Big O(n^2) Complexity

The video tutorial explains quadratic time complexity, denoted as O(N^2), which often occurs with nested loops. It uses a list example to demonstrate how operations increase quadratically with the number of elements. The tutorial also covers the notation for quadratic functions and discusses complexity when dealing with multiple input lists. The video concludes by summarizing the key points and hinting at the next topic.

What are the implications of removing constants when simplifying the notation for a function's complexity?

How does the complexity change when considering two different lists with N and M elements?