Big O Notation (Foundations of Computer Science)
Channel: Sparky's Training Academy
Date: 20/04/2024

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In this comprehensive lecture, we explore the critical concept of Big O Notation, a fundamental principle used in computer science to express the upper limit of time or space complexity of an algorithm. The lecture delves into definitions, computations, and practical real-world applications of Big O Notation, highlighting its importance in assessing the scalability and efficiency of algorithms as input sizes increase. We examine various examples, such as sorting and searching algorithms, to illustrate how Big O Notation helps in optimizing performance, particularly in large datasets. This understanding is not only crucial for theoretical academic purposes but also immensely valuable for practical implementations in software engineering and database management.

00:00 - Intro
00:10 - Big O Notation Explained
01:10 - Understanding Big O Notation
02:08 - Practical Impact of Big O
03:06 - Time Complexities Catalog
04:06 - Space vs. Time in Algorithms
05:03 - Calculating Big O
05:54 - Growth Rates Visualized
06:52 - Big O in the Wild
07:47 - Recap Big O Essentials
08:44 - Big O Mastery Review