{"id":13415921,"url":"https://github.com/learn-anything/courses","last_synced_at":"2025-05-03T19:31:49.872Z","repository":{"id":41271407,"uuid":"93441989","full_name":"learn-anything/courses","owner":"learn-anything","description":"Awesome Courses","archived":false,"fork":false,"pushed_at":"2022-02-24T12:08:44.000Z","size":195,"stargazers_count":1054,"open_issues_count":2,"forks_count":181,"subscribers_count":53,"default_branch":"master","last_synced_at":"2024-05-23T08:03:35.629Z","etag":null,"topics":["awesome","awesome-list","courses","education","learning","list","resources"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/learn-anything.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":"contributing.md","funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-06-05T20:05:54.000Z","updated_at":"2024-05-20T09:48:31.000Z","dependencies_parsed_at":"2022-07-13T15:59:41.727Z","dependency_job_id":null,"html_url":"https://github.com/learn-anything/courses","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/learn-anything%2Fcourses","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/learn-anything%2Fcourses/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/learn-anything%2Fcourses/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/learn-anything%2Fcourses/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/learn-anything","download_url":"https://codeload.github.com/learn-anything/courses/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224370617,"owners_count":17300075,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["awesome","awesome-list","courses","education","learning","list","resources"],"created_at":"2024-07-30T21:00:53.053Z","updated_at":"2024-11-13T01:18:32.253Z","avatar_url":"https://github.com/learn-anything.png","language":null,"readme":"# Courses [![Lists](https://img.shields.io/badge/-more%20lists-0a0a0a.svg?style=flat\u0026colorA=0a0a0a)](https://github.com/learn-anything/curated-lists)\n\n_Please read [contribution guidelines](contributing.md) before contributing._\n\n- [Algorithms](#algorithms)\n- [Artificial Intelligence](#artificial-intelligence)\n- [Business](#business)\n- [Chemistry](#chemistry)\n- [Compilers](#compilers)\n- [Computer Science](#computer-science)\n- [Computer vision](#computer-vision)\n- [Cryptocurrency](#cryptocurrency)\n- [Cryptography](#cryptography)\n- [CSS](#css)\n- [Decentralized systems](#decentralized-systems)\n- [Deep Learning](#deep-learning)\n- [Discrete math](#discrete-math)\n- [Functional programming](#functional-programming)\n- [Game development](#game-development)\n- [Haskell](#haskell)\n- [Investing](#investing)\n- [iOS](#ios)\n- [Machine learning](#machine-learning)\n- [Math](#math)\n- [Networking](#networking)\n- [Neuroscience](#neuroscience)\n- [Natural Language Processing](#natural-language-processing)\n- [Operating systems](#operating-systems)\n- [Programming](#programming)\n- [React](#react)\n- [ReasonML](#reasonml)\n- [Rust](#rust)\n- [Scala](#scala)\n- [Security](#security)\n- [Statistics](#statistics)\n- [Swift](#swift)\n- [Type theory](#type-theory)\n- [Vim](#vim)\n- [Web Development](#web-development)\n- [Related](#related)\n\n## Algorithms\n\n- [Algorithmic thinking](https://www.coursera.org/learn/algorithmic-thinking-1) 💰\n- [Algorithms (2010)](http://www.cs.cmu.edu/afs/cs/academic/class/15451-f10/www/) - Taught by Manuel Blum who has a Turing Award due to his contributions to algorithms. 🆓\n- [Algorithms specialization](https://www.coursera.org/specializations/algorithms)\n- [Algorithms: Part 1](https://www.coursera.org/learn/algorithms-part1/home/welcome) 🆓\n- [Algorithms: Part 2](https://www.coursera.org/learn/algorithms-part2) 🆓\n- [Data structures (2016)](http://datastructur.es/sp16/) 🆓\n- [Data structures (2017)](http://datastructur.es/sp17/) 🆓\n- [Design and analysis of algorithms (2012)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/) 🆓\n- [Evolutionary computation (2014)](https://courses2.cit.cornell.edu/cs5724/) 🆓\n- [Introduction to programming contests (2012)](http://web.stanford.edu/class/cs97si/) 🆓\n- [MIT advanced data structures (2014)](http://courses.csail.mit.edu/6.851/spring14/index.html) 🆓\n- [MIT introduction to algorithms](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/) 🆓\n\n## Artificial Intelligence\n\n- [Berkeley intro to ai (2014)](http://ai.berkeley.edu/home.html) 🆓\n- [MIT artificial intelligence (2010)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/) 🆓\n- [The society of mind (2011)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/index.htm) 🆓\n\n## Business\n\n- [Gamification](https://www.coursera.org/learn/gamification) 💰\n\n## Chemistry\n\n- [Bioinformatics specialization](https://www.coursera.org/specializations/bioinformatics) 💰\n\n## Compilers\n\n- [Principles of compiler design (2016)](https://www.cs.swarthmore.edu/%7Ejpolitz/cs75/s16/s_schedule.html) 🆓\n- [Stanford compiler construction (2016)](https://web.stanford.edu/class/cs143/) 🆓\n\n## Computer Science\n\n- [Computational complexity (2008)](https://people.eecs.berkeley.edu/~luca/cs278-08/) 🆓\n- [Computer science 101](https://lagunita.stanford.edu/courses/Engineering/CS101/Summer2014/about) 🆓\n- [Data structures](https://www.coursera.org/learn/data-structures) 💰\n- [Great ideas in computer architecture (2015)](http://www-inst.eecs.berkeley.edu/%7Ecs61c/sp15/) 🆓\n- [Information retrieval (2013)](http://www.cs.cornell.edu/courses/cs4300/2013fa/) 🆓\n- [MIT great ideas in theoretical computer science](https://stellar.mit.edu/S/course/6/sp15/6.045/materials.html) 🆓\n- [MIT Mathematics for Computer Science (2010)](https://www.youtube.com/playlist?list=PLB7540DEDD482705B) 🆓\n- [MIT Structure and Interpretation of Programs (1986)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/video-lectures/) 🆓\n- [Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexity (2018)](https://www.edx.org/course/efficient-quantum-computing-fault-tolerance-and-complexity) 🆓\n- [Software foundations (2014)](http://www.seas.upenn.edu/%7Ecis500/cis500-f14/index.html) 🆓\n- [The art of recursion (2012)](http://www.cis.upenn.edu/~cis39903/) 🆓\n\n## Computer vision\n\n- [Computer vision](http://crcv.ucf.edu/courses/CAP5415/) 🆓\n- [Introduction to computer vision (2015)](http://www.cs.cornell.edu/courses/cs4670/2015sp/lectures/lectures.html) 🆓\n- [Programming computer vision with python (2012)](http://programmingcomputervision.com/) 🆓\n\n## Cryptocurrency\n\n- [Bitcoin and Cryptocurrency Technologies](https://www.coursera.org/learn/cryptocurrency) 🆓\n\n## Cryptography\n\n- [Stanford cryptography I](https://www.coursera.org/learn/crypto) 💰\n- [Stanford cryptography II (2017)](https://www.coursera.org/learn/crypto2) 💰\n\n## CSS\n\n- [CSS Grid by Wes Bos](https://github.com/wesbos/css-grid) 🆓\n\n## Decentralized systems\n\n- [MIT Decentralized Applications (2018)](http://nil.lcs.mit.edu/6.S974/papers.html) 🆓\n\n## Deep Learning\n\n- [Advanced Deep Learning \u0026 Reinforcement Learning (2018)](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) 🆓\n- [Berkeley deep reinforcement learning (2017)](http://rll.berkeley.edu/deeprlcourse/) 🆓\n- [Deep learning (2017)](http://deeplearning.cs.cmu.edu/) 🆓\n- [Stanford natural language processing with deep learning (2017)](https://www.youtube.com/watch?v=OQQ-W_63UgQ\u0026list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) 🆓\n- [Deep learning at Oxford (2015)](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu) 🆓\n- [Lectures](https://www.youtube.com/watch?v=2pWv7GOvuf0\u0026feature=youtu.be\u0026list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT) 🆓\n- [Oxford CS Deep NLP (2017)](https://github.com/oxford-cs-deepnlp-2017/lectures) 🆓\n- [Ucl reinforcement learning (2015)](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html)\n- [Stanford convolutional neural networks for visual recognition](http://cs231n.stanford.edu/syllabus.html) 🆓\n- [Stanford deep learning for natural language processing](http://cs224d.stanford.edu/syllabus.html) 🆓\n\n## Discrete math\n\n- [Discrete Mathematics and Probability Theory](http://www-inst.eecs.berkeley.edu/%7Ecs70/archives.html) 🆓\n\n## Functional programming\n\n- [Course in functional programming by KTH](https://github.com/ID1019/functional-programming) 🆓\n- [Functional Programming Course](https://github.com/data61/fp-course) 🆓\n- [Programming paradigms (2018)](http://www.cs.nott.ac.uk/~pszgmh/pgp.html) 🆓\n- [Functional Programming in OCaml (2019)](http://www.cs.cornell.edu/courses/cs3110/2019sp/textbook/)\n\n## Game development\n\n- [HTML5 game development](https://www.udacity.com/course/html5-game-development--cs255) 🆓\n\n## Haskell\n\n- [Advanced Programming (2017)](https://www.seas.upenn.edu/~cis552/current/index.html) 🆓\n- [Haskell ITMO (2017)](https://github.com/jagajaga/FP-Course-ITMO) 🆓\n- [Introduction to Haskell (2016)](http://www.seas.upenn.edu/%7Ecis194/spring13/) 🆓\n- [Stanford functional systems in Haskell (2014)](http://www.scs.stanford.edu/14sp-cs240h/) 🆓\n\n## Investing\n\n- [Computational investing](https://www.coursera.org/learn/computational-investing) 💰\n\n## iOS\n\n- [Developing iOS 10 apps with Swift (2017)](https://itunes.apple.com/us/course/developing-ios-10-apps-with-swift/id1198467120) 🆓\n\n## Machine learning\n\n- [MIT Deep Learning (2019)](https://github.com/lexfridman/mit-deep-learning)\n- [Amazon’s Machine Learning University course (2018)](https://aws.amazon.com/blogs/machine-learning/amazons-own-machine-learning-university-now-available-to-all-developers/) 🆓\n- [Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization](https://www.coursera.org/specializations/advanced-machine-learning-tensorflow-gcp) - Get hands-on experience optimizing, deploying, and scaling production ML models. 💰\n- [Artificial intelligence for robotics](https://www.udacity.com/course/artificial-intelligence-for-robotics--cs373) 🆓\n- [Coursera machine learning](https://www.coursera.org/learn/machine-learning) 💰\n- [Introduction to Deep Learning (2018)](http://introtodeeplearning.com/) - Introductory course on deep learning algorithms and their applications. 🆓\n- [Introduction to Machine Learning for Coders](http://course.fast.ai/ml.html) - The course covers the most important practical foundations for modern machine learning. 🆓\n- [Introduction to matrix methods (2015)](http://stanford.edu/class/ee103/) 🆓\n- [Learning from data (2012)](https://work.caltech.edu/telecourse.html) 🆓\n- [Machine Learning Crash Course (2018)](https://developers.google.com/machine-learning/crash-course/) - Google's fast-paced, practical introduction to machine learning. 🆓\n- [Machine learning for data science (2015)](http://www.cs.cornell.edu/courses/cs4786/2015sp/index.htm) 🆓\n- [Machine learning in Python with scikit-learn](https://github.com/justmarkham/scikit-learn-videos) 🆓\n- [Machine Learning with TensorFlow on Google Cloud Platform Specialization](https://www.coursera.org/specializations/machine-learning-tensorflow-gcp) - Learn ML with Google Cloud. Real-world experimentation with end-to-end ML. 💰\n- [Mathematics of Deep Learning, NYU, Spring (2018)](https://joanbruna.github.io/MathsDL-spring18/) 🆓\n- [mlcourse.ai](http://mlcourse.ai) - Open Machine Learning course by OpenDataScience. 🆓\n- [Neural networks for machine learning](https://www.coursera.org/learn/neural-networks) 💰\n- [Notes](https://github.com/1094401996/machine-learning-coursera) 🆓\n- [Practical Deep Learning For Coders (2018)](http://course.fast.ai/) - Learn how to build state of the art models without needing graduate-level math. 🆓\n- [Statistical learning (2015)](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) 🆓\n- [Tensorflow for deep learning research (2017)](http://web.stanford.edu/class/cs20si/index.html) 🆓\n\n## Math\n\n- [Abstract algebra (2019)](https://www.math.upenn.edu/~ted/502F19//math502.html) 🆓\n- [MIT linear algebra (2010)](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/) 🆓\n- [MIT multivariable calculus (2007)](https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/) 🆓\n- [MIT multivariable calculus by Prof. Denis Auroux](https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/index.htm) 🆓\n- [MIT multivariable control systems (2004)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-245-multivariable-control-systems-spring-2004/) 🆓\n- [MIT singlevariable calculus (2006)](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/) 🆓\n- [Nonlinear dynamics and chaos (2014)](https://www.youtube.com/playlist?list=PLbN57C5Zdl6j_qJA-pARJnKsmROzPnO9V) 🆓\n- [Stanford mathematical foundations of computing (2016)](http://web.stanford.edu/class/cs103/) 🆓\n- [Types, Logic, and Verification (2013)](https://www.fcs.uoregon.edu/research/summerschool/summer13/curriculum.html)\n\n## Networking\n\n- [Introduction to computer networking](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about) 🆓\n- [Introduction to EECS II: digital communication systems (2012)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-02-introduction-to-eecs-ii-digital-communication-systems-fall-2012/index.htm) 🆓\n\n## Neuroscience\n\n- [The Human Brain (2018)](https://nancysbraintalks.mit.edu/course/9-11-the-human-brain) 🆓\n\n## Natural Language Processing\n\n- [YSDA Natural Language Processing course (2018)](https://github.com/yandexdataschool/nlp_course) 🆓\n\n## Operating systems\n\n- [Computer Science 162](https://www.youtube.com/watch?v=feAOZuID1HM\u0026list=PLggtecHMfYHA7j2rF7nZFgnepu_uPuYws) 🆓\n- [Computer science from the bottom up](http://www.bottomupcs.com/) 🆓\n- [How to make a computer operating system (2015)](https://github.com/SamyPesse/How-to-Make-a-Computer-Operating-System) 🆓\n- [Operating system engineering](https://pdos.csail.mit.edu/6.828/2016/schedule.html) 🆓\n\n## Programming\n\n- [Build a modern computer from first principles: from nand to tetris ](https://www.coursera.org/learn/build-a-computer) 💰\n- [Introduction to programming with matlab](https://www.coursera.org/learn/matlab) 💰\n- [MIT software construction (2016)](http://web.mit.edu/6.005/www/fa16/) 🆓\n- [MIT structure and interpretation of computer programs (2005)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/index.htm) 🆓\n- [Stanford C Programming](https://www.youtube.com/playlist?list=PLjn3WmBeabPOUzxcCkzk4jYMGRZMZ6ylF\u0026app=desktop) 🆓\n- [Structure and interpretation of computer programs (in Python) (2017)](https://cs61a.org/) 🆓\n- [Unix tools and scripting (2014)](http://www.cs.cornell.edu/courses/cs2043/2014sp/) 🆓\n- [Composing Programs](https://composingprograms.com/) - Free online introduction to programming and computer science.\n\n## React\n\n- [Advanced React Patterns (2017)](https://github.com/kentcdodds/advanced-react-patterns) 🆓\n- [Beginner's guide to React (2017)](https://egghead.io/courses/the-beginner-s-guide-to-react) 🆓\n- [Survive JS: React, From apprentice to master](https://survivejs.com/react/introduction/) 🆓\n- [Building React Applications with Idiomatic Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) 🆓\n- [Building React Applications with Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) 🆓\n- [Complete intro to React v4 (2018)](https://btholt.github.io/complete-intro-to-react-v4/) 🆓\n- [Leverage New Features of React 16 (2018)](https://egghead.io/courses/leverage-new-features-of-react-16) 🆓\n- [React Holiday (2017)](https://react.holiday/) - React through examples. 🆓\n\n## ReasonML\n\n- [Get Started with Reason (2018)](https://egghead.io/courses/get-started-with-reason) 🆓\n\n## Rust\n\n- [Rust programming (2016)](http://cis198-2016s.github.io/) 🆓\n\n## Scala\n\n- [Functional programming principles in scala](https://www.coursera.org/learn/progfun1) 💰\n\n## Security\n\n- [Computer and network security (2013)](https://courseware.stanford.edu/pg/courses/lectures/349991) 🆓\n- [Hacker101 (2018)](https://github.com/Hacker0x01/hacker101) - Free class for web security. 🆓\n\n## Statistics\n\n- [Introduction to probability - the science of uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) 🆓\n- [MIT probabilistic systems analysis and applied probability (2010)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/index.htm) 🆓\n- [Statistical Learning (2016)](https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about) 🆓\n- [Statistics 110](https://www.youtube.com/watch?v=KbB0FjPg0mw\u0026list=EC2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) 🆓\n\n## Swift\n\n- [Hacking with Swift (2018)](https://www.hackingwithswift.com/read) 🆓\n\n## Type theory\n\n- [Homotopy Type Theory (2014)](https://www.cs.cmu.edu/%7Erwh/courses/hott/) 🆓\n\n## Vim\n\n- [Vim valley](https://vimvalley.com/) 💰\n\n## Web Development\n\n- [Cutting-edge web technologies (2015)](http://inst.eecs.berkeley.edu/%7Ecs294-101/sp15/) 🆓\n- [Interactive Flexbox course (2018)](https://scrimba.com/g/gflexbox) 🆓\n\n## Related\n\n- [Awesome artificial intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) 🆓\n- [Awesome courses](https://github.com/prakhar1989/awesome-courses) 🆓\n- [CS video courses](https://github.com/Developer-Y/cs-video-courses) 🆓\n- [Data science courses](https://github.com/DataScienceSpecialization/courses) 🆓\n- [Dive into machine learning](https://github.com/hangtwenty/dive-into-machine-learning) 🆓\n\n[![CC4](https://img.shields.io/badge/license-CC4-0a0a0a.svg?style=flat\u0026colorA=0a0a0a)](https://creativecommons.org/licenses/by/4.0/)\n[![Lists](https://img.shields.io/badge/-more%20lists-0a0a0a.svg?style=flat\u0026colorA=0a0a0a)](https://github.com/learn-anything/curated-lists)\n[![Contribute](https://img.shields.io/badge/-contribute-0a0a0a.svg?style=flat\u0026colorA=0a0a0a)](contributing.md)\n[![Twitter](http://bit.ly/latwitt)](https://twitter.com/learnanything_)\n","funding_links":[],"categories":["Others","Learn","Other Lists","Uncategorized"],"sub_categories":["TeX Lists","Uncategorized"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flearn-anything%2Fcourses","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flearn-anything%2Fcourses","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flearn-anything%2Fcourses/lists"}