DSA ROADMAP For Beginners.

[SajalJha]

DSA ROADMAP

1. Basics of Programming

• Languages: Choose a language like C++, Java, or Python.
• Key Concepts:
  • Variables, Data Types
  • Loops (for, while)
  • Conditional Statements (if-else, switch)
  • Functions and Recursion
  • Time and Space Complexity (Big-O Notation)

2. Basic Data Structures

• Arrays:
  • Introduction to arrays and their types (1D, 2D)
  • Operations: traversal, insertion, deletion
  • Basic problems (e.g., reverse an array, find the largest element)
• Strings:
  • String manipulation, concatenation, comparison
  • Problems like palindrome check, anagram, substring search
• Linked Lists:
  • Singly Linked List: insertion, deletion, traversal
  • Doubly Linked List: insertion, deletion, traversal
  • Circular Linked List basics
  • Problems like detecting cycles (Floyd’s cycle detection)
• Stacks:
  • Stack using arrays and linked lists
  • Operations: push, pop, top, isEmpty
  • Applications: balanced parentheses, reverse a string
• Queues:
  • Queue using arrays and linked lists
  • Circular Queue
  • Priority Queue (introduction)
  • Problems like the first non-repeating character in a stream

3. Recursion and Backtracking

• Learn the concept of recursion and base conditions.
• Key Recursion Problems: Tower of Hanoi, Fibonacci series, factorials, subsets

4. Sorting and Searching Algorithms

• Sorting Algorithms:
  • Bubble Sort
  • Selection Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
• Searching Algorithms:
  • Linear Search
  • Binary Search (very important)
  • Problems: First/last occurrence in a sorted array, search in a rotated sorted array

5. Advanced Data Structures

• Trees:
  • Binary Trees: Preorder, Inorder, Postorder traversal
  • Binary Search Trees (BST): insertion, deletion, traversal
  • Problems: LCA (Lowest Common Ancestor), height of a tree, diameter of a tree
• Heaps:
  • Introduction to Min-Heap and Max-Heap
  • Priority Queue implementation using Heaps
  • Heap sort algorithm
• Hashing:
  • Hash Tables and Hash Maps
  • Collision resolution techniques
  • Problems like finding duplicates, count of each element in an array

6. Dynamic Programming

• Introduction to DP: Memoization vs Tabulation
• Key Problems:
  • 0/1 Knapsack
  • Longest Common Subsequence (LCS)
  • Longest Increasing Subsequence (LIS)
  • Coin change problem
  • Edit Distance

7. Graphs

• Basic Graph Representations:
  • Adjacency Matrix and Adjacency List
  • BFS (Breadth-First Search)
  • DFS (Depth-First Search)
• Graph Algorithms:
  • Dijkstra’s Shortest Path Algorithm
  • Floyd-Warshall Algorithm
  • Bellman-Ford Algorithm
  • Minimum Spanning Tree (Kruskal, Prim)
  • Problems like detecting cycles, connected components, bipartite check

8. Greedy Algorithms

• Greedy Algorithm Concept
• Key Problems:
  • Activity Selection Problem
  • Fractional Knapsack
  • Job Sequencing Problem
  • Huffman Coding

9. Advanced Topics

• Backtracking: Problems like n-queens, solving a maze
• Trie Data Structure: Used for efficient searching and prefix problems
• Segment Trees: Used for range query problems
• Disjoint Set (Union-Find): Used for connected components and cycle detection in graphs

10. Practice and Competitive Programming

• Practice on platforms like LeetCode, HackerRank, Codeforces, and GeeksforGeeks.
• Solve problems of increasing difficulty (Easy → Medium → Hard).
• Take part in contests to improve problem-solving speed.

Recommended Learning Path:

• 1. Basics → 2. Sorting/Searching → 3. Recursion/Backtracking → 4. Data Structures → 5. Dynamic Programming → 6. Graphs → 7. Advanced Topics

Personal Recommendations for Practice and Learning

• Arsh DSA Sheet (ProElevate) - A structured DSA sheet for practice
• CodeHelp DSA YouTube Playlist - Great beginner-friendly YouTube playlist
• Striver's DSA YouTube Playlist - Advanced DSA concepts explained
• GeeksforGeeks DSA Tutorial - Comprehensive tutorials for DSA

Popular Coding Platforms to Practice

• LeetCode
• HackerRank
• Codeforces
• CodeChef