Data Structures Tutorial

1. Data Structures Introduction

Why the right data structure matters, a hash map vs list speed comparison, and Big-O notation explained from scratch.

2. Arrays & Strings

Fixed vs dynamic arrays, the Big-O of common operations, and solving reverse-a-string and first-non-repeating-character.

3. Linked Lists

Singly vs doubly linked lists, insert/delete/traverse with full code, array trade-offs, and detecting a cycle with Floyd's algorithm.

4. Stacks & Queues

LIFO stacks and FIFO queues in Python, real use cases like undo and BFS, and solving the valid parentheses problem.

5. Hash Tables

How hashing, buckets, and collisions work, average vs worst-case complexity, and solving two sum with a hash map.

6. Trees & Binary Search Trees

Tree terminology, BST insert/search/delete, the four traversal methods, and when a BST degrades to O(n).

7. Heaps & Priority Queues

Min-heaps vs max-heaps, the array-based heap representation, Python's heapq, and finding the k largest elements.

8. Graphs

Directed, undirected, and weighted graphs, adjacency lists vs matrices, and BFS/DFS traversal with real use cases.

9. Tries

What a prefix tree is, a complete insert/search/starts-with implementation, and building a simple autocomplete feature.

10. Choosing the Right Data Structure

A practical decision guide mapping common needs to the right structure, with worked leaderboard and duplicate-detection scenarios.

11. Data Structures Interview Questions

Commonly asked data structures interview questions with clear, practical answers.