SASInstitute A00-402 : SAS Viya 3.5 Supervised Machine Learning Pipelines

A00-402 real exams

Exam Code: A00-402

Exam Name: SAS Viya 3.5 Supervised Machine Learning Pipelines

Updated: Sep 11, 2026

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SASInstitute A00-402: SAS Viya 3.5 Supervised Machine Learning Pipelines exam is a certification test designed for professionals in the field of data science and machine learning. A00-402 exam is intended to measure the candidate's knowledge and skills in supervised machine learning pipelines using SAS Viya 3.5. SAS Viya 3.5 Supervised Machine Learning Pipelines certification is globally recognized and is highly valued by employers.

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SASInstitute A00-402: SAS Viya 3.5 Supervised Machine Learning Pipelines Exam is an important certification exam for professionals who want to demonstrate their expertise in building effective machine learning pipelines using SAS Viya. A00-402 exam covers a range of topics related to supervised machine learning, including data preparation, data exploration, feature engineering, model building, and model deployment. Candidates who pass the exam will receive the SAS Certified Professional: Machine Learning Using SAS Viya 3.5 certification, which is recognized by employers around the world.

Reference: https://www.sas.com/en_us/certification/credentials/advanced-analytics/machine-learning-specialist.html

SASInstitute A00-402 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Preparation for Machine Learning- Feature engineering
  • 1. Feature transformation techniques
    • 2. Variable selection methods
      - Data cleansing and preprocessing in SAS Viya
      • 1. Encoding categorical variables
        • 2. Handling missing values
          Topic 2: Supervised Learning Algorithms- Tree-based models
          • 1. Gradient boosting
            • 2. Random forest
              • 3. Decision trees
                - Regression and classification models
                • 1. Logistic regression
                  • 2. Linear regression
                    Topic 3: Model Assessment and Deployment- Deployment in SAS Viya
                    • 1. Model publishing
                      • 2. Scoring pipelines
                        - Model evaluation
                        • 1. ROC and gain charts
                          • 2. Confusion matrix interpretation
                            Topic 4: Model Training and Optimization- Model training workflows in SAS Viya Model Studio
                            • 1. Pipeline creation and management
                              • 2. Hyperparameter tuning
                                - Model validation
                                • 1. Cross-validation techniques
                                  • 2. Performance metrics (AUC, accuracy, lift)

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