Time Complexity & Big-O Notation Explained Simply

The post explains time complexity as how operation count grows with input size.

It compares common Big-O classes: O(1), O(n), O(log n), and O(n²) with examples and a growth table.

The article highlights how Big-O helps compare algorithms, estimate performance on large inputs, and reason about tradeoffs in interviews.