DataRobot Time Series 00:45
Activity: Simple Sales Forecasting 01:30
Activity: Selecting Your Evaluation Period 01:00
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Time Series Starter
Key concepts around using DataRobot Time Series.
On this mission, you will learn the key concepts that provide the foundation for building time series models with DataRobot. After gaining that foundation, you will generate sales forecasts using DataRobot Automated Time Series. You will also build a model for forecasting the number of train passengers for a specified evaluation period. You will use DataRobot’s Time Series evaluation tools to understand and optimize your forecasts.
Mission format and duration: self-paced, hands-on, 1.5 hours
Upon completion of this mission, you will be able to:
- Develop datasets for time series modeling
- Calculate dataset sizes for time series modeling
- Determine whether to use a regular, semi-regular, or irregular time series for a forecast model
- Determine whether to use Out-of-Time Validation (OTV) or time series modeling for a forecast model
- Select Feature Derivation Window (FDW) and Forecast Distance (FD) parameters
- Employ backtesting during time series modeling
- Build and evaluate time series forecast models
- Select the evaluation period for your models
Who should complete this mission?
- Business Analysts
- Citizen Data Scientists
- Data Scientists
Before embarking on this mission, you should complete one of the following:
- Starter Quest appropriate for your role (self-paced mission)
- AutoML I (virtual instructor-led mission)
- DataRobot for Data Scientists (virtual instructor-led mission)
- Chrome browser
- DataRobot Automated Time Series — (this mission assumes you currently have access to this product).