Time Series Analysis and Forecasting with Python

It moves through decomposition, stationarity, ARIMA and SARIMA, Facebook Prophet, and neural approaches — a genuinely wide arc that's useful precisely because there's no single best forecasting method: which one wins depends on the data, and seeing the range lets you choose rather than default. It's aimed at people who already know some Python and statistics.

So skip it if you lack that grounding or you want theory alone. Udemy lists a high price but it's nearly always $12–20 on sale with lifetime access — wait for the discount. The certificate marks what you completed, not an accredited qualification (as of 2026).

This course covers time series analysis and forecasting from classical methods to deep learning: decomposition, stationarity testing, ARIMA and SARIMA models, Facebook Prophet for trend and seasonality modeling, and LSTM neural networks for sequence forecasting.