60-Day DSA Roadmap

This 60-day roadmap is designed to guide you through learning Data Structures and Algorithms (DSA) from scratch. Each day is structured with specific topics and resources to ensure steady progress.

Day 1: Choose a Programming Language

Choose a programming language you're comfortable with or one that's widely used for DSA. Popular options include:
- C++ (Great for competitive programming)
- Python (Beginner-friendly and versatile)
- Java (Widely used and object-oriented)

Week 1: Basics and Complexity Analysis

Day 2-3: Learn basic syntax of your chosen language.

Day 4-5: Understand time complexity (Big O notation).

Day 6-7: Practice basic algorithms like linear and binary search.

Week 2: Arrays

Day 8-9: Learn about arrays and solve basic problems (max/min, reverse an array).

Day 10-11: Study the two-pointer technique and solve pair sum problems.

Day 12-14: Learn the sliding window technique and solve subarray problems.

Week 3: Strings

Day 15-16: Practice basic string manipulations (palindrome check, frequency count).

Day 17-18: Learn pattern matching algorithms like KMP.

Day 19-21: Solve advanced string problems (longest substring, string compression).

Week 4: Searching and Sorting

Day 22-23: Master binary search and its variations.

Day 24-25: Learn QuickSort, MergeSort, and HeapSort.

Day 26-28: Solve problems like Kth largest element and median of two sorted arrays.

Week 5: Linked Lists

Day 29-30: Learn singly linked lists (insert, delete, traverse).

Day 31-32: Practice reversing a linked list and detecting cycles.

Day 33-35: Solve advanced problems like merging sorted linked lists.

Week 6: Stacks and Queues

Day 36-37: Understand stack operations and solve problems like valid parentheses.

Day 38-39: Learn about queues (normal, circular, deque).

Day 40-42: Solve problems like sliding window maximum and stack using queues.

Week 7: Trees

Day 43-44: Learn binary tree traversal (inorder, preorder, postorder).

Day 45-46: Study Binary Search Trees (BST) and operations.

Day 47-48: Solve tree problems like height calculation and lowest common ancestor.

Week 8: Heaps and Hashing

Day 49-50: Learn heaps and priority queues. Solve Kth largest element.

Day 51-52: Understand hashing concepts and solve problems like two-sum.

Week 9: Graphs

Day 53-54: Learn graph representations (adjacency matrix, list).

Day 55-56: Practice BFS and DFS traversals.

Day 57-58: Solve graph problems like cycle detection and shortest paths.

Week 10: Dynamic Programming

Day 59: Understand the basics of dynamic programming (tabulation vs. memoization).

Day 60: Solve beginner DP problems (Fibonacci, 0/1 Knapsack).