This is the order I followed (helped me quite a bit) I did points 1, 2 and 3 side by side because all of them more or less cover the same content (and I wanted a practical insight into whatever theory I was learning).
Strongly recommend David Silver's RL Course
Sutton and Barto's Reinforcement Learning: An Introduction book.
You should also consider solving the problems, but here is the solutions in case you are stuck with some problem.
Again, in no particular order, if the above does not suffice, you can always google your way through. But here are some resources to make your job easier (some/most of these courses are introductory courses but there are a few which are a little advanced and will need you to have basic knowledge about RL):
https://www.microsoft.com/en-us/research/event/reinforcement-learning-day-2019/agenda/
https://www.deepmind.com/learning-resources/reinforcement-learning-lecture-series-2021
https://sites.google.com/view/rltheoryseminars/past-seminars
http://dalimeeting.org/dali2017/data-efficient-reinforcement-learning.html
https://www.youtube.com/playlist?list=PLp0hSY2uBeP8q2G3mfHGVGvQFEMX0QRWM