Time Series Fundamentals

Decompose, test for stationarity, read ACF/PACF, build ARIMA and boosted forecasters, and evaluate them without fooling yourself

Master time series forecasting: trend and seasonal decomposition, stationarity and differencing, ACF/PACF, exponential smoothing and ARIMA/SARIMA, lag-feature gradient boosting, temporal backtesting with MAE, MAPE, sMAPE and MASE, prediction intervals, and the leakage traps interviewers probe.

Practice questions (5)

• Computing a Simple Exponential Smoothing Forecast

  Intermediate · Free
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• Interpreting ADF and KPSS Together

  Advanced
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• Choosing ARIMA Orders from ACF/PACF

  Advanced
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• Debugging a Leaky Gradient Boosting Forecast Pipeline

  Advanced
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• Choosing the Right Forecast Error Metric

  Intermediate
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Quizzes (1)