Daniel Schmidt's teaching and accompanying lecture notes make this unit a 5-starer. Great head-first dive into the field of statistics and modeling for aspiring data scientists. The assignments were enjoyable and employed the concepts covered in class to real-world data. The unit is quite maths-heavy and content-heavy, but Daniel accommodates (at least when I took this) by excluding certain advanced topics from the exam. The notes are super useful and the tutorials provide great examples using R. You may find yourself going to Kaggle and grabbing data to discover trends in or model. My one issue with the unit is the lack of Bayesian statistics, I think it may have been worth discussing _at least_ the philosophy, especially since a lot of Daniel's work seems to be Bayesian!