SASInstitute A00-401 : SAS Viya 3.4 Supervised Machine Learning Pipelines

A00-401 real exams

Exam Code: A00-401

Exam Name: SAS Viya 3.4 Supervised Machine Learning Pipelines

Updated: Jul 23, 2026

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About SASInstitute A00-401 Exam

SASInstitute A00-401 certification exam is a rigorous and comprehensive test of a candidate's ability to use SAS Viya 3.4 to develop and deploy supervised machine learning pipelines. It is an excellent opportunity for data science professionals to demonstrate their skills and expertise in this critical area of data analytics. By earning the certification, candidates can position themselves for success in a rapidly growing and evolving field.

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SASInstitute A00-401 exam is designed for professionals who want to demonstrate their expertise in building and deploying machine learning models using the SAS Viya platform. SAS Viya 3.4 Supervised Machine Learning Pipelines certification is an industry-recognized credential that validates a candidate's knowledge and skills in designing, building, and deploying supervised machine learning pipelines using SAS Viya 3.4.

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The SAS Viya 3.4 Supervised Machine Learning Pipelines Exam is intended for data scientists, machine learning engineers, and data analysts who have working knowledge of SAS programming, data manipulation, and machine learning concepts. A00-401 exam is structured in such a way that it tests the candidate's ability to apply machine learning algorithms to real-world business problems.

SASInstitute A00-401 certification exam is recognized globally and is highly valued in the industry. It is an excellent way for individuals to demonstrate their expertise in machine learning and SAS Viya 3.4. SAS Viya 3.4 Supervised Machine Learning Pipelines certification can help individuals advance their careers in data science and machine learning and open up new opportunities for them. Employers also benefit from hiring SASInstitute A00-401 certified professionals as they can be assured of their skills and knowledge in building and managing machine learning pipelines using SAS Viya 3.4.

SASInstitute A00-401 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Preparation20%- Prepare data for modeling
  • 1. Transform and standardize variables
  • 2. Handle missing values
  • 3. Perform variable selection and feature engineering
  • 4. Create derived variables and features
Topic 2: Model Assessment and Deployment20%- Evaluate and deploy models
  • 1. ROC and lift analysis
  • 2. Select champion models
  • 3. Assess model performance metrics
  • 4. Publish and deploy models
  • 5. Compare competing models
Topic 3: Data Sources and Data Exploration25%- Access and manage data sources
  • 1. Import and load data into SAS Viya
  • 2. Understand metadata and project structure
  • 3. Explore data distributions and relationships
  • 4. Identify data quality issues
Topic 4: Building Models35%- Develop supervised machine learning models
  • 1. Decision trees
  • 2. Gradient boosting
  • 3. Support vector machines
  • 4. Forest models
  • 5. Model tuning and comparison
  • 6. Neural networks

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