This is the material from my presenttion at the BU summer school on differential privacy in the summer of 2022. https://bostondataprivacy.github.io/summerschool/ It consists of my slides and two jupyter notebooks, one covering privacy semantics and the other utility. The notebooks are best used inside a Google Collab environment because they cache data on google drive to avoid recomputation.
The privacy semantics notebook is particularly useful for people getting into the mathematics of privacy, as it uses simulations to show the privacy loss random variables and the associated hypothesis testing semantics of DP.
This material is free to use for academic and educational purposes, just make sure to cite the source.