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To pass the A00-274 certification exam, candidates must demonstrate their ability to use SAS Visual Statistics to explore data, create visualizations, and build predictive models. They must be familiar with SAS Viya architecture, data preparation techniques, and statistical models. Candidates must also know how to deploy models and interpret model results. A thorough understanding of SAS programming, data manipulation, and statistics is essential for success in A00-274 exam.
SASInstitute A00-274 exam is a valuable credential for individuals who want to enhance their career prospects in data analysis, predictive modeling, and business intelligence. A00-274 exam validates candidates' knowledge and proficiency in advanced statistical techniques, machine learning algorithms, and data visualization. Pass the exam is an excellent way to demonstrate your expertise in using SAS Visual Statistics to solve complex business problems.
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SASInstitute A00-274 certification exam is designed for individuals who want to demonstrate their skills and knowledge in Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya. Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya certification exam is intended for data scientists, statisticians, and analytics professionals who want to gain a deeper understanding of SAS Visual Statistics and its various features. A00-274 exam measures the candidate's proficiency in creating and deploying interactive models, including data preparation, model assessment, and model deployment using SAS Visual Statistics.
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The A00-274 exam is a comprehensive test that covers a wide range of topics related to interactive model building using SAS Visual Statistics 8.4 on SAS Viya. Candidates will be tested on their knowledge of data preparation, exploration, and visualization, as well as their ability to build predictive models, perform model assessment, and deploy models.
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SASInstitute A00-274 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model comparison and scoring | 9% | - Score models and export score code - Compare models |
| Topic 2: Building and assessing regression-type models | 41% | - Perform generalized additive and nonparametric logistic regression - Explain and perform linear and generalized regression modeling - Assess model results (Fit statistics, ROC, residuals, predictions) - Perform logistic regression modeling |
| Topic 3: SAS visual statistics cross-functional tasks | 22% | - Perform model validation - Filter data used for a model - Use interactive group-by - Prepare data using SAS Visual Analytics |
| Topic 4: Building and assessing segmentation models | 28% | - Assess decision tree results - Perform unsupervised segmentation using cluster analysis - Perform supervised segmentation using decision trees - Analyze cluster results |
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