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The PEGAPCDS80V1_2019 exam is comprehensive and challenging, with 65 multiple-choice questions that must be answered within 90 minutes. PEGAPCDS80V1_2019 exam has a passing score of 65%, and candidates need to demonstrate proficiency in data science concepts and techniques using Pega's platform. Pega Certified Data Scientist (PCDS) 80V1 2019 certification credential, once obtained, validates the holder's ability to utilize Pega's data science capabilities to solve complex business challenges. Pega certification is widely recognized by employers worldwide and has become a valuable resource for individuals to advance their careers in data science.

The PCDS 80V1 2019 exam evaluates the skills of data scientists in various areas, including data analysis and visualization, data preparation and cleansing, machine learning, and statistical analysis. Passing this certification exam indicates that the individual has expert knowledge in the latest techniques and tools for data science and can apply them efficiently to improve business outcomes.

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Those who pass the PEGAPCDS80V1_2019 exam earn the title of Pega Certified Data Scientist (PCDS) and prove that they possess the necessary skills to manage and analyze data. PEGAPCDS80V1_2019 exam assesses candidates' ability to create predictive models, perform data analysis, and use various data mining techniques to achieve business objectives. These skills are relevant to different industries such as healthcare, financial services, insurance, and telecommunications.

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Pegasystems PEGAPCDS80V1_2019 is a certification exam that tests the skills and knowledge of individuals seeking to become Pega Certified Data Scientists (PCDS) in the year 2019. As technology evolves, the demand for data scientists increases, and Pegasystems has established this certification to ensure the industry standards are met by the professionals working in the field of data science.

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Pegasystems PEGAPCDS80V1_2019 Exam Syllabus Topics:

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

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