# Awesome Algorithms A curated list of awesome places to learn and/or practice algorithms. Inspired by [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness) and all the other awesome Awesome libraries. If you want to contribute, please read the [contribution guidelines](https://github.com/tayllan/awesome-algorithms/blob/master/CONTRIBUTING.md). - [Awesome Algorithms](#awesome-algorithms) - [Websites](#websites) - [Online Courses](#online-courses) - [Books](#books) - [Github Libraries](#github-libraries) - [Online Judges](#online-judges) - [Tools](#tools) ## Websites *Websites you should use to learn classic algorithms* * [A Visual Guide to Graph Traversal Algorithms](https://workshape.github.io/visual-graph-algorithms/) - Interactive visualisations for learning how graph traversal algorithms work * [Algomation](http://www.algomation.com/) - A didactic, animated, exposition of algorithms. * [Algorithm Visualizer](http://algo-visualizer.jasonpark.me/) - Dozens of animated algorithms (with code), and you can also create your own. * [Algorithms Visualization](http://bost.ocks.org/mike/algorithms/) - A dense article on Algorithms Visualization. * [Big-O Cheat Sheet](http://bigocheatsheet.com/) - Big-O complexities of common algorithms used in Computer Science. * [Code-Drills](https://code-drills.com/tools/comparator) - Practice problems recommender (includes Codeforces, Codechef and Spoj). * [Data Structure Visualizations](http://www.cs.usfca.edu/~galles/visualization/Algorithms.html) - Visualize the behavior of Data Structures and play with its operations. * [Geeks for Geeks](http://www.geeksforgeeks.org/fundamentals-of-algorithms/) - Lots and lots of well explained and implemented algorithms. * [Path Finding](https://qiao.github.io/PathFinding.js/visual/) - 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. * [Rosetta Code](http://rosettacode.org/wiki/Rosetta_Code) - A programming chrestomathy site which aims to present implementations of many algorithms and data structures in different programming languages. * [Sorting Algorithms](http://www.sorting-algorithms.com/) - Nice and simple animations of sorting algorithms. With short codes and discussions. * [Stoimen's web log](http://www.stoimen.com/blog/) - Some algorithms nicely explained. * [The Sound of Sorting](http://panthema.net/2013/sound-of-sorting/) - The Sound of Sorting - "Audibilization" and Visualization of Sorting Algorithms * [VisuAlgo](http://visualgo.net) - Visualising data structures and algorithms through animation. * [Wikipedia - Algorithms](https://en.wikipedia.org/wiki/List_of_algorithms) - Of course!! * [Wikipedia - Data Structures](https://en.wikipedia.org/wiki/List_of_data_structures) - and why not ?!! ## Online Courses *Free and High Quality Courses Online* * [Algorithms: Divide and Conquer, Sorting and Searching, and Randomized Algorithms](https://www.coursera.org/learn/algorithms-divide-conquer) - 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](https://www.coursera.org/learn/algorithms-graphs-data-structures) - The primary topics are: data structures, graph primitives, and their applications. * [Algorithms: Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming](https://www.coursera.org/learn/algorithms-greedy) - The primary topics are: greedy algorithms and dynamic programming. * [Algorithms: Shortest Paths Revisited, NP-Complete Problems and What To Do About Them](https://www.coursera.org/learn/algorithms-npcomplete) - 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](https://www.coursera.org/learn/algorithms-part1/home/welcome) - 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](https://www.coursera.org/learn/algorithms-part2) - Part II focuses on graph- and string-processing algorithms. * [Khan Academy Algorithms](https://www.khanacademy.org/computing/computer-science/algorithms) - Algorithm course ministred by Tomas Cormen and Devin Balkcom. * [MIT - 6-006](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/) - Well explained algorithms. * [MIT - 6-046j](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-introduction-to-algorithms-sma-5503-fall-2005/video-lectures/) - Similar to the previous one, but with different algorithms. * [MIT - 6-00sc](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-00sc-introduction-to-computer-science-and-programming-spring-2011/index.htm) - An easy and well explained introduction to algorithms. * [Udacity Intro to Algorithms](https://www.udacity.com/course/intro-to-algorithms--cs215) - Python-based Algorithms course. * [Algorithms in Motion](https://www.manning.com/livevideo/algorithms-in-motion) - Beginner's algorithms course with fun illustrations, based on the book Grokking Algorithms * ~~[YogiBearian YouTube Channel](https://www.youtube.com/channel/UCv3Kd0guxD5KWQtP---9D6g) - 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* * [Algorithm Design](https://www.pearsonhighered.com/program/Kleinberg-Algorithm-Design/PGM319216.html) - Pretty straight-forward. * [Algorithms](http://algs4.cs.princeton.edu/home/) - Problems explained with Java, OO good practices, visualizations, and free online resources. * [Classic Computer Science Problems in Python](https://www.manning.com/books/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 Using C](http://www.amazon.com/Data-Structures-Using-Aaron-Tenenbaum/dp/0131997467) - The basic concepts and usages of data structures. * [Elementary Algorithms](https://github.com/liuxinyu95/AlgoXY) - An awesome book about algorithms and data structures. * [Grokking Algorithms](http://www.manning.com/bhargava) - An illustrated book on algorithms with practical examples. * [Introduction to Algorithms](http://mitpress.mit.edu/books/introduction-algorithms) - Essential! * [Swift Algorithms & Data Structures](http://shop.waynewbishop.com/) - A practical guide to concepts, theory and code. * [The Algorithm Design Manual](http://www.algorist.com/) - Easy to read and full of real world examples. * [The Art of Computer Programming](http://www-cs-faculty.stanford.edu/~uno/taocp.html) - The Book. * [Structure and Interpretation of Computer Programs](https://mitpress.mit.edu/books/structure-and-interpretation-computer-programs-second-edition) ## Github Libraries *Implementations of the most classic algorithms in a wide variety of programming languages* * [C](https://github.com/fragglet/c-algorithms) * [CoffeeScript](https://github.com/BrunoRB/algorithms.coffee) * 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) * [Erlang](https://github.com/aggelgian/erlang-algorithms) * [Go](https://github.com/arnauddri/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) * 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) * Objective-C * [by @ EvgenyKarkan](https://github.com/EvgenyKarkan/EKAlgorithms) * 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) * 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](https://github.com/vkostyukov/scalacaster) * 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) ## Online Judges *Online Judges to practice what you learned above* * [A2 Online Judge](https://a2oj.com/) - Online Judge and problem archive. * [ACM-ICPC Live Archive](https://icpcarchive.ecs.baylor.edu/) - Hundreds of problems from previous ACM-ICPC Regionals and World Finals. * [AIZU ONLINE JUDGE](http://judge.u-aizu.ac.jp/onlinejudge/) - Japanese Online Judge. * [Algo Muse](http://www.algomuse.appspot.com) - Research based algorithmic problems. * [AtCoder](https://atcoder.jp/) - Japanese programming contest website. * [Baekjoon Online Judge](https://www.acmicpc.net/) - Korean Online Judge. 10000+ problems. Supports 60+ languages. * [CS Academy](https://csacademy.com/) - Holds online contests and IOI practice contests * [CodeChef](https://www.codechef.com/) - More problems and monthly online contests. * [Codeforces ](http://codeforces.com/) - The only programming contests Web 2.0 platform * [Codefights](https://codefights.com/) - Practive programming and tackle out your next tech interview * [CodeMarshal](https://algo.codemarshal.org/) - Real world contests online! * [CodeWars](http://www.codewars.com/) - A website that houses support to solve algorithms in many languages in varying difficulty. * [CoderByte](http://www.coderbyte.com/) - A decent website with algorithm challenges from beginner to advanced levels. Supports most of the popular languages like C++, python, javascript, ruby. * [Firecode](https://www.firecode.io/)- 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. * [HackerEarth ](https://www.hackerearth.com/) - Practice alogrithmic problems & challenges and participate in hiring challenges. * [HackerRank](https://www.hackerrank.com/) - Featured algorithm and functional programming online judges * [HiHoCoder](http://hihocoder.com/) - Chinese and English problem solving practice and recruitment challenge site. * [Infoarena](http://www.infoarena.ro/) - Romanian Online Judge. 1500+ algorithmic problems * [Kattis](https://open.kattis.com/)- Online judge and problem archive * [LavidaOnlineJudge](http://judge.lavida.us) - Korean Online Judge(Half English). 1300+ problems. * [Learneroo Algorithms Tutorials](https://www.learneroo.com/subjects/8) - Learn and practice algorithms by solving challenges online. * [LeetCode](https://leetcode.com/) - Learn algorithms and prepare for interviews. * [PKU JudgeOnline](http://poj.org/) - Chinese Online Judge. * [ProjectEuler](https://projecteuler.net/) - Mathematical problems that can be solved using algorithms (or just a pencil, depends on how much you already know). * [Rosalind](http://rosalind.info/problems/locations/) - A platform for learning bioinformatics and programming through problem solving. * [ShareCode.io ](https://sharecode.io/) - Online Judge and contest host with a lot of algorithmic problems in the archive to practice. * [Snakify](https://snakify.org/) - An introductory Python course with 100+ algorithmic problems and a step-by-step debugger (from Russia). * [SPOJ](http://www.spoj.com/) - More problems. * [TopCoder](https://www.topcoder.com/) - Lots of problems and real world/money worthy problems in Graphic Design, Data Science and Development. * [URI](https://www.urionlinejudge.com.br/judge/login) - Brazilian Online Judge. Not so much problems, but it's growing and it has online contests. * [UVA](https://uva.onlinejudge.org/) - Hundreds of problems (from previous ACM-ICPC Regionals, World Finals and others). ## Tools *Some tools that can help you in the learning of algorithms* * [interactive-coding-challenges](https://github.com/donnemartin/interactive-coding-challenges) - Interactive, test-driven coding challenges (algorithms and data structures). ## License And for the sake of copyleft, here's our license: [![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)](http://creativecommons.org/licenses/by/4.0/) This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).