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This course is an introduction to time series forecasting with Python. It's a perfect starting point for beginners looking to forecast time series data. You will learn the fundamental concepts of time series forecasting. ✏️ Course developed by @datasciencewithmarco Solutions notebook: https://github.com/marcopeix/youtube_... Dataset: https://github.com/marcopeix/youtube_... Learn even more with this paid course: Applied Time Series Forecasting in Python https://www.datasciencewithmarco.com/... ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Chapters ⭐️ ⌨️ (0:00:00) Introduction ⌨️ (0:02:12) Define time series ⌨️ (0:06:30) Baseline models ⌨️ (0:10:02) Baseline models (code) ⌨️ (0:24:14) ARIMA ⌨️ (0:31:53) ARIMA (code) ⌨️ (0:39:13) Cross-validation ⌨️ (0:41:30) Cross-validation (code) ⌨️ (0:50:48) Forecasting with exogenous features ⌨️ (0:55:20) Exogenous features (code) ⌨️ (1:09:02) Prediction intervals ⌨️ (1:10:24) Prediction intervals (code) ⌨️ (1:15:23) Evaluation metrics ⌨️ (1:19:50) Evaluation metrics (code) ⌨️ (1:30:17) Next steps 🎉 Thanks to our Champion and Sponsor supporters: 👾 Drake Milly 👾 Ulises Moralez 👾 Goddard Tan 👾 David MG 👾 Matthew Springman 👾 Claudio 👾 Oscar R. 👾 jedi-or-sith 👾 Nattira Maneerat 👾 Justin Hual -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news