🔧 Data Structures & Algorithms
Master the fundamental building blocks of computer science. This section covers essential data structures, algorithms, and problem-solving techniques.
📚 Learning Path
1
Basic Data Structures
Arrays, Linked Lists, Stacks, Queues
2
Advanced Data Structures
Trees, Graphs, Heaps, Hash Tables
3
Basic Algorithms
Sorting, Searching, Recursion
4
Advanced Algorithms
Dynamic Programming, Graph Algorithms
🗂️ Data Structures
Arrays & Strings
Linear data structures for storing and manipulating data
Arrays
Strings
2D Arrays
Dynamic Arrays
Linked Lists
Dynamic data structure with nodes connected by pointers
Singly Linked
Doubly Linked
Circular
Operations
🔄 Algorithms
Sorting Algorithms
Algorithms to arrange elements in a specific order
Bubble Sort
Quick Sort
Merge Sort
Heap Sort
Searching Algorithms
Algorithms to find elements in data structures
Linear Search
Binary Search
DFS
BFS
Dynamic Programming
Optimization technique for solving complex problems
Memoization
Tabulation
LCS
Knapsack
📊 Complexity Analysis
Time Complexity Cheat Sheet
| Complexity | Description | Examples |
|---|---|---|
| O(1) | Constant time | Array access, Hash table lookup |
| O(log n) | Logarithmic time | Binary search, Binary tree operations |
| O(n) | Linear time | Linear search, Array traversal |
| O(n log n) | Linearithmic time | Merge sort, Quick sort, Heap sort |
| O(n²) | Quadratic time | Bubble sort, Selection sort, Nested loops |
| O(2ⁿ) | Exponential time | Recursive Fibonacci, Subset generation |
📈 Progress Tracking
Data Structures
80% CompleteSorting Algorithms
90% CompleteDynamic Programming
60% CompleteGraph Algorithms
70% Complete"The best way to learn algorithms is to implement them yourself. Don't just read about them - code them!"