Here’s a step-by-step DSA (Data Structures and Algorithms) Syllabus for beginners:
Step 1: Introduction to DSA
- What is Data Structure?
- What is an Algorithm?
- Importance of DSA in Coding and Interviews
- Complexity Analysis (Time & Space Complexity)
- Big O Notation, Omega (Ω), and Theta (Θ)
Step 2: Basic Data Structures
1. Arrays
- Introduction & Memory Representation
- Operations (Insertion, Deletion, Traversal, Searching)
- Two-Pointer Technique
- Sorting Basics (Bubble Sort, Selection Sort, Insertion Sort)
- Searching Algorithms (Linear Search, Binary Search)
2. Strings
- String Manipulation & Common Functions
- Pattern Matching Algorithms (Naïve, KMP, Rabin-Karp)
- Anagram Problems
- Palindrome Checking
3. Linked List
- Types (Singly, Doubly, Circular)
- Operations (Insertion, Deletion, Reversal, Searching)
- Detecting Loops (Floyd’s Cycle Detection Algorithm)
- Merge Two Sorted Linked Lists
4. Stack & Queue
- Stack (LIFO Principle, Applications – Undo, Recursion)
- Queue (FIFO Principle, Applications – Scheduling)
- Implementation using Arrays & Linked List
- Special Queues (Deque, Priority Queue)
Step 3: Recursion & Backtracking
- Basics of Recursion (Base Case, Recursive Case)
- Factorial, Fibonacci, Tower of Hanoi
- Backtracking (N-Queens, Sudoku Solver, Rat in a Maze)
Step 4: Advanced Data Structures
1. Trees
- Binary Tree Basics
- Tree Traversal (Inorder, Preorder, Postorder)
- Binary Search Tree (BST) & Operations
- Lowest Common Ancestor (LCA) Problem
- AVL Trees, B-Trees (Introduction)
2. Heaps
- Min Heap & Max Heap
- Heapify & Heap Sort
- Priority Queue using Heap
3. Graphs
- Graph Representation (Adjacency Matrix & List)
- BFS (Breadth-First Search)
- DFS (Depth-First Search)
- Shortest Path Algorithms (Dijkstra’s, Bellman-Ford)
- Minimum Spanning Tree (Kruskal’s, Prim’s)
- Topological Sorting
Step 5: Greedy & Divide and Conquer Algorithms
- Greedy Algorithms (Activity Selection, Huffman Coding)
- Divide & Conquer (Merge Sort, Quick Sort)
- Binary Search Variations
Step 6: Dynamic Programming (DP)
- Introduction to DP (Top-Down & Bottom-Up Approach)
- Fibonacci Using DP
- Knapsack Problem (0/1 Knapsack)
- Longest Common Subsequence (LCS)
- Matrix Chain Multiplication
- DP on Trees & Graphs
Step 7: Advanced Topics
- Bit Manipulation
- Disjoint Set Union (DSU)
- Trie Data Structure
- Segment Trees & Fenwick Tree
- String Algorithms (Z-Algorithm, Aho-Corasick)
- Computational Geometry (Convex Hull, Line Intersection)
Step 8: Practice & Competitive Programming
- Solve problems on platforms like LeetCode, CodeChef, Codeforces
- Participate in Contests
- Work on real-world applications of DSA (Pathfinding, Scheduling, AI-based search)
