Awesome Algorithms

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
  • Online Courses
  • Books
  • Cheat Sheets
  • Github Libraries
  • Online Judges
  • Tools

Websites

Websites you should use to learn classic algorithms

• A Visual Guide to Graph Traversal Algorithms - Interactive visualisations 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 especially popular in 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 on 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 which 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 sturctures and algorithms in Javascript.
• redblobgames - interactive visual explanations of math and algorithms, using motivating examples from computer games.

Online Courses

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 ministred 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.
• 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 vidoes on various computer science subjects. Account terminated due to violations of Youtube Policies.

Books

The most highly regarded books to learn algorithms

Algorithms and Data structures

• Algorithm Design - Pretty straight-forward.
• 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 forms of puzzles. No programming experience is required!

Algorithm Analysis

• 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.

Randomized Algorithms

• 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.

Cheat Sheets

• 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.

Github Libraries

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

• C
  • [by @fragglet](https://github.com/fragglet/c-algorithms)
  • [by @TheAlgorithms](https://github.com/TheAlgorithms/C)
• CoffeeScript
• C#
  • [by @shkolovy](https://github.com/shkolovy/classic-algorithms)
  • [by @aalhour](https://github.com/aalhour/C-Sharp-Algorithms)
  • [by @justcoding121](https://github.com/justcoding121/Advanced-Algorithms)
• C++
  • [by @xtaci](https://github.com/xtaci/algorithms)
  • [by @PetarV-](https://github.com/PetarV-/Algorithms)
  • [by @faheel](https://github.com/faheel/Algos)
  • [by @sslotin](http://github.com/sslotin/algo)
• Erlang
• Go
  • [by @arnauddri](https://github.com/arnauddri/algorithms)
  • [by @floyernick](https://github.com/floyernick/Data-Structures-and-Algorithms)
• Java
  • [by @jpa99](https://github.com/jpa99/Algorithms)
  • [by @phishman3579](https://github.com/phishman3579/java-algorithms-implementation)
  • [by @asmolich](https://github.com/asmolich/algorithms)
  • [by @psjava](https://github.com/psjava/psjava)
  • [by @jeandersonbc](https://github.com/jeandersonbc/algorithms-and-ds)
  • [by @pedrovgs](https://github.com/pedrovgs/Algorithms)
  • [by @Erdos-Graph-Framework](https://github.com/Erdos-Graph-Framework/Erdos)
  • [by @deepak-malik](https://github.com/deepak-malik/Data-Structures-In-Java)
  • [by @yusufcakal](https://github.com/yusufcakal/algorithms)
  • [by @FarheenB](https://github.com/FarheenB/Data-Structures-and-Algorithms)
• JavaScript
  • [by @jiayihu](https://github.com/jiayihu/pretty-algorithms)
  • [by @felipernb](https://github.com/felipernb/algorithms.js)
  • [by @nzakas](https://github.com/nzakas/computer-science-in-javascript)
  • [by @duereg](https://github.com/duereg/js-algorithms)
  • [by @mgechev](https://github.com/mgechev/javascript-algorithms)
  • [by @trekhleb](https://github.com/trekhleb/javascript-algorithms)
  • [by @ManrajGrover](https://github.com/ManrajGrover/algorithms-js)
  • [by @amejiarosario](https://github.com/amejiarosario/dsa.js)
  • [by @zonayedpca](https://github.com/zonayedpca/AlgoDS.js)
• Lua
  • [by @evandrolg](https://github.com/EvandroLG/computer_science_in_lua)
• Objective-C
  • by @ EvgenyKarkan
• PHP
  • [by @TheAlgorithms](https://github.com/TheAlgorithms/PHP)
• Python
  • [by @nryoung](https://github.com/nryoung/algorithms)
  • [by @prakhar1989](https://github.com/prakhar1989/Algorithms)
  • [by @laurentluce](https://github.com/laurentluce/python-algorithms)
  • [by @nbro](https://github.com/nbro/ands)
  • [by @keon](https://github.com/keon/algorithms)
  • [by @vinta](https://github.com/vinta/fuck-coding-interviews)
• Ruby
  • [by @kanwei](https://github.com/kanwei/algorithms)
  • [by @sagivo](https://github.com/sagivo/algorithms)
  • [by @kumar91gopi](https://github.com/kumar91gopi/Algorithms-and-Data-Structures-in-Ruby)
• Scala
• Swift
  • [by @kingreza](https://github.com/kingreza/Swift-Algorithms-Strings-)
  • [by @waynewbishop](https://github.com/waynewbishop/SwiftStructures)
  • [by @hollance](https://github.com/hollance/swift-algorithm-club)
• Language agnostic
  • [by @kennyledet](https://github.com/kennyledet/Algorithm-Implementations)
  • [by @indy256](https://github.com/indy256/codelibrary)
  • [by @sagivo](https://github.com/sagivo/algorithms)
  • [by @patmorin](https://github.com/patmorin/ods)
  • [by @btjanaka](https://github.com/btjanaka/algorithm-problems)

Online Judges

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 - Practive programming and tackle out 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 have problems based on Maths, Data Structures, Various Algorithm and also conducts Coding Competition.
• HackerEarth - Practice alogrithmic 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, depends 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 on a regular basis.
• URI - Brazilian Online Judge. Not so much 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

Blogs

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 - Really informative blog for starting with the sport of programming.
• Algorithms and Data Structures - For getting deeper knowledge of algorithms and how to think in 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.

Tools

Some tools that can help you in the learning of algorithms

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

Related Awesome Lists

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

License

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

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