Understanding Arithmetic and Asymptotic Complexity: Big-O, Ω, and Θ Explained

In this video I explain the concepts and differences of arithmetic and asymptotic time complexity referring to algorithms in computer science. After shortly introducing the mathematical basics, we apply the theory to practical examples.


-----


Timestamps

[00:00] Introduction

[00:18] What is algorithmic complexity?
[00:59] What is asymptotic complexity?
[02:18] Big-O Explained (Theory)
[05:18] Big-O Explained (Example)
[06:43] Big-Ω Explained (Theory)
[08:11] Big-Θ Explained (Theory)
[10:22] Rules for Simplification- Rule 1 w/ Example
[10:50] Rules for Simplification- Rule 2 w/ Examples
[13:11] Rules for Simplification- Rule 3 (Loops) w/ Examples
[15:24] Rules for Simplification- Rule 4 (Nested Loops) w/ Example
[16:23] Rules for Simplification- Rule 5 (Programs) w/ Example
[18:00] Outro