Learn about Big O notations in this 21-minute tutorial video. Explore how computer algorithms scale as data volume increases, covering O(1), O(N), O(N^2), O(log N), and O(N log N) notations. Gain a simplified understanding of these concepts through clear explanations and practical examples. Discover how Big O notations are used to measure algorithm efficiency, not just in terms of speed but also in relation to data growth. Follow along with the provided code examples to reinforce your understanding of these fundamental computer science concepts.
Overview
Syllabus
Big O Notations
Taught by
Derek Banas