SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 Practice Exam

The SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 certification is designed for professionals who wish to validate their skills in creating predictive models and employing statistical techniques to derive actionable insights from data using SAS Enterprise Miner. The certification assess your skills in using SAS tools to build, validate, and deploy models. The certification attests to your expertise in predictive modeling especially suitable for data analysts, data scientists, and business intelligence professionals .
Why is SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 important?

• Validates expertise in predictive modeling using SAS Enterprise Miner.
• Enhances career opportunities in data analytics and predictive analytics roles.
• Demonstrates proficiency in applying statistical techniques to real-world data.
• Recognizes skills in building and validating predictive models.
• Provides a competitive edge in industries focused on data-driven decision-making.

Who should take the SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 Exam?

• Data Analyst
• Predictive Modeler
• Data Scientist
• Business Analyst
• Analytics Consultant
• Market Research Analyst

Skills Evaluated

Candidates taking the certification exam on the SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 is evaluated for the following skills:

• Ability to use SAS Enterprise Miner for data exploration and preprocessing.
• Proficiency in building, assessing, and validating predictive models.
• Knowledge of statistical methods and algorithms used in predictive analytics.
• Skills in interpreting model results and communicating findings.
• Understanding of data mining techniques and model deployment strategies.

SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 Certification Course Outline
The SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 Certification covers the following topics -

Module 1. Data Sources

• Create data sources from SAS tables in Enterprise Miner

• Explore and assess data sources

• Modify source data

• Prepare data to be submitted to a predictive model

Module 2. Developing Predictive Models

• Explain key predictive modeling terms and concepts

• Develop predictive models using decision trees

• Develop predictive models using regression

• Develop predictive models using neural networks

Module 3. Predictive Model Assessment and Implementation

• Use the correct fit statistic for different prediction types

• Use decision processing to adjust for oversampling (separate sampling)

• Use profit/loss information to assess model performance

• Compare models with the MODEL COMPARISON node

• Score data sets within Enterprise Miner

Module 4. Pattern Analysis

• Recognize clusters of similar data with the CLUSTER and SEGMENT PROFILE nodes

• Perform association and sequence analysis (market basket analysis)