The Last Algorithms Course You'll Ever Need

https://theprimeagen.github.io/fem-algos/

Resources/Books

• https://amzn.to/3bYmBMu
• https://amzn.to/3Qp9KlB or https://learning.oreilly.com/library/view/a-common-sense-guide/9781680508048/

Big O Notation

Look for loops.

Important concepts

1. growth is with respect to the input
2. Constants are dropped
3. Worst case is usually the way we measure

• O(n). Single loop counting chars.
• O(log n). Binary Search trees.
• O(n log n). Quicksort.
• O(n^2). Two nested loops.

N = 1, O(10N) = 10, O(N^2) = 1
N = 5, O(10N) = 50, O(N^2) = 25
N = 100, O(10N) = 1,000, O(N^2) = 10,000 // 10x bigger
N = 1000, O(10N) = 10,000, O(N^2) = 1,000,000 // 100x bigger
N = 10000, O(10N) = 100,000, O(N^2) = 100,000,000 // 1000x bigger

Complexity Cheat Sheet

https://www.hackerearth.com/practice/notes/big-o-cheatsheet-series-data-structures-and-algorithms-with-thier-complexities-1/