Get Started in Time Series Forecasting in Python | Full Course

Lifetime access to the course, modules are regularly updated, and your questions are answered by me directly!

Course material:

This video is the perfect starting point for beginners looking to forecast time series data. We use 100% Python code to cover the fundamental concepts of time series forecasting:
- defining time series data
- time series decomposition
- forecasting with ARIMA
- cross-validation in time series
- using exogenous features
- generating prediction intervals
- evaluation metrics for forecasting models

Chapters:
- 0:00 Introduction
- 1:20 Define time series
- 5:38 Baseline models
- 9:10 Baseline models (code)
- 23:22 ARIMA
- 31:01 ARIMA (code)
- 38:21 Cross-validation
- 40:38 Cross-validation (code)
- 49:56 Forecasting with exogenous features
- 54:28 Exogenous features (code)
- 1:08:10 Prediction intervals
- 1:09:32 Prediction intervals (code)
- 1:14:31 Evaluation metrics
- 1:18:58 Evaluation metrics (code)
- 1:29:25 Next steps