Apply the Time Series curriculum to a checked project.
Project brief
Required concepts
- Time-series calendar: distinguish missing periods from measured zeros
- Lag features: prove each input existed at forecast time
- Seasonal naive forecast: establish a baseline before fitting a model
- Rolling-origin backtests: rehearse the forecast as it would have run
- Forecast metrics by horizon: keep errors, zeros and denominators explicit
- Forecast intervals: measure future-outcome coverage by horizon
- Forecast monitoring: separate data delay, demand shift and model failure
Completion standard
Submit runnable work, a data manifest, measured results and failure-case evidence.