Module 1: Introduction

Topics Covered:

Big O Notation
Introduction to Recursion
Importance of Algorithmic Thinking

Key Concepts:

Time complexity and space complexity.
Understanding recursion and its base case.

Quiz:

What is the time complexity of performing a linear search on an unsorted array?
- a) O(log n)
- b) O(n)
- c) O(n log n)
- d) O(1)
Which of the following is a characteristic of a recursive algorithm?
- a) It calls itself.
- b) It always has a base case.
- c) It often divides a problem into smaller subproblems.
- d) All of the above.
What is the purpose of Big O notation?
- a) To find the exact execution time of an algorithm.
- b) To describe the worst-case complexity of an algorithm.
- c) To optimize space usage.
- d) None of the above.