📊
Big OTreesGraphsDP
Essential for coding interviews. Master time complexity, data structures like trees and graphs, and classic algorithms including sorting, searching, and dynamic programming.
Learn Algorithms & Data Structures
Master algorithms and data structures essential for technical interviews and efficient programming. Learn arrays, linked lists, trees, graphs, sorting, searching, dynamic programming, and algorithm analysis.
18
Topics
200+
Code Examples
~7 hrs
Reading Time
📊 What You'll Learn
- ✓ Big O Notation: Analyzing algorithm complexity
- ✓ Data Structures: Arrays, linked lists, stacks, queues, trees, graphs
- ✓ Sorting: Bubble, merge, quick sort and more
- ✓ Searching: Linear, binary, and advanced search techniques
- ✓ Recursion: Recursive problem solving and thinking
- ✓ Dynamic Programming: Optimization and memoization
- ✓ Graph Algorithms: BFS, DFS, shortest paths, MST
- ✓ Problem Solving: Techniques for coding interviews
Topics
Lesson 1
Beginner
Big O Notation
Understanding time and space complexity analysis for algorithms
15 minFull Guide
Lesson 2
Beginner
Arrays
Understanding array data structure, operations, and common algorithms
20 minFull Guide
Lesson 3
Beginner
Linked Lists
Singly and doubly linked lists, operations, and use cases
25 minFull Guide
Lesson 4
Beginner
Stacks
Stack data structure, LIFO principle, and practical applications
15 minFull Guide
Lesson 5
Beginner
Queues
Queue data structure, FIFO principle, and implementation
18 minFull Guide
Lesson 6
Beginner
Hash Tables
Hash tables, hash functions, collision handling, and performance
22 minFull Guide
Lesson 7
Intermediate
Trees & Binary Trees
Tree data structures, binary trees, and tree traversals
25 minFull Guide
Lesson 8
Intermediate
Binary Search Trees
BST properties, operations, and balanced trees
20 minFull Guide
Lesson 9
Intermediate
Heaps & Priority Queues
Heap data structure, heap operations, and priority queues
18 minFull Guide
Lesson 10
Intermediate
Graphs
Graph representations, BFS, DFS, and graph algorithms
30 minFull Guide
Lesson 11
Intermediate
Sorting Algorithms
Common sorting algorithms: bubble sort, merge sort, quick sort, and more
35 minFull Guide
Lesson 12
Intermediate
Searching Algorithms
Linear search, binary search, and advanced search techniques
20 minFull Guide
Lesson 13
Intermediate
Recursion
Recursive thinking, base cases, and recursive problem solving
22 minFull Guide
Lesson 14
Advanced
Dynamic Programming
Memoization, tabulation, and solving optimization problems
40 minFull Guide
Lesson 15
Advanced
Greedy Algorithms
Greedy approach, optimization problems, and when to use greedy
25 minFull Guide
Lesson 16
Advanced
Backtracking
Backtracking technique for solving constraint satisfaction problems
28 minFull Guide
Lesson 17
Advanced
Tries
Trie data structure for efficient string operations
20 minFull Guide
Lesson 18
Advanced
Advanced Graph Algorithms
Dijkstra's, Bellman-Ford, Floyd-Warshall, and MST algorithms
35 minFull Guide
💡 Why Learn This?
Algorithms and data structures are fundamental to computer science and software engineering:
- 🎯 Technical Interviews: Essential for FAANG and top tech companies
- ⚡ Performance: Write efficient, scalable code
- 🧠 Problem Solving: Develop algorithmic thinking
- 💼 Career Growth: Stand out as a developer