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SASInstitute A00-401 Exam Syllabus Topics:

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

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