A curated list of awesome places to learn and/or practice algorithms. Inspired by awesome-awesomeness and all the other awesome Awesome libraries.

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• Awesome Algorithms
  • Websites
  • YouTube Playlists
  • Online Courses
  • Books
  • Cheat Sheets
  • Github Libraries
  • Online Judges
  • Tools

Websites you should use to learn classic algorithms

• A Visual Guide to Graph Traversal Algorithms - Interactive visualizations for learning how graph traversal algorithms work.
• W3School - Data Structures tutorial.
• CodeChef - Learning DSA by practice on Codechef
• Algorithm Visualizer - Dozens of animated algorithms (with code), and you can also create your own.
• Algorithms Visualization - A dense article on Algorithms Visualization.
• Big-O Cheat Sheet - Big-O complexities of common algorithms used in Computer Science.
• Code-Drills - Practice problems recommender (includes Codeforces, Codechef, and Spoj).
• CP-Algorithms - Algorithms and data structures are especially popular in the field of competitive programming.
• Data Structure Visualizations - Visualize the behavior of Data Structures and play with its operations.
• Geeks for Geeks - Lots and lots of well-explained and implemented algorithms.
• Path Finding - A visual representation of how algorithms such as A*, IDA*, Breadth-First-Search, Best-First-Search, and others describe a path between two points A and B.
• Programiz - Easy to follow tutorials on data structures and algorithms along with suitable examples.
• Rosetta Code - A programming chrestomathy site that aims to present implementations of many algorithms and data structures in different programming languages.
• Sorting Algorithms - Nice and simple animations of sorting algorithms. With short codes and discussions.
• Stoimen's web log - Some algorithms nicely explained.
• The Sound of Sorting - The Sound of Sorting - "Audibilization" and Visualization of Sorting Algorithms
• VisuAlgo - Visualising data structures and algorithms through animation.
• Wikipedia - Algorithms - Of course!!
• Wikipedia - Data Structures - and why not ?!!
• Learnersbucket - Tutorials on data structures and algorithms in Javascript.
• redblobgames - interactive visual explanations of math and algorithms, using motivating examples from computer games.

High Quality Courses and tutorials on youtube

• FreeCodeCamp - Algorithms and Data Structures Tutorial - Full Course for Beginners - Complete beginner friendly Algorithms and Data Structures Tutorial with mindblowing animation.

• Abdul Bari - Introduction to Algorithm - This playlist is so much informative and provide simulation with code example. As like as you are in a class.

• Jenny's Lectures- Algorithm - Another complete alogrithm playlist from basic level to intermediate. Easy explanation and simulation.

Free and High-Quality Courses Online

• Algorithms: Divide and Conquer, Sorting and Searching, and Randomized Algorithms - The primary topics are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer, and randomized algorithms.
• Algorithms: Graph Search, Shortest Paths, and Data Structures - The primary topics are: data structures, graph primitives, and their applications.
• Algorithms: Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming - The primary topics are: greedy algorithms and dynamic programming.
• Algorithms: Shortest Paths Revisited, NP-Complete Problems and What To Do About Them - The primary topics are: shortest paths, NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems.
• Algorithms, Part I - This course covers the essential information that every serious programmer needs to know about algorithms and data structures. Part I covers elementary data structures, sorting, and searching algorithms.
• Algorithms, Part II - Part II focuses on graph- and string-processing algorithms.
• Khan Academy Algorithms - Algorithm course ministered by Tomas Cormen and Devin Balkcom.
• MIT - 6-006 - Well explained algorithms.
• MIT - 6-046j - Similar to the previous one, but with different algorithms.
• MIT - 6-00sc - An easy and well-explained introduction to algorithms.
• MIT 18-409 - Topics in Theoretical Computer Science: An Algorithmist's Toolkit - It covers a collection of geometric techniques that apply broadly in modern algorithm design.
• Udacity Intro to Algorithms - Python-based Algorithms course.
• Algorithms in Motion - Beginner's algorithms course with fun illustrations, based on the book Grokking Algorithms
• YogiBearian YouTube Channel - Lots of well-explained videos on various computer science subjects. Account terminated due to violations of Youtube Policies.

The most highly regarded books to learn algorithms

• Algorithm Design - Pretty straightforward.
• Algorithms - Problems explained with Java, OO good practices, visualizations, and free online resources.
• Algorithms and Data Structures in JavaScript - Classical algorithms and data structures implemented and explained using JavaScript.
• Algorithms in a Nutshell - by George T. Heineman.
• Classic Computer Science Problems in Python -This great book presents dozens of coding challenges, ranging from simple tasks to clustering data using k-means.
• Data Structures and Algorithms Made Easy - A great way to implement algorithms with their specific programmable tasks.
• Data Structures Using C - The basic concepts and usages of data structures.
• Elementary Algorithms - An awesome book about algorithms and data structures.
• Grokking Algorithms - An illustrated book on algorithms with practical examples.
• Introduction to Algorithms - Essential!
• Real World Algorithms: A Beginner's Guide - An introduction to algorithms for readers with no background in advanced mathematics or computer science.
• Swift Algorithms & Data Structures - A practical guide to concepts, theory, and code.
• The Algorithm Design Manual - Easy to read and full of real-world examples.
• The Art of Computer Programming - The Book.
• Structure and Interpretation of Computer Programs
• Algorithms and Data Structures in Action - A different and a great way to introduce algorithms and data structures that can be used at work.
• Algorithmic Puzzles - A very accessible illustration of algorithms in the forms of puzzles. No programming experience is required!
• Standford CS166 - Standford CS166, a course in the design, analysis, and implementation of data structures.

• Sedgewick & Flajolet. An Introduction to the Analysis of Algorithm - Am advanced complete survey, intended only for the mathematically matured reader.
• McConnell. Analysis of Algorithms - A very accessible and brief book on algorithms analysis, with implemented code included.
• Vrajitoru & Knight. Practical Analysis of Algorithms - A very accessible and brief book on algorithms analysis, with implemented code included.

• Motwani & Raghavan. Randomized Algorithms - A standard classic book.
• Mitzenmacher & Upfal. Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis - Standard text for probability methods and their applications on randomized algorithms.

• The Technical Interview Cheat Sheet
• Princeton DS Cheat Sheet
• CLRS in short
• Rice university DS course in short
• Useful Reddit thread
• Algo Deck - An open-source collection of +200 algorithmic cards.

Implementations of the most classic algorithms in a wide variety of programming languages

• C
  • by @fragglet
  • by @TheAlgorithms
• CoffeeScript
• C#
  • by @shkolovy
  • by @aalhour
  • by @justcoding121
• C++
  • by @xtaci
  • by @PetarV-
  • by @faheel
  • by @sslotin
• Erlang
• Go
  • by @arnauddri
  • by @floyernick
• Java
  • by @jpa99
  • by @phishman3579
  • by @asmolich
  • by @psjava
  • by @jeandersonbc
  • by @pedrovgs
  • by @Erdos-Graph-Framework
  • by @deepak-malik
  • by @yusufcakal
  • by @FarheenB
• JavaScript
  • by @jiayihu
  • by @felipernb
  • by @nzakas
  • by @duereg
  • by @mgechev
  • by @trekhleb
  • by @ManrajGrover
  • by @amejiarosario
  • by @zonayedpca
• Lua
  • by @evandrolg
• Objective-C
  • by @ EvgenyKarkan
• PHP
  • by @TheAlgorithms
• Python
  • by @nryoung
  • by @prakhar1989
  • by @laurentluce
  • by @nbro
  • by @keon
  • by @vinta
• Ruby
  • by @kanwei
  • by @sagivo
  • by @kumar91gopi
• Scala
• Swift
  • by @kingreza
  • by @waynewbishop
  • by @hollance
• Language agnostic
  • by @kennyledet
  • by @indy256
  • by @sagivo
  • by @patmorin
  • by @btjanaka

Online Judges to practice what you learned above

• A2 Online Judge - Online Judge and problem archive.
• ACM-ICPC Live Archive - Hundreds of problems from previous ACM-ICPC Regionals and World Finals.
• AIZU ONLINE JUDGE - Japanese Online Judge.
• Algo Muse - Research-based algorithmic problems.
• AtCoder - Japanese programming contest website.
• Baekjoon Online Judge - Korean Online Judge. 10000+ problems. Supports 60+ languages.
• CS Academy - Holds online contests and IOI practice contests
• CodeChef - More problems and monthly online contests.
• Codeforces - The only programming contests Web 2.0 platform
• Codefights - Practice programming and tackle your next tech interview
• CodeMarshal - Real-world contests online!
• CodeWars - A website that houses support to solve algorithms in many languages in varying difficulty.
• CoderByte - A decent website with algorithm challenges from beginner to advanced levels. Supports most of the popular languages like C++, python, javascript, ruby.
• Firecode - Firecode.io uses machine learning algorithms along with curated real-world interview questions, solutions & a vibrant social community of learners to get you ready for your next coding interview.
• Coding Blocks - Website that has problems based on Maths, Data Structures, Various Algorithm and also conducts Coding Competition.
• HackerEarth - Practice algorithmic problems & challenges and participate in hiring challenges.
• HackerRank - Featured algorithm and functional programming online judges
• HiHoCoder - Chinese and English problem-solving practice and recruitment challenge site.
• Infoarena - Romanian Online Judge. 1500+ algorithmic problems
• Interviewbit - Learn, practice, and prepare for interviews.
• Kattis- Online judge and problem archive
• LavidaOnlineJudge - Korean Online Judge(Half English). 1300+ problems.
• Learneroo Algorithms Tutorials - Learn and practice algorithms by solving challenges online.
• LeetCode - Learn algorithms and prepare for interviews.
• PKU JudgeOnline - Chinese Online Judge.
• ProjectEuler - Mathematical problems that can be solved using algorithms (or just a pencil, depending on how much you already know).
• Rosalind - A platform for learning bioinformatics and programming through problem-solving.
• ShareCode.io - Online Judge and contest host with a lot of algorithmic problems in the archive to practice.
• Snakify - An introductory Python course with 100+ algorithmic problems and a step-by-step debugger (from Russia).
• SPOJ - More problems.
• TopCoder - Lots of problems and real-world/money-worthy problems in Graphic Design, Data Science, and Development.
• Toph - Bangladeshi Online Judge. Holds online contests regularly.
• URI - Brazilian Online Judge. Not so many problems, but it's growing and it has online contests.
• UVA - Hundreds of problems (from previous ACM-ICPC Regionals, World Finals, and others).
• Codility - Compete to land coding jobs at top companies

Awesome list of blogs, mainly for competitive programming but you can refer to these when learning a new topic/algorithm

• An awesome list for competitive programming! - Awesome blog for all the resources and list of books and algorithms.
• Algorithms Weekly - A good blog by Petr Mitrichev, mainly in Java.
• Sport of Programming - Informative blog for starting with the sport of programming.
• Algorithms and Data Structures - For getting a deeper knowledge of algorithms and how to think in the right direction.
• Algorithm Tutorials by Tanuj Khattar - Excellent blog by Tanuj Khattar. Covers tutorials on some interesting data structures along with example problems to solve.

Some tools that can help you in the learning of algorithms

• interactive-coding-challenges - Interactive, test-driven coding challenges (algorithms and data structures).

• Math - Freely available lecture notes on mathematics.
• Theoretical Computer Science - The interdisciplinary of Mathematics and Computer Science, Distinguished by its emphasis on mathematical technique and rigour.

And for the sake of copyleft, here's our license:

This work is licensed under a Creative Commons Attribution 4.0 International License.