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SASInstitute A00-401 Exam Braindumps - in .pdf Free Demo

  • Exam Code: A00-401
  • Exam Name: SAS Viya 3.4 Supervised Machine Learning Pipelines
  • , Last Updated: Oct 15, 2026
  • Q & A: 0 Questions and Answers
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SASInstitute A00-401 Exam Braindumps - Testing Engine PC Screenshot

  • Exam Code: A00-401
  • Exam Name: SAS Viya 3.4 Supervised Machine Learning Pipelines
  • , Last Updated: Oct 15, 2026
  • Q & A: 0 Questions and Answers
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SASInstitute A00-401 Exam Overview:

Certification Vendor:SAS Institute
Exam Name:SAS Viya 3.4 Supervised Machine Learning Pipelines
Exam Number:A00-401
Related Certifications:SAS Certified Specialist: Machine Learning Using SAS Viya
Exam Duration:100 minutes
Real Exam Qty:50-60
Exam Format:Short Answer, Multiple Choice
Exam Price:$180 USD
Available Languages:Japanese, English
Exam Way:Pearson VUE testing centers or Pearson VUE online proctored exam.
Pre Condition:No formal prerequisite exam required. Candidates should have practical experience with SAS Viya, machine learning concepts, data preparation, model building, assessment, and deployment.
Official Syllabus URL:https://www.sas.com/en_us/certification/credentials/advanced-analytics/machine-learning-using-sas-viya.html

SASInstitute A00-401 Exam Syllabus Topics:

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

SASInstitute A00-401 Exam — Answers to Your Questions

The SASInstitute SAS Viya 3.4 Supervised Machine Learning Pipelines (exam code A00-401) is the exam you pass to earn the SASInstitute Certification certification, a credential at the Specialist level. It is also connected with related credentials such as SAS Certified Specialist: Machine Learning Using SAS Viya. If you are mapping out a certification path with SASInstitute, this exam is a milestone worth planning around.

The A00-401 exam includes 50-60 questions, and you have 100 minutes to complete them. With that many questions on the clock, pacing is part of the challenge: divide your time into rough blocks as you go, and flag the items that stall you so you can circle back at the end instead of burning minutes on a single question. A week or two before your exam date, sit at least one full timed session in the ExamsTorrent test engine under the same time limit, so the pace feels familiar rather than frantic on the day.

No formal prerequisite exam required. Candidates should have practical experience with SAS Viya, machine learning concepts, data preparation, model building, assessment, and deployment.

Eligibility rules can be adjusted by SASInstitute over time, so before you register, confirm the current requirements on the official exam page: view the official A00-401 exam information.

Yes. ExamsTorrent offers a free PDF demo of the A00-401 practice questions, so you can judge the quality of the material firsthand before paying anything. Every purchase also includes 365 days of free updates — if SASInstitute changes the exam during that year, your material changes with it. And when the free update period expires, you can extend it at a 50% discount from within your member zone.

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The official SASInstitute SAS Viya 3.4 Supervised Machine Learning Pipelines outline divides the exam content into 4 main domains. The first three are:

  • Data Preparation — 20%
  • Building Models — 35%
  • Data Sources and Data Exploration — 25%

That is only the headline view — scroll back up to the Exam Topics section on this page for the complete domain-by-domain breakdown before you plan your study schedule.

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