Course materials for the Coursera MOOC: Practical Time Series Analysis from The State University of New York
The course has all its assignments and notebooks in R.
As Python is the go-to language for me, this repository tries to rewrite R notebooks and all the analysis that has explained step by step, including the PDFs lessons, in Python.
Datasets are the same and have been accumulated in its respectively week data folder.
| Week Number | Weeks Cap Name | Link to Repo |
|---|---|---|
| 1 | Basic Statistical | Week Repo |
| 2 | Visualizing Time Series, and Beginning to Model Time Series | Week Repo |
| 3 | Stationarity, MA(q) and AR(q) processes | Week Repo |
| 4 | AR(p) processes, Yule-Walker equations, PACF | Coming Soon |
| 5 | Akaike Information Criterion (AIC), Mixed Models, Integrated Models | Coming Soon |
| 6 | Seasonality, SARIMA, Forecasting | Coming Soon |
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