DSA Example

javascript

// A Map replaces the nested loop.
function twoSum(nums, target) {
  const seen = new Map()
  for (let i = 0; i < nums.length; i++) {
    const need = target - nums[i]
    if (seen.has(need)) {
      return [seen.get(need), i]
    }
    seen.set(nums[i], i)
  }
}

Guided tutorial track

DSA Tutorial

Learn data structures and algorithms in JavaScript — arrays, hash maps, trees, graphs, recursion and the patterns interviews actually ask about.

Start learning

Tutorial overview

Start here, then move through the chapters

This tutorial is designed to be followed in order. Read the chapter, practice with the editor, test your understanding, and move toward completion.

Lessons

Sections

Access

Free

Level

intermediate

Ready to begin?

Start with lesson one and follow the tutorial step by step.

Open first lesson

This tutorial teaches data structures and algorithms in plain JavaScript - from what Big O actually measures to the handful of patterns that most interview questions turn out to be. Every example runs in the editor on the page, and every chapter says when the technique is the wrong choice.

The same lookup, two structures

javascript

const users = [
  { id: 1, name: "Ada" },
  { id: 2, name: "Grace" },
]

// Array: check each entry until you find it. O(n).
function findInArray(id) {
  for (const user of users) {
    if (user.id === id) return user
  }
}

// Map: jump straight to it. O(1).
const byId = new Map(users.map((u) => [u.id, u]))

console.log(findInArray(2).name)  // "Grace"
console.log(byId.get(2).name)     // "Grace"

What DSA actually means

A data structure is how you arrange data - an array, a Map, a tree. A algorithm is what you do with it - search, sort, count, find a path.

They are not separate subjects. Choosing the structure is usually most of the work, and the algorithm falls out of that choice. The two functions beside this do the same job; one of them stops being usable at ten million records.

Why it is worth your time

Two reasons, and only one of them is interviews.

The first is that it is what interviews test, at almost every company that pays well. Not because you will implement a red-black tree at work, but because it is a fast way to see whether you can reason about cost.

The second matters more day to day: it is the difference between a page that loads instantly and one that times out. A nested loop over a list that grew from 200 rows to 200,000 is the single most common cause of code that worked fine last year and does not now.

What this tutorial covers

Complexity - Big O, time against space, and why amortised is a stronger promise than average.
Core structures - arrays, strings, hash maps, stacks, queues, linked lists, heaps, trees, tries, graphs.
Core techniques - recursion, backtracking, sorting, searching, dynamic programming, greedy.
Specialised topics - intervals, prefix sums and Fenwick trees, bit manipulation, number theory, matrices.
Interview patterns - how to recognise which technique a question is asking for, and how to talk through it.

Twenty-five sections and fifty-four chapters, in a deliberate order: nothing uses an idea you have not met yet.

Two pointers, in the editor

javascript

// Find the pair that adds to the target, in one pass over a sorted array.
function twoSumSorted(sorted, target) {
  let left = 0
  let right = sorted.length - 1

  while (left < right) {
    const sum = sorted[left] + sorted[right]
    if (sum === target) return [left, right]
    if (sum < target) left++
    else right--
  }

  return []
}

console.log(twoSumSorted([1, 3, 4, 6, 8, 11], 10))  // [2, 3]

Everything here runs

Every code block on this site has a Run button. Press it, change a number, run it again - that loop is worth more than reading three explanations.

Each chapter also carries ten practice problems: five to write from scratch and five where you are given working-looking code with one bug in it. The bug-fix half is closer to real work than the blank-page half.

What you need before you start

Comfortable JavaScript: functions, loops, arrays, objects, and the difference between const and let. If any of that is shaky, work through the JavaScript tutorial first - this one moves quickly and assumes it.

You do not need maths beyond arithmetic. Big O looks like maths and is really a way of describing shape: does the work double when the input doubles, or square?

How long this takes

The first third - complexity, arrays, strings, hash maps, two pointers - is a week of evenings, and it is the part that pays off immediately in ordinary code.

Trees, graphs and dynamic programming take longer, because the difficulty is not syntax but recognising the shape of a problem. That recognition only comes from doing the exercises, not from reading the chapters.

Nobody learns this once. You will forget how to write a heap, look it up, and remember it faster the second time. That is the normal path, not a sign you missed something.

Common questions

No. The ideas are the same in every language, and interviewers at almost every company let you answer in whichever one you know best. JavaScript's one genuine gap is that it ships no priority queue, so the heaps chapter writes one from scratch.

The learning path

Work through these in order. Each part builds on the one before it, and every part lists what it covers and roughly how long it takes.

Part 1Beginner

DSA Introduction

2 lessons12 min

What Are Data Structures and Algorithms · How to Approach a DSA Problem

DSA Tutorial

Start here, then move through the chapters

What DSA actually means

Why it is worth your time

What this tutorial covers

Everything here runs

What you need before you start

How long this takes

Common questions

Do I need to know a language other than JavaScript?

Should I learn DSA before or after React?

How many problems do I need to solve?

Is it still worth learning with AI writing code?

Do I need to memorise the algorithms?

The learning path

What You Will Learn

Practice Live

Tutorial Features

Code examples inside chapters

Practice with the Try It Editor

Quiz for self-check

Certificate after completion

How to Use This Tutorial

Learn the chapter

Practice the example

Test your understanding

Finish with proof

Complete the tutorial with confidence

Why Learn DSA

Easy to Learn

Essential Skill

Build Real Websites