Pegasystems Pega Certified Data Scientist (PCDS) 80V1 2019 : PEGAPCDS80V1_2019

PEGAPCDS80V1_2019 real exams

Exam Code: PEGAPCDS80V1_2019

Exam Name: Pega Certified Data Scientist (PCDS) 80V1 2019

Updated: Sep 10, 2026

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The Pega Certified Data Scientist (PCDS) 80V1 2019 Certification Exam covers a wide range of topics, including data preparation, data modeling, predictive analytics, decisioning, and machine learning. Candidates will need to have a solid understanding of data science principles, as well as experience working with Pega's tools, in order to pass the exam.

Pegasystems developed the certification exam to meet the increasing demand for talented data scientists with advanced skills in using Pega's technology. Pega Certified Data Scientist (PCDS) 80V1 2019 certification serves as a valuable addition to the resumes of candidates who possess strong analytical and technical skills and are looking for career advancement opportunities in the field of data science.

To prepare for the Pegasystems PEGAPCDS80V1_2019 certification exam, candidates are encouraged to take Pega's data science courses and complete the certification exam practice tests. These courses are designed to provide hands-on experience with Pega's data science tools and help candidates prepare for the certification exam. Additionally, candidates can also benefit from studying data science concepts and theories from other sources to gain a deeper understanding of the field.

Pegasystems PEGAPCDS80V1_2019 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Text and Predictive Analytics Tools10%- Text analytics configuration
- Predictive analyzer usage
Topic 2: Decision Strategy Design25%- Decision strategy canvas
- Simulation and validation
- Eligibility and arbitration logic
Topic 3: Adaptive Model Management25%- Adaptive model configuration
- Model performance monitoring
- Model refresh and retraining
Topic 4: Pega Customer Decision Hub Implementation20%- Real-time decisioning
- Integration with predictive models
- Outcome analysis and reporting
Topic 5: Predictive Analytics Fundamentals20%- Statistical modeling concepts
- Predictive model types
- Data preparation and feature engineering

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