SASInstitute A00-403 Valid Test : SAS Viya 3.5 Forecasting and Optimization

  • Exam Code: A00-403
  • Exam Name: SAS Viya 3.5 Forecasting and Optimization
  • Updated: Aug 18, 2026
  • Q&As: 0 Questions and Answers

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SASInstitute A00-403 (SAS Viya 3.5 Forecasting and Optimization) Certification Exam is a globally recognized certification that validates the knowledge and skills of professionals in using SAS Viya 3.5 for forecasting and optimization tasks. SAS Viya 3.5 Forecasting and Optimization certification can provide career advancement opportunities and access to a community of SAS certified professionals. Candidates can prepare for the exam by using resources such as training courses, online tutorials, and practice exams, as well as gaining practical experience in using SAS Viya 3.5 for real-world tasks.

Reference: https://www.sas.com/en_us/certification/credentials/advanced-analytics/forecasting-and-optimization-specialist.html

SASInstitute A00-403 (SAS Viya 3.5 Forecasting and Optimization) Exam is a certification exam that assesses the knowledge, skills, and abilities of candidates in using SAS Viya for forecasting and optimization. A00-403 exam is intended for professionals who are involved in statistical analysis, forecasting, operations research, or any other fields that require the use of mathematical models to optimize business processes.

SASInstitute A00-403 Exam Syllabus Topics:

SectionObjectives
Topic 1: Optimization in SAS Viya- Linear programming fundamentals
- Constraint formulation using OPTMODEL
- Integer and mixed-integer optimization
Topic 2: SAS Viya Forecasting (Visual Forecasting)- Automatic forecasting pipelines
- Model selection and comparison
- Data preparation for time series
Topic 3: Integrated Forecasting and Optimization- Decision optimization with forecasts
- Demand planning and scenario analysis
Topic 4: Forecasting Fundamentals- Stationarity and transformations
- Forecast accuracy metrics
- Time series components and decomposition
Topic 5: Time Series Modeling- Exponential smoothing (ETS models)
- ARIMA and seasonal ARIMA models
- Regression-based forecasting

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