Pegasystems is a reputable software company that is recognized for its innovative solutions in the field of customer relationship management (CRM) and business process management (BPM). The company offers a range of certifications that are designed to validate the skills and expertise of IT professionals. One of the most popular certifications offered by Pegasystems is the Pega Certified Data Scientist (PCDS) 80V1 2020 exam.
The PEGAPCDS80V1_2020 exam is a rigorous and challenging exam that requires a thorough understanding of the Pega platform and its various features. PEGAPCDS80V1_2020 exam consists of multiple-choice questions and requires the candidate to complete a series of tasks that demonstrate their ability to use the Pega platform to analyze and interpret data. PEGAPCDS80V1_2020 exam is designed to test the candidate's ability to think critically and to apply their knowledge of data analysis and modeling to real-world business problems.
The Pega Certified Data Scientist (PCDS) 80V1 2020 certification exam is a computer-based exam that consists of 60 multiple-choice questions. Candidates have 90 minutes to complete the exam and must score at least 65% to pass. PEGAPCDS80V1_2020 exam is administered by Pearson VUE and can be taken at any Pearson VUE testing center worldwide. Pega Certified Data Scientist (PCDS) 80V1 2020 certification is valid for two years and can be renewed by passing a recertification exam.
Reference: https://academy.pega.com/exam/pega-certified-data-scientist
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Pegasystems PEGAPCDS80V1_2020 is a certification exam that is designed to validate the knowledge and skills of a data scientist in the Pega Platform. PEGAPCDS80V1_2020 exam is intended for professionals who want to demonstrate their expertise in designing and building predictive models and analytics solutions using the Pega Platform. Pega Certified Data Scientist (PCDS) 80V1 2020 exam is an ideal certification for professionals who wish to gain recognition in the field of data science.
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Pegasystems PEGAPCDS80V1_2020 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Predictive Analytics | 32% | - Building predictive models - Using third-party predictive models |
| Next-Best-Action | 4% | - Introduction to Pega for data scientists |
| Decision Strategies | 16% | - Decisioning logic and hierarchy
|
| Adaptive Analytics | 36% | - Monitoring model performance - Adaptive model creation and learning - Quantifying ML impact |
| Text Analytics | 12% | - Sentiment and text classification use cases |








