Big O Notations - Understanding Algorithm Efficiency
Offered By: Derek Banas via YouTube
Course Description
Overview
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.
Syllabus
Big O Notations
Taught by
Derek Banas
Related Courses
Probabilistic Graphical Models 1: RepresentationStanford University via Coursera Computer Security
Stanford University via Coursera Intro to Computer Science
University of Virginia via Udacity Introduction to Logic
Stanford University via Coursera Internet History, Technology, and Security
University of Michigan via Coursera