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SASInstitute A00-406 still valid dumps - in .pdf Free Demo

  • Exam Code: A00-406
  • Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
  • Last Updated: Aug 21, 2026
  • Q & A: 98 Questions and Answers
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  • Exam Code: A00-406
  • Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
  • Last Updated: Aug 21, 2026
  • Q & A: 98 Questions and Answers
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SASInstitute A00-406 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Building Models40-46%- Build regression models
- Understand supervised machine learning concepts
- Integrate custom code
- Build decision trees and ensemble models
- Use model interpretability tools
- Build neural networks and SVM models
Topic 2: Model Assessment and Deployment24-30%- Select champion models
- Deploy models into production
- Apply model assessment principles
- Evaluate and compare model performance
Topic 3: Data Sources30-36%- Reduce dimensionality
- Modify and prepare data
- Explore and understand data
- Perform variable selection
- Create a project in Model Studio

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

1. What is a data lake architecture designed to store primarily?

A) Only unstructured data in raw form
B) Highly structured data in tabular format
C) Data from a single source or department
D) All types of data, including structured and unstructured data


2. What is the primary goal of building models in data science and machine learning?

A) Feature engineering
B) Making predictions or inferences from data
C) Data cleaning
D) Data visualization


3. 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 visualize data distribution
C) To create synthetic data
D) To evaluate the model's accuracy


4. Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?

A) Min samples split
B) Max depth
C) Learning rate
D) Max features


5. In a supervised learning pipeline, what is the role of the training data set?

A) To train the machine learning model
B) To test the model's generalization capability
C) To evaluate the model's predictions
D) To validate the model's performance


Solutions:

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

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