๐ป DSA Learning Roadmap 2026
If you're starting Data Structures & Algorithms from scratch, follow this order and practice each topic before moving ahead.
๐ข Part 1 โ Programming Fundamentals
โข Variables and data types, Operators, Conditions, Loops, Functions
โข Recursion basics, Arrays and strings, Input/output, Basic problem solving
๐ฏ Goal: Become comfortable writing code before starting DSA.
๐ข Part 2 โ Complexity Analysis
โข Time complexity, Space complexity, Big O notation, Big ฮฉ, Big ฮ
โข Best, average and worst case, Comparing algorithms, Complexity of common operations
๐ฏ Goal: Learn to judge whether a solution is efficient.
๐ก Part 3 โ Arrays
โข Traversal, Searching, Insertion and deletion, Prefix sums
โข Two pointers, Sliding window, Kadane's algorithm, Sorting-based problems, Subarrays
๐ฏ Goal: Solve common array problems efficiently.
๐ก Part 4 โ Strings
โข String manipulation, Character frequency, Palindromes, Anagrams, Substrings
โข Two pointers, Sliding window, String hashing basics
๐ก Part 5 โ Searching & Sorting
Learn:
โข Searching: Linear search, Binary search, Binary search on answer
โข Sorting: Bubble sort, Selection sort, Insertion sort, Merge sort, Quick sort, Counting sort, Heap sort
๐ฏ Goal: Understand both the algorithms and when to use them.
๐ต Part 6 โ Linked Lists
โข Singly linked list, Doubly linked list, Circular linked list
โข Insert/delete, Reverse a linked list, Fast & slow pointers, Cycle detection, Merge linked lists, Find middle node
๐ต Part 7 โ Stack & Queue
โข Stack: Push/pop, Applications, Balanced parentheses, Monotonic stack, Next greater element
โข Queue: Enqueue/dequeue, Circular queue, Deque, Priority queue
๐ฃ Part 8 โ Hashing
โข Hash tables, Hash maps, Hash sets, Frequency counting
โข Duplicate detection, Two-sum pattern, Prefix-sum + hashing, Collision concepts
๐ฏ Goal: Learn how hashing can reduce many problems from O(nยฒ) to O(n).
๐ฃ Part 9 โ Recursion & Backtracking
โข Recursion fundamentals, Base cases, Recursive trees
โข Subsets, Subsequences, Permutations, Combination problems, N-Queens, Sudoku, Maze problems
๐ Part 10 โ Trees
โข Binary trees, Tree terminology, DFS, BFS, Preorder, Inorder, Postorder, Level-order traversal
โข Height/depth, Diameter, Balanced trees, Lowest Common Ancestor
๐ Part 11 โ Binary Search Trees
โข BST properties, Search, Insert, Delete, Minimum/maximum, Successor/predecessor, Validate BST, LCA in BST
๐ด Part 12 โ Heap & Priority Queue
โข Min heap, Max heap, Heapify, Insert/delete, Priority queue
โข Top K problems, Kth largest/smallest, Heap sort, Merge K sorted lists
๐ด Part 13 โ Graphs
โข Graph representation, Adjacency matrix, Adjacency list, BFS, DFS
โข Connected components, Cycle detection, Bipartite graphs, Topological sorting
๐ด Part 14 โ Advanced Graph Algorithms
โข Dijkstra, Bellman-Ford, Floyd-Warshall, Minimum Spanning Tree
โข Prim's algorithm, Kruskal's algorithm, Disjoint Set Union, Strongly connected components, Shortest paths
๐ค Part 15 โ Greedy Algorithms
โข Greedy strategy, Activity selection, Fractional knapsack, Job scheduling, Interval problems, Minimum platforms, Huffman coding
๐ฏ Goal: Learn when making the locally optimal choice leads to a global solution.
