Data Structures and Algorithms The Complete Masterclass - Big O(1) Complexity

The lecture introduces Big O notation, focusing on constant time complexity (O(1)). It uses a student list example to demonstrate that the number of operations remains constant regardless of input size. The lecture explains that even if multiple operations are performed, the complexity is still considered constant. It emphasizes that Big O notation simplifies to O(1) for constant operations, regardless of the number of operations. The lecture concludes with a preview of calculating complexity step-by-step in the next session.

What is the complexity of the function 'display student' and why?

How does the number of elements in the input list affect the number of operations performed by the function?

Explain the significance of constant time complexity in terms of scalability.

What does it mean when we say that big O of 2, 3, or 4 is considered constant?

What are the two points studied in the lecture regarding complexity?