5. Data Structures & Algorithms
This volume teaches data structures and algorithms in Python, with a focus on practical problem solving and efficient coding. Chapters are numbered continuously across the volume.
Part I: Introduction to DSA in Python
- 1. Importance Of Dsa
- 2. Time Complexity
- 3. Space Complexity
- 4. Big O Notation Basics
- 5. Amortized Analysis
Part II: Arrays and Strings
- 6. Array Basics
- 7. Common Array Operations
- 8. Advanced Array Problems Two Pointer Technique
- 9. Advanced Array Problems Sliding Window
- 10. String Basics
- 11. String Manipulation In Python
- 12. Pattern Matching Basics
- 13. Advanced Pattern Matching
Part III: Stacks and Queues
- 14. Stack Basics
- 15. Stack Implementations
- 16. Stack Applications
- 17. Queue Basics
- 18. Queue Implementations
- 19. Deque And Priority Queue
- 20. Queue Applications
Part IV: Linked Lists
- 21. Singly Linked List Basics
- 22. Singly Linked List Operations
- 23. Doubly Linked List
- 24. Circular Linked List
- 25. Linked List Problems
Part V: Trees and Graphs
- 26. Binary Tree Basics
- 27. Binary Tree Traversals
- 28. Binary Search Tree
- 29. Balanced Trees
- 30. Tree Applications
- 31. Graph Basics
- 32. Graph Representations
- 33. Graph Traversals Bfs Dfs
- 34. Shortest Path Algorithms
- 35. Minimum Spanning Tree
Part VI: Searching and Sorting Algorithms
- 36. Linear Search
- 37. Binary Search
- 38. Binary Search Applications
- 39. Bubble Sort
- 40. Selection Sort
- 41. Insertion Sort
- 42. Merge Sort
- 43. Quick Sort
- 44. Heap Sort
- 45. Counting Sort
- 46. Radix Sort
Part VII: Advanced Algorithms
- 47. Greedy Algorithms Basics
- 48. Classic Greedy Problems
- 49. Dynamic Programming Basics
- 50. Classic Dp Problems
- 51. Backtracking Basics
- 52. Classic Backtracking Problems
- 53. Graph Algorithms
Part VIII: Capstone Project
- 54. Project Overview
- 55. Designing Custom Data Structure
- 56. Implementing Algorithms
- 57. Testing And Benchmarking
- 58. Final Wrap Up
By completing this volume, you will gain mastery of core data structures, algorithms, and problem-solving strategies essential for technical interviews and real-world applications.