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S07 · Time Series and Forecasting

A free, illustrated L2 to L3 course of 10 modules in the Statistics and Data Analysis track. Modules include: Trend, seasonality and noise; Stationarity and autocorrelation; Exponential smoothing.

S07 L2 to L3 · Intermediate to Advanced 10 modules · about 40 lessons Planned · Ring 3

Part of the Statistics and Data Analysis track. Ships in Ring 3 (Breadth) of the roadmap.

Modules

1. Trend, seasonality and noise
2. Stationarity and autocorrelation
3. Exponential smoothing
4. The ARIMA family
5. State-space models and the Kalman filter
6. Spectral analysis
7. Multivariate series and vector autoregression
8. Forecast evaluation and backtesting
9. ML and deep forecasting
10. Anomaly and change-point detection

Signature illustrations

The pictures a learner should still see in their head a year later:

Decomposition stack plots, a reading guide for autocorrelation plots, the Kalman predict-and-update cycle, rolling-origin backtest diagram.

Status

This course is planned, not written yet. It ships with Ring 3 (Breadth).

Every lesson will follow the same twelve-part blueprint with at least three purpose-made figures. Watch the repository to hear when modules ship, or help write and review it.