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tayllan/awesome-algorithms

Analysis updated 2026-06-21

25,082Audience · developerComplexity · 1/5Setup · easy

TLDR

A curated directory of the best places online to learn and practice algorithms, covering videos, books, interactive tools, and coding challenge platforms, organized by skill level.

Mindmap

mindmap
  root((Awesome Algorithms))
    For beginners
      YouTube playlists
      Visual tools
      Intro books
    Interview prep
      LeetCode
      Cheat sheets
    Competitions
      Codeforces
      HackerEarth
    Deep study
      Textbooks
      MIT lectures
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

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What do people build with it?

USE CASE 1

Find beginner-friendly YouTube playlists and interactive tools to start learning algorithms from scratch.

USE CASE 2

Prepare for technical job interviews using curated LeetCode, HackerEarth, and cheat-sheet resources.

USE CASE 3

Discover competitive programming platforms like Codeforces for contest preparation.

USE CASE 4

Locate classic textbooks and MIT lecture series for deep theoretical study of algorithms.

How does it compare?

tayllan/awesome-algorithmspypa/pipenvicsharpcode/ilspy
Stars25,08225,07825,093
LanguagePythonC#
Setup difficultyeasyeasyeasy
Complexity1/52/52/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
The explanation does not mention a license.

In plain English

Awesome Algorithms is a curated collection of links pointing to the best places on the internet to learn or practice algorithms. Algorithms are step-by-step problem-solving procedures used in software, sorting a list, searching a database, finding the shortest path on a map, and learning them is a core part of becoming a developer or passing technical job interviews. This repository does not contain code itself, it is a directory of resources organized by audience and purpose. Beginners can find YouTube playlists (including Khan Academy and FreeCodeCamp), introductory books, and interactive visualization tools like VisuAlgo that animate how algorithms work step by step. Those preparing for programming contests will find links to competitive coding platforms such as LeetCode, Codeforces, and HackerEarth. There are also sections covering theoretical textbooks like the classic "Introduction to Algorithms," MIT OpenCourseWare lecture series, cheat sheets for interview preparation, and specialty topics like database query optimization and distributed systems. You would use this list if you are a student learning computer science fundamentals, a developer preparing for job interviews, or someone entering programming competitions and wanting to know where to start. There is no single programming language required, the linked resources span Python, JavaScript, Java, and more.

Copy-paste prompts

Prompt 1
I'm a beginner with no CS background, which resources from awesome-algorithms should I start with to learn sorting and searching?
Prompt 2
I have a coding interview in 2 weeks, give me a study plan using the resources listed in awesome-algorithms.
Prompt 3
What's the best way to use VisuAlgo (linked from awesome-algorithms) to understand how quicksort works step by step?
Prompt 4
Point me to the competitive programming resources in awesome-algorithms that are best for someone who already knows Python.

Frequently asked questions

What is awesome-algorithms?

A curated directory of the best places online to learn and practice algorithms, covering videos, books, interactive tools, and coding challenge platforms, organized by skill level.

What license does awesome-algorithms use?

The explanation does not mention a license.

How hard is awesome-algorithms to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is awesome-algorithms for?

Mainly developer.

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