Complexity Analysis Mastery

Public lesson preview

Confidently analyse time and space complexity — the skill that separates good solutions from optimal ones in coding interviews.

Learning objectives

By the end of this lesson, you will understand:

• ✓Big-O Notation Fundamentals
• ✓Analysing Simple Loops
• ✓Analysing Recursion
• ✓Space Complexity
• ✓Amortised Analysis Basics

Lesson outline

1. Big-O Notation Fundamentals
2. Analysing Simple Loops
3. Single Loop → O(n)
4. Nested Loops → Multiply
5. Sequential Blocks → Add
6. Loops with Non-Obvious Iterations
7. Analysing Recursion
8. Linear Recursion → O(n)
9. Binary Recursion → O(2ⁿ)
10. Memoised Recursion → O(n)
11. The Master Theorem (Simplified)
12. Space Complexity
13. Amortised Analysis Basics
14. Common Complexity Traps
15. Trap 1: Hidden Loops in Built-in Operations
16. Trap 2: Sorting Dominates
17. Trap 3: Recursion Depth ≠ Total Work
18. From Brute Force to Optimal
19. Key Takeaways