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Data Structures & Algorithms · JavaScript

Data Structures & Algorithms in JavaScript

Learn data structures and algorithms visually with JavaScript implementations, animations, complexity analysis, and coding problems.

JavaScript12 topicsVisual lessons
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Data Structures & Algorithms in JavaScript

What you'll learn

Think like an engineer, code in JavaScript

  • ✓Understand how every core data structure works in memory
  • ✓Visualize algorithms step by step before writing code
  • ✓Analyze time and space complexity with Big O notation
  • ✓Write clean, idiomatic implementations from scratch
  • ✓Recognize common patterns in coding interview problems
  • ✓Choose the right data structure for real-world tasks
binarySearch.js
1function binarySearch(arr, target) {
2  let left = 0, right = arr.length - 1;
3  while (left <= right) {
4    const mid = Math.floor((left + right) / 2);
5    if (arr[mid] === target) return mid;
6    if (arr[mid] < target) left = mid + 1;
7    else right = mid - 1;
8  }
9  return -1;
10}

Curriculum

Course content

  1. 01

    Big O & Complexity

    Measure time and space so you can compare solutions with confidence.

  2. 02

    Arrays & Strings

    Two pointers, sliding windows, prefix sums and in-place techniques.

  3. 03

    Linked Lists

    Singly and doubly linked lists, fast & slow pointers, reversal.

  4. 04

    Stacks & Queues

    LIFO and FIFO structures, monotonic stacks and deques.

  5. 05

    Hash Tables

    Hashing, collisions and constant-time lookups explained visually.

  6. 06

    Recursion & Backtracking

    Watch the call stack grow and unwind, then generate every solution.

  7. 07

    Sorting & Searching

    Bubble to merge and quick sort, plus binary search on any space.

  8. 08

    Trees & BSTs

    Traversals, balanced trees and binary search tree operations.

  9. 09

    Heaps & Priority Queues

    Heapify step by step and solve top-k and scheduling problems.

  10. 10

    Graphs

    BFS, DFS, shortest paths, topological sort and union-find.

  11. 11

    Greedy Algorithms

    Learn when the locally best choice leads to the global optimum.

  12. 12

    Dynamic Programming

    Memoization and tabulation, built up one table cell at a time.

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