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