"Section 3: Time/Space Complexity"
📚 Vanakkam DSA Course (24 sections) · Hope AI — ML & DS Course
Overview
Understanding time and space complexity is fundamental to writing efficient algorithms and acing technical interviews.
Lessons
| # | Lesson Name | Duration | Notes |
|---|
| 1 | Time & Space Complexity | 1h 29m 31s | |
Lesson Checklist
- [ ] Time & Space Complexity (1h 29m 31s)
My Notes
Add your personal notes, key takeaways, and insights here as you progress through the section.
Big-O Notation
Common Complexities
| Complexity | Name | Example |
|---|
| O(1) | Constant | Array access |
| O(log n) | Logarithmic | Binary search |
| O(n) | Linear | Linear search |
| O(n log n) | Linearithmic | Merge sort |
| O(n²) | Quadratic | Bubble sort |
| O(2ⁿ) | Exponential | Recursive Fibonacci |
Space Complexity Notes
Key Takeaways