The ideal schedule is given below. This schedule may vary during the semester. Chapters refer to the book Forecasting: Principles and Practice.
| Week | Date | Class | Exercises | Forecasting competition |
|---|---|---|---|---|
| 1 | 18.9 | Time series decomposition: Chapter 6 | R/RStudio installation, group formation. Exercices 6.5 & 6.6 | |
| 2 | 25.9 | Exponential smoothing: Chapter 7 Time series of counts: Chapter 12.2 | Follow the instructions | |
| 3 | 2.10 | ARIMA models: Chapter 8 | Launch of R-packages competition | |
| 4 | 9.10 | Complex seasonality: Chapter 11.1 Dealing with missing values and outliers: Chapter 12.9 | R-packages | |
| 5 | 16.10 | Presentation: R-packages Forecast combination: Chapter 12.4 | Report for R-packages | |
| 6 | 23.10 | Dynamic regression models: Chapter 9 | Launch of a new competition | |
| 7 | 30.10 | Web scraping and social media API | ||
| 8 | 6.11 | Bootstrapping and bagging: Chapter 11.4 | ||
| 9 | 13.11 | Presentation | Report | |
| 10 | 20.11 | GARCH extension | Launch of a new competition | |
| 11 | 27.11 | Neural network models: Chapter 11.3 | ||
| 12 | 4.12 | Presentation | Report. Launch of last competition | |
| 13 | 11.12 | Judgmental forecasts: Chapter 4 | ||
| 14 | 18.12 | Presentation | Report |