PEGAPCDS86V1 Pega Certified Data Scientist (PCDS) 86V1 exam is new launched for Pega Certified Data Scientist (PCDS) certification, PEGAPCDS85V1 exam is still valid to take in pearson vue at present, you can take either PEGAPCDS86V1 or PEGAPCDS85V1 exams for your PCDS certification path. PassQuestion team new released PCDS Version 8.6 PEGAPCDS86V1 Exam Questions to help you achieve the best results and clear the Pega Certified Data Scientist (PCDS) 86V1 exam on the first attempt.If you are using our detailed PCDS Version 8.6 PEGAPCDS86V1 Exam Questions, then it will help you improve your preparation level. Moreover, you can will be able to clear your concepts about the subject with the help of these files.

PCDS Version 8.6 Certification Overview

The Pega Certified Data Scientist (PCDS) certification exam is for data scientists who wish to acquaint themselves with the skills and knowledge needed to successfully apply AI in Pega Customer Decision Hub and Pega Customer Service. The PCDS certification ensures you become familiar with Pega’s next-best-action paradigm, have the skills to build and simulate decision strategies and use predictive, adaptive and text analytics in those strategies.

The PCDS Version 8.6 exam includes multiple choice and scenario questions. If multiple answers are required, the text states how many responses are needed.

PCDS (Pega Certified Data Scientist) Exam Path

The Pega Certified Data Scientist (PCDS) certification is for data scientists who wish to acquaint themselves with the skills and knowledge needed to successfully apply AI in Pega Customer Decision Hub and Pega Customer Service.

PCDS Version 8.6 Certification Path:

Pega Data Scientist mission
Exam Code: PEGAPCDS86V1
Type of Exam: 50 question exam
Length: 90 minutes
Passing Grade: 70% 

PCDS Version 8.5 Certification Path:

Pega Data Scientist mission
Exam Code: PEGAPCDS85V1
Type of Exam: 50 question exam
Length: 90 minutes
Passing Grade: 70%

PCDS Version 8.6 Exam Topics

Next-Best-Action (4%)

Introducing Pega to data scientists

Decision Strategies (16%)

Understanding decisioning logic
Arbitrating between customer actions

Predictive Analytics (32%)

Building predictive models
Using third party predictive models

Adaptive Analytics (36%)

Predicting customer behavior using real-time data
Demonstrating adaptive learning
Quantifying the impact of machine learning

Text Analytics (12%)

Utilizing text analytics for email routing