Data Structures & Algorithms (DSA)

Data Structures and Algorithms (DSA) form the foundation of problem-solving in coding interviews. Mastering DSA concepts helps you crack technical interviews efficiently and develop strong programming fundamentals. This catalog is designed to guide learners from beginner to advanced levels, with AI-powered mock interviews, curated coding challenges, and instant feedback.

Beginner Level

Introduction to Data Structures and Algorithms
Time and Space Complexity Analysis (Big O Notation)
Arrays and Strings: Basic operations, Two-Pointer technique
Linked Lists: Singly, Doubly, Circular
Stacks and Queues: Implementation using Arrays and Linked Lists
Recursion: Base cases, Recursive trees, Backtracking basics
Sorting Algorithms: Bubble, Selection, Insertion, Merge, Quick Sort
Searching Algorithms: Linear Search, Binary Search

Intermediate Level

Hashing: Hash Tables, Collision Handling
Recursion & Backtracking: Permutations, N-Queens, Subsets
Trees: Binary Trees, Binary Search Trees, Tree Traversals
Heaps and Priority Queues: Min Heap, Max Heap, Heap Sort
Graphs: Adjacency Matrix/List, BFS, DFS
Sliding Window Technique
Greedy Algorithms: Activity Selection, Huffman Coding
Dynamic Programming Basics: Fibonacci, Knapsack, Coin Change

Advanced Level

Advanced Trees: AVL Trees, Red-Black Trees, Segment Trees, Trie
Advanced Graph Algorithms: Dijkstra, Floyd-Warshall, Bellman-Ford, Topological Sort
Bit Manipulation Techniques
Advanced Dynamic Programming: LCS, LIS, Matrix Chain Multiplication
Disjoint Set Union: Union-Find, Kruskal’s Algorithm
String Algorithms: KMP, Rabin-Karp, Z-Algorithm
Computational Geometry: Convex Hull, Line Intersection

Enhance your problem-solving skills with structured learning, hands-on coding challenges, and instant AI-powered feedback to confidently prepare for top tech interviews.

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