Algorithmic Complexity: Big-O Notation

In course

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Description

This lecture covers the fundamentals of algorithmic complexity, focusing on Big-O notation to analyze the efficiency of algorithms. Topics include logic, mathematical reasoning, basic structures, and growth functions. The instructor explains how to determine time complexity, worst-case complexity, and the efficiency of algorithms through Big-O, Big-Omega, and Big-Theta notations.

Official source

https://mediaspace.epfl.ch/media/0_fuwumrym

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Ontological neighbourhood

Mathematics

Analysis: Complex analysis

Number theory: Topics in number theory

Algebra: Abstract algebra

Theoretical computer science

Theory of computation: Computational complexity theory

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