As 2026 continues, GuideTorrent keeps its A00-401 commitments simple — verified answers in the SASInstitute SAS Viya 3.4 Supervised Machine Learning Pipelines bank, 365 days of free updates, 0 practice questions for the A00-401 exam, and support that works through weekends and official holidays alike.
SASInstitute A00-401 Exam Overview:
| Certification Vendor: | SAS Institute |
|---|---|
| Exam Name: | SAS Viya 3.4 Supervised Machine Learning Pipelines |
| Exam Number: | A00-401 |
| Passing Score: | 70% |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Certificate Validity Period: | 5 years |
| Exam Format: | Short Answer, Multiple Choice |
| Real Exam Qty: | 50-55 |
| Exam Price: | $180 USD |
| Related Certifications: | SAS Certified Professional: Artificial Intelligence and Machine Learning |
| Recommended Training: | Official Exam Content Guide Machine Learning Using SAS Viya |
| Exam Registration: | SAS Certification Registration Pearson VUE Registration |
| Exam Way: | In-person at Pearson VUE test centers or online proctored |
| Pre Condition: | Basic knowledge of statistics and predictive modeling; familiarity with SAS Viya and Model Studio recommended |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/machine-learning-specialist-34.html |
SASInstitute A00-401 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Assessment and Deployment | 20% | - Export score code - Model comparison in Model Studio - Register and publish models - Fit statistics, ROC, Lift and comparison reports - Model evaluation principles |
| Topic 2: Data Sources | 30% | - Reduce dimensionality and handle redundancy - Explore and modify data - Create a project in Model Studio - Use Variable Selection node - Understand variable types and measurement scales |
| Topic 3: Building Models | 50% | - Supervised learning concepts - Incorporate external and custom code - Autotuning and regularization - Neural networks - Support vector machines - Decision trees and ensemble models - Regression models |
SASInstitute SAS Viya 3.4 Supervised Machine Learning Pipelines Details Every Buyer Should Read
- Model Assessment and Deployment (20%)
- Building Models (50%)
- Data Sources (30%)


