Combinatorics and Probability Study Guide (Coursera)

Course Link: Combinatorics and Probability (part of the discrete math specialization)

I’m continuing to review and practice math concepts to be a better software engineer. Here are some thoughts if you want to go through the course and a list of external resources I’ve found helpful.

Although the course covers quite a few concepts and is well-structured, the prerequisites aren’t clarified in the description. I also had to supplement my study with other resources since this course doesn’t have everything I wanted to review.

I mainly complemented this course with the Statistics 110 course by Professor Joe Blitzstein. I’ve also went through various articles, videos, and tools to help develop a better intuition.

Prerequisites Clarification

Required

Logical Statements
Sets (notation, relationships, operations, Venn diagrams)
Python (loops, conditionals, functions, itertools)
- Required for the final assignment
- Knowing itertools is optional but it’ll make writing simulations easier

Optional

Functions
Calculus (if you want to derive some of the distributions)
Series (Geometric, Taylor)

Read the Introduction and Preliminaries section (chapter 0) of this book.

Math Review Handout (Stat 110).

Translating Between Probability and Sets (Stat 110).

Suggested Resources

There’s a separate section on Bayes’ Theorem because it was the most relevant topic for me (spent the most time on it).

Book

Discrete Mathematics: An Open Introduction by Oscar Levin

Complementary Course

Statistics 110 by Professor Joe Blitzstein
- Lectures 1-10 recommended
- Watch the other lectures as required