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| Certification Vendor: | SAS Institute |
| Exam Name: | SAS Advanced Predictive Modeling |
| Exam Number: | A00-225 |
| Exam Duration: | 110 minutes |
| Passing Score: | 67% |
| Available Languages: | English |
| Real Exam Qty: | 50-55 |
| Exam Price: | $180 USD |
| Exam Format: | Multiple-choice, Short-answer, Interactive performance-based |
| Related Certifications: | SAS Certified Advanced Analytics Professional Using SAS 9 |
| Certificate Validity Period: | 3 years |
| Recommended Training: | Neural Network Modeling Predictive Modeling Using Logistic Regression Data Mining Techniques: Predictive Analytics on Big Data Using SAS to Put Open Source Models into Production |
| Exam Registration: | Pearson VUE Registration SAS Official Exam Page |
| Exam Way: | Online proctored or onsite testing at Pearson VUE centers |
| Pre Condition: | Recommended: SAS Certified Statistical Business Analyst or equivalent experience; hands-on experience with SAS/STAT, SAS Enterprise Miner, SAS Visual Analytics |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/advanced-analytics-professional/advanced-predictive-modeling-exam.html |
The cost of SAS Institute A00-225 Exam is $180 USD.
#What is the test format of SAS Institute A00-225 Exam?
| Section | Weight | Objectives |
|---|---|---|
| Logistic Regression | 30% | - Model building and variable selection - Interpretation of results - Using SAS/STAT and SAS Enterprise Miner - Model assessment and validation |
| Predictive Analytics on Big Data | 40% | - SAS LASR Analytic Server and SAS Visual Analytics - Scaling models for large datasets - Working with distributed and in-memory data - High-performance modeling techniques |
| Neural Networks | 20% | - Training and tuning neural models - Neural network architecture design - Model evaluation and performance - Implementation in SAS Enterprise Miner |
| Open Source Models in SAS | 10% | - Integrating open source code with SAS - Deploying Python/R models in SAS environment - Productionalization of hybrid models |
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