Lecture 2: Why we need to learn time complexity | DSA Intensive | Tultul NeuroStack | Mubtasim Taha

Time complexity measures how an algorithm's execution time grows as its input size increases. It evaluates algorithmic performance independent of hardware, using Big-O notation to represent worst-case scenarios

In this video, we will learn the basics of Time Complexity and understand how to measure the efficiency of an algorithm using Big O notation with simple explanations and real examples. Topics include O(1) and basic optimization concepts for problem solving .

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Видео Lecture 2: Why we need to learn time complexity | DSA Intensive | Tultul NeuroStack | Mubtasim Taha канала Tultul NeuroStack