Pegasystems Pega Certified Data Scientist (PCDS) 80V1 2020 : PEGAPCDS80V1_2020

  • Exam Code: PEGAPCDS80V1_2020
  • Exam Name: Pega Certified Data Scientist (PCDS) 80V1 2020
  • Updated: Jul 22, 2026     Q & A: 50 Questions and Answers

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About Pegasystems PEGAPCDS80V1_2020 Exam

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The Pega Certified Data Scientist (PCDS) 80V1 2020 certification exam is an excellent opportunity for data scientists and machine learning engineers to enhance their skills and demonstrate their expertise in using the Pega Platform for predictive analytics. It is a rigorous exam that requires a significant investment of time and effort, but the benefits of certification can be significant, including increased job opportunities and higher salaries.

Pegasystems PEGAPCDS80V1_2020 exam is designed for professionals seeking to become certified data scientists in the Pega platform. Pega Certified Data Scientist (PCDS) 80V1 2020 certification verifies the candidate's knowledge of Pega's in-built machine learning algorithms, big data analytics, predictive and prescriptive analytics, and customer decision hub (CDH) management. Utilizing these tools, certified data scientists can design, analyze and deploy machine learning models, optimize CDH operations, and deliver data-driven insights.

Reference: https://academy.pega.com/exam/pega-certified-data-scientist

The Pega Certified Data Scientist (PCDS) 80V1 2020 certification is highly valued in the industry and can lead to significant career opportunities. It demonstrates the candidate's proficiency in data science and analytics, as well as their ability to apply these concepts in the Pega platform. Overall, the Pega Certified Data Scientist (PCDS) 80V1 2020 exam is a challenging and rewarding certification that can help professionals stay ahead in the rapidly evolving field of data science.

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Pegasystems PEGAPCDS80V1_2020 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Adaptive Analytics34%- Quantifying business impact of machine learning
- Real-time adaptive learning
- Monitoring and tuning adaptive models
- Adaptive model fundamentals
Topic 2: Text Analytics10%- Applying text analytics in decision strategies
- Use cases such as email routing and interaction analysis
- Text analytics concepts and NLP basics
Topic 3: Decision Strategies26%- Arbitrating and prioritizing customer actions
- Building and simulating decision strategies
- Understanding decisioning logic
Topic 4: Predictive Analytics22%- Fundamentals of predictive models
- Using Prediction Studio
- Integrating third-party predictive models
- Building and evaluating predictive models
Topic 5: Next-Best-Action8%- Introduction to Pega for data scientists
- Next-Best-Action paradigm concepts

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