Data Structures and Algorithms roadmap

Before you start

• Computer Science Fundamentals

What you will learn

1. 1. Arrays, Strings & Hashing

   The everyday data structures: arrays, strings, hash tables and sets.

   • Arrays — Data Structures · Arrays
   • Strings — Data Structures · Strings
   • Hash Tables & Sets — Data Structures · Hash Tables & Sets

2. 2. Linked Lists, Stacks & Queues

   Linear structures and when to reach for a linked list, a stack or a queue.

   • Linked Lists — Data Structures · Linked Lists
   • Stacks — Data Structures · Stacks
   • Queues — Data Structures · Queues

3. 3. Searching & Sorting

   Sorting algorithms and binary search, and the trade-offs between them.

   • Sorting — Algorithms · Sorting
   • Searching & Binary Search — Algorithms · Searching & Binary Search

4. 4. Trees & Heaps

   Binary trees and heaps, the structures behind hierarchies and priority queues.

   • Trees & Binary Trees — Data Structures · Trees & Binary Trees
   • Heaps & Priority Queues — Data Structures · Heaps & Priority Queues

5. 5. Graphs & Traversal

   Model relationships as graphs and explore them with BFS and DFS.

   • Graphs — Data Structures · Graphs
   • BFS & DFS — Algorithms · BFS & DFS

6. 6. Two Pointers & Sliding Window

   Two classic patterns that turn quadratic scans over arrays and strings into linear ones.

   • Two Pointers — Algorithms · Two Pointers
   • Sliding Window — Algorithms · Sliding Window

7. 7. Matrices & Prefix Sums

   Work with grids and matrices and answer range queries fast with prefix sums.

   • Matrices — Data Structures · Matrices
   • Prefix Sum — Algorithms · Prefix Sum

8. 8. Tree Traversal & Divide and Conquer

   Recursive algorithms that split a problem into smaller ones: tree traversals and divide and conquer.

   • Tree Traversal — Algorithms · Tree Traversal
   • Divide and Conquer — Algorithms · Divide and Conquer

9. 9. Greedy & Intervals

   Greedy choices and the interval problems, like merging and scheduling, where they shine.

   • Greedy — Algorithms · Greedy
   • Intervals — Algorithms · Intervals

10. 10. Search Trees, Tries & String Algorithms

    Ordered lookups with binary search trees, prefix search with tries and classic string algorithms.

    • Binary Search Trees — Data Structures · Binary Search Trees
    • Tries — Data Structures · Tries
    • String Algorithms — Algorithms · String Algorithms

11. 11. Backtracking & Dynamic Programming

    Search solution spaces with backtracking and avoid repeated work with dynamic programming.

    • Recursion & Backtracking — Algorithms · Recursion & Backtracking
    • Dynamic Programming — Algorithms · Dynamic Programming

12. 12. Advanced Graph Algorithms

    Topological sort, shortest paths and union-find for dependency, routing and connectivity problems.

    • Topological Sort — Algorithms · Topological Sort
    • Shortest Paths — Algorithms · Shortest Paths
    • Disjoint Set — Data Structures · Disjoint Set
    • Union Find — Algorithms · Union Find