Скачать или смотреть What Is Algorithmic Complexity?

This video is about algorithmic complexity, which is understanding how much work a computer does to solve a problem. It's not about how fast the computer is, but how efficiently the method used is designed. Complexity is measured in terms of time (how long it takes) and space (how much memory it needs). The video explains different levels of complexity using "Big O notation", like O(n) which means time grows linearly with the amount of data, and O(log n) which is much faster as the data gets bigger. It also covers other complexities like O(1), O(n^2), and O(2^n), explaining how they impact performance as the problem size increases. Finally, it touches on space complexity and how it relates to time complexity, and how to simplify Big O notation by focusing on the dominant term.