During my studies I got to see a lot of programming and a lot of mathematics. I remember having a hard time with some probability and statistics but after some after getting some help from fellow students, I managed to pass the courses.

Over the years after my graduation, I wanted to keep up with the field and continue learning. The main method I use to keep is by doing Coursera/Edx online courses. I also practiced a lot of exercises on Datacamp and learned some technologies on Udemy. Some were more deep than others but almost all of them did help me. In these cases I was always learning with a clear goal. I also have many books on computer science and data science topics which I use from time to time. But, up to now I never took the time to go through them cover to cover and do the exercises.

Now some of those early maths and CS courses are 10 years (or more) ago and I wonder how much stuck with me. So, I'm planning to go over some of the books I have. I want to go over them quietly at my own pace and without the pressure from University.

The first book I chose is Introduction to Probability, of which I've heard many positive things. What I also like is that there are resources available online which can help me. Since the book uses R, this is a great opportunity to do a little R programming and add the notes and explanation in R code.

If I have any notes worth sharing I'll put them in the notes section of this website. There is no planning for when or if I make them, since I want to take as long as it takes and life often gets in the way.