Course 3A: Time Series in Driverless AI

Learning Outcomes:

By the end of this training, the attendee will be able to

  • Create and tune a predictive model with a time component
  • Explain what is meant by a “gap” and determine its value for a given problem
  • Locate and explain expert settings related to time series models
  • Incorporate additional time series models, transformers, and scorers via recipes
  • Compare multiple models side-by-side and find Shapley values for predictions


This course assumes 

  • Completion of “Introduction to Driverless AI” or equivalent experience.
  • Completion of “Customizing Driverless AI with Recipes.”
  • Familiarity with statistical or machine learning modeling.
  • Prior experience with Time Series models preferred, but not required.

Are you interested in this course? If so, we will email you once this course is available.

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