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The SASInstitute A00-403 exam will test for the ability to use the SAS Viya 3.5 platform to perform forecasting and optimization analyses on large datasets. A00-403 exam also evaluates the examinee's understanding of machine learning models, such as decision trees, linear regression, and clustering algorithms. Additionally, the exam includes questions on various SAS Viya 3.5 tools, such as SAS Studio, SAS Visual Analytics, and SAS Visual Data Mining and Machine Learning.
Passing the SASInstitute A00-403 exam is a valuable credential for professionals who work in forecasting and optimization. SAS Viya 3.5 Forecasting and Optimization certification demonstrates that the candidate has a thorough understanding of SAS Viya 3.5 software and can use it to solve complex problems related to forecasting and optimization. Additionally, this certification can help professionals advance in their careers and increase their earning potential.
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To pass the exam, the candidate must score at least 70%. SAS Viya 3.5 Forecasting and Optimization certification is globally recognized and is ideal for individuals who want to showcase their advanced skills and knowledge to employers. The SASInstitute A00-403 certification also provides ample opportunities for professional growth and career development. It is an excellent investment for individuals who aspire to take their career to the next level in the forecasting and optimization domain.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Post-Forecasting Functionality | 10-15% | - Generate forecast reports and outputs - Apply forecast overrides and adjustments - Evaluate forecast accuracy |
| Topic 2: Data Visualization | 15-20% | - Interpret visual outputs - Use attribute variables for analysis - Visualize time series and modeling data |
| Topic 3: Optimization | 25-30% | - Use mixed integer linear programming - Solve optimization models in SAS Viya - Formulate linear programming problems - Apply non-linear programming techniques |
| Topic 4: Pipeline Modeling | 25-30% | - Deploy forecasting pipelines - Build forecasting pipelines - Refine and compare models - Automate model fitting and selection |
| Topic 5: Hierarchical Forecasting | 15-20% | - Reconcile forecasts across levels - Create hierarchical forecast structures - Apply aggregation/disaggregation methods |
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