SAS® Certified Professional: AI & Machine Learning | SAS India

SAS® Certified Professional: AI & Machine Learning

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SAS® Certified AI & Machine Learning

Earn three specialist-level certifications and automatically get a professional-level credential in artificial intelligence and machine learning

Make a difference in your career and the future

Course commences on 26 June, 2021

Course details

SAS® Certified Specialist Machine Learning Using SAS® Viya

  • Apply the analytical life cycle to a business need.
  • Prepare and explore data for analytical model development.
  • Create and select features for predictive modeling. 
  • Develop supervised learning models based on different techniques, from decision tree to support vector machines.
  • Evaluate and select the best model based on business needs.
  • Deploy and manage analytical models under production.

SAS® Certified Specialist Natural Language & Computer Vision

  • Interpret term maps and automatically identify key textual topics large document collections. 
  • Create, modify and enable (or disable) custom concepts and test linguistic rule definitions with validation checks within the same interactive GUI.
  • Extract individual instances of concepts from within documents. 
  • Create custom Boolean rules to categorize documents with respect to a categorical target variable and automatically modify those rules.
  • Define, understand and learn how to search the hyper-parameter space to build deep learning models. 
  • Apply models to score new data and modify existing data for better model performance. 

SAS® Certified Specialist Forecasting & Optimization

  • Automatically create and fit custom forecast models using structured analytic workflows or pipelines.
  • Refine forecast models to improve forecast accuracy, and generate forecast data sets for deployment.
  • Build and share custom pipelines for large-scale forecasting analyses.
  • Visualize modeling data using attribute variables.
  • Apply overrides-generated forecasts.
  • Identify and formulate appropriate approaches to solving various linear, mixed-integer linear and nonlinear optimization problems using the OPTMODEL procedure in SAS

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