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

  • Exam Code: A00-406
  • Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
  • Updated: Sep 17, 2026

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About SASInstitute A00-406 Exam

Everyone wants to achieve something in their own field, and for IT workers the SASInstitute SAS® Viya® Supervised Machine Learning Pipelines is a key that unlocks that ambition. TorrentVCE helps you turn it with 98 expert-verified practice questions for the A00-406 exam, current throughout 2026.

SASInstitute A00-406 Exam Overview:

Certification Vendor:SAS Institute
Exam Name:SAS® Viya® Supervised Machine Learning Pipelines (SAS Certified Specialist: Machine Learning Using SAS Viya)
Exam Number:A00-406
Certificate Validity Period:5 years
Exam Format:Multiple choice, Short answer
Real Exam Qty:50-55
Passing Score:62%
Available Languages:English
Exam Price:USD 180
Related Certifications:SAS Certified Specialist: Forecasting and Optimization Using SAS Viya
SAS Certified Associate: Applied Statistics for Machine Learning
SAS Certified Specialist: Natural Language Processing and Computer Vision Using SAS Viya
Exam Duration:90 minutes
Sample Questions:Free Download A00-406 Exam PDF Torrent
Exam Way:Administered by SAS and Pearson VUE (online or test center)
Pre Condition:Familiarity with SAS Visual Data Mining and Machine Learning software; basic understanding of statistics recommended
Official Syllabus URL:https://www.sas.com/en_gb/certification/credentials/advanced-analytics/machine-learning-using-sas-viya.html

SASInstitute A00-406 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model Assessment and Deployment24-30%- Deploying models into production
- Assessing model performance (metrics, ROC curves, confusion matrices)
Topic 2: Data Sources30-36%- Dimensionality reduction and feature engineering
- Exploring and modifying data
- Importing and preparing data
Topic 3: Building Models40-46%- Supervised model creation (decision trees, ensembles, SVM, neural networks)
- Model comparison and selection

SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Questions, Answered Carefully

Per the latest exam information, the A00-406 exam presents 50-55 questions in 90 minutes minutes. Knowing the format precisely removes one major source of exam-day anxiety.

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The SASInstitute SAS® Viya® Supervised Machine Learning Pipelines blueprint covers these core domains:

  • Data Sources (30-36%)
  • Model Assessment and Deployment (24-30%)
  • Building Models (40-46%)

SASInstitute publishes these prerequisites for the SASInstitute SAS® Viya® Supervised Machine Learning Pipelines: Familiarity with SAS Visual Data Mining and Machine Learning software; basic understanding of statistics recommended.

Check the authoritative wording on the official certification page before registering.

At present, passing the A00-406 exam requires 62%, and the registration fee is USD 180. Both are set by SASInstitute and can change — confirm them on the official site when you book.

Written, clear, and honored. If you fail the corresponding exam within 60 days of purchase, send us a scanned copy of your enrollment slip and your official Score Report PDF within two days of the exam date; verified claims are refunded in full within seven days. Exclusions: exams taken within three days of purchase, candidate names that differ from the payer, and free or expired products. If you prefer, exchange your product for two others of equal value at no charge.

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

Question #1

Which type of data source typically stores structured data in a tabular format?

  • A. NoSQL databases
  • B. Text documents
  • C. APIs
  • D. Relational databases
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Question #2

Which data source typically provides access to real-time financial market data?

  • A. Social media platforms
  • B. Stock market APIs
  • C. Weather stations
  • D. Online news websites
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #3

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

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

Correct Answer: A  🗳️

Question #4

Which of the following metrics is commonly used to evaluate the performance of a binary classification model in a machine learning pipeline?

  • A. Mean Absolute Error (MAE)
  • B. R-squared
  • C. Root Mean Squared Error (RMSE)
  • D. Accuracy
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Question #5

Which algorithm is commonly used for decision-making tasks in classification models?

  • A. K-Means
  • B. Principal Component Analysis (PCA)
  • C. Decision Trees
  • D. Linear Regression
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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