilities. PEGAPCDS80V1_2019 exam measures a candidate's ability to use predictive analytics and machine learning techniques to solve business problems using Pega's Decision Management and Core Engine capabilities.

Pegasystems PEGAPCDS80V1_2019 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Text Analytics10%- Text Analysis Capabilities
  • 1. Sentiment analysis
  • 2. Text categorization
  • 3. Email and customer interaction analysis
Topic 2: Pega Decisioning Foundation10%- Introduction to Pega Customer Decision Hub
  • 1. Next-Best-Action concepts
  • 2. Customer engagement framework
  • 3. Decision management architecture
Topic 3: Predictive Analytics30%- Predictive Models
  • 1. Model creation and configuration
  • 2. Predictor analysis
  • 3. Model deployment and monitoring
  • 4. Model performance evaluation
Topic 4: Adaptive Analytics30%- Adaptive Models
  • 1. Adaptive learning concepts
  • 2. Response propensity analysis
  • 3. Monitoring adaptive performance
  • 4. Real-time model updates
Topic 5: Decision Strategies20%- Strategy Design and Execution
  • 1. Filtering and prioritization
  • 2. Strategy components and flows
  • 3. Customer action selection
  • 4. Decision arbitration

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