Combinatorics and Probability Study Guide (Coursera)

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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


  • 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


  • 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).


Complementary Course

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

Bayes’ Theorem

These are ordered by suggested study order.



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