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SASInstitute A00-406 Exam Overview:
| Certification Vendor: | SAS Institute |
|---|---|
| Exam Name: | SAS® Viya® Supervised Machine Learning Pipelines |
| Exam Number: | A00-406 |
| Real Exam Qty: | 50-55 |
| Exam Price: | $180 USD |
| Certificate Validity Period: | 5 years |
| Passing Score: | 62% |
| Exam Format: | Short answer, Multiple choice |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Recommended Training: | SAS Visual Data Mining and Machine Learning SAS Viya Machine Learning Path |
| Exam Registration: | Pearson VUE Scheduling SAS Certification Registration |
| Sample Questions: |  |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Basic knowledge of SAS Viya, statistics, and supervised machine learning concepts; experience with Model Studio recommended |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/machine-learning-using-sas-viya.html |
SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building Models | 40-46% | - Integrate custom code - Build neural networks and SVM models - Understand supervised machine learning concepts - Build decision trees and ensemble models - Build regression models - Use model interpretability tools |
| Topic 2: Model Assessment and Deployment | 24-30% | - Deploy models into production - Select champion models - Evaluate and compare model performance - Apply model assessment principles |
| Topic 3: Data Sources | 30-36% | - Reduce dimensionality - Create a project in Model Studio - Modify and prepare data - Explore and understand data - Perform variable selection |
A00-406 Exam FAQ — Simulate, Schedule, Succeed on Your Terms
The official SASInstitute SAS® Viya® Supervised Machine Learning Pipelines outline defines 3 domains. The leading three are Building Models (40-46%), Model Assessment and Deployment (24-30%), and Data Sources (30-36%). The full list is in the topics section above, and GuideTorrent's 98 practice questions cover each one.
Basic knowledge of SAS Viya, statistics, and supervised machine learning concepts; experience with Model Studio recommended Since requirements change over time, confirm the latest on the official SASInstitute exam page before scheduling.
Online proctored or onsite at Pearson VUE test centers Register for the SASInstitute SAS® Viya® Supervised Machine Learning Pipelines exam through these official channels:
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The A00-406 exam is a SASInstitute certification exam validating the SASInstitute SAS® Viya® Supervised Machine Learning Pipelines syllabus shown above. Candidates in 2026 start with GuideTorrent's 98 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
The SASInstitute SAS® Viya® Supervised Machine Learning Pipelines exam contains 50-55 to complete within 90 minutes. Timed simulation in the GuideTorrent Desktop Test Engine teaches that rhythm before exam day does.
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The SASInstitute SAS® Viya® Supervised Machine Learning Pipelines exam requires 62% to pass, and registration costs $180 USD. A failed attempt means paying the same fee again — a readiness check with the GuideTorrent engines before booking is the cheaper option.
SASInstitute recommends these training resources for the SASInstitute SAS® Viya® Supervised Machine Learning Pipelines exam:
Follow the training with steady self-testing — the 98 practice questions from GuideTorrent help you apply theory and fill any gaps the training leaves.
Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 98 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
What is the purpose of cross-entropy loss in machine learning, especially in the context of classification?
- A. To calculate the mean squared error of a regression model
- B. To measure the dissimilarity between predicted and actual class probabilities
- C. To quantify the variance of a model
- D. To evaluate feature importance
Correct Answer: B 🗳️
Which machine learning technique is typically used for building a model to predict a numeric target variable?
- A. Regression
- B. Clustering
- C. Classification
- D. Dimensionality reduction
Correct Answer: A 🗳️
In the context of model building, what is the purpose of hyperparameter tuning?
- A. Optimizing the model's hyperparameters for better performance
- B. Visualizing data
- C. Training the model
- D. Selecting the most important features
Correct Answer: A 🗳️
What does "data lineage" refer to in the context of data source management?
- A. The history of data transformation processes
- B. The security protocols for data access
- C. The structure of a relational database
- D. The physical location of data storage
Correct Answer: A 🗳️
What is the primary goal of A/B testing in the context of model deployment?
- A. To create synthetic data
- B. To evaluate the model's accuracy
- C. To assess data quality
- D. To compare two different versions of a model or strategy to determine which performs better
Correct Answer: D 🗳️
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