Adding more statistics and forecasting material to AI&DS

Added two courses from Harvard and Monash University, as well as an open source course to familiarise people with forecasting.

src/data/roadmaps/ai-data-scientist/content/classic-ml-sup-unsup-advanced-ml-ensembles-nns@FdBih8tlGPPy97YWq463y.md

@@ -5,3 +5,5 @@
 - [@article@Pattern Recognition and Machine Learning by Christopher Bishop](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf)
 - [@opensource@Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop](https://github.com/gerdm/prml)
 - [@feed@Explore top posts about Machine Learning](https://app.daily.dev/tags/machine-learning?ref=roadmapsh)
+- [@article@Forecasting with Python](https://cienciadedatos.net/en/forecasting-python) 
+- [@article@Forecasting: Principles and Practice](https://otexts.com/fpp3/)

src/data/roadmaps/ai-data-scientist/content/statistics-clt@Y9YJdARIRqqCBCy3GVYdA.md

@@ -1,4 +1,4 @@
 # Statistics, CLT
 
 - [@article@Introduction to Statistics](https://imp.i384100.net/3eRv4v)
-
+- [@article@Introduction to Statistical Learning](https://www.statlearning.com/)