A00-406 exam dumps

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  • Exam Code: A00-406
  • Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
  • No. of Questions: 98 Questions and Answers
  • Updated: Jul 31, 2026

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  • Total Questions: 98
  • Updated on: Jul 31, 2026
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  • Total Questions: 98
  • Updated on: Jul 31, 2026
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  • Total Questions: 98
  • Updated on: Jul 31, 2026
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SASInstitute A00-406 Exam Syllabus Topics:

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

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

1. In reinforcement learning, what is the "reward signal"?

A) The accuracy of the model's predictions
B) The final prediction made by the model
C) A numerical value that indicates the performance of an action taken by the agent
D) A regularization parameter


2. What is the primary purpose of "continuous integration and continuous deployment" (CI/CD) in the context of model deployment?

A) To automate the testing, integration, and deployment of new model versions
B) To evaluate the model's accuracy
C) To visualize data distribution
D) To create synthetic data


3. In reinforcement learning, what is the agent's objective?

A) To generate synthetic data
B) To make predictions
C) To maximize a cumulative reward over time
D) To learn from labeled data


4. What is "model retraining" in the context of model deployment?

A) The process of building the initial model
B) Periodically updating and improving a deployed model with new data
C) The process of feature selection
D) The process of data preprocessing


5. What is the primary purpose of a supervised machine learning pipeline in SAS Viya?

A) Data preprocessing and cleaning
B) Data storage and retrieval
C) Data visualization
D) Model training and evaluation


Solutions:

Question # 1
Answer: C
Question # 2
Answer: A
Question # 3
Answer: C
Question # 4
Answer: B
Question # 5
Answer: D


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