SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406

  • Exam Code: A00-406
  • Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
  • Updated: Oct 02, 2026
  • Q & A: 98 Questions and Answers

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About SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406 Exam

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SASInstitute A00-406 Exam Syllabus Topics:

SectionObjectives
Model Evaluation and Deployment- Model deployment
  • 1. Model governance
    • 2. Scoring models in SAS Viya
      - Model assessment metrics
      • 1. Accuracy, precision, recall
        • 2. ROC and lift charts
          Supervised Machine Learning Models- Model selection techniques
          • 1. Cross-validation
            • 2. Performance comparison
              - Regression and classification models
              • 1. Linear and logistic regression
                • 2. Tree-based models
                  Machine Learning Pipelines in SAS Viya- Pipeline construction
                  • 1. Node-based pipeline design
                    • 2. Model Studio workflows
                      - Model tuning and optimization
                      • 1. Automated machine learning (AutoML)
                        • 2. Hyperparameter tuning
                          Data Preparation for Machine Learning- Data cleaning and preprocessing
                          • 1. Handling missing values
                            • 2. Outlier detection and treatment
                              - Feature engineering
                              • 1. Variable transformation
                                • 2. Encoding categorical variables

                                  SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

                                  Question #1

                                  What is the primary purpose of model deployment in the context of data science and machine learning?

                                  • A. Making the model available for use in real-world applications
                                  • B. Data preprocessing
                                  • C. Model building
                                  • D. Model evaluation
                                  Reveal Solution  Discussion  0

                                  Correct Answer: A  🗳️

                                  Question #2

                                  When deploying a machine learning model, what is "model drift"?

                                  • A. A change in the distribution of the input data or target variable over time
                                  • B. The process of feature extraction
                                  • C. A measure of feature importance
                                  • D. A sudden increase in the model's accuracy
                                  Reveal Solution  Discussion  0

                                  Correct Answer: A  🗳️

                                  Question #3

                                  What is the main goal of data preprocessing in a machine learning pipeline?

                                  • A. To remove irrelevant features
                                  • B. To visualize the data
                                  • C. To train the model
                                  • D. To prepare the data for analysis and modeling
                                  Reveal Solution  Discussion  0

                                  Correct Answer: D  🗳️

                                  Question #4

                                  In a machine learning pipeline, what is the purpose of cross-validation?

                                  • A. To evaluate the model's performance on new data
                                  • B. To visualize the data distribution
                                  • C. To split the dataset into training and testing sets
                                  • D. To train multiple models on different subsets of the data to assess generalization
                                  Reveal Solution  Discussion  0

                                  Correct Answer: D  🗳️

                                  Question #5

                                  What is the primary role of a data warehouse in an organization?

                                  • A. Data transformation and cleaning
                                  • B. Real-time data analysis
                                  • C. Long-term data storage and analysis
                                  • D. Data exploration and visualization
                                  Reveal Solution  Discussion  0

                                  Correct Answer: C  🗳️

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