# Learn Anything | Massive Courses Resources ⭐ **URL:** \ **Category:** Give-Away and Freebies\ **Tags:** learning, freebies\ **Created:** [January 17, 2021, 1:34pm UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133 "2021-01-17T13:34:25Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![Aina](https://onehack.st/user_avatar/onehack.st/aina/32/167469_2.png) [@Aina](https://onehack.st/u/Aina)\ **Post date:** [January 17, 2021, 1:34pm UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/1 "2021-01-17T13:34:25Z")
![image](https://onehack.st/uploads/default/original/3X/0/e/0e86f37f1a81675cc9f100be7fe0bc1fe38ea2d8.jpeg) # Courses _Please read [contribution guidelines](https://github.com/learn-anything/courses/blob/master/contributing.md) before contributing._ - [Algorithms](https://github.com/learn-anything/courses#algorithms) - [Artificial Intelligence](https://github.com/learn-anything/courses#artificial-intelligence) - [Business](https://github.com/learn-anything/courses#business) - [Chemistry](https://github.com/learn-anything/courses#chemistry) - [Compilers](https://github.com/learn-anything/courses#compilers) - [Computer Science](https://github.com/learn-anything/courses#computer-science) - [Computer vision](https://github.com/learn-anything/courses#computer-vision) - [Cryptocurrency](https://github.com/learn-anything/courses#cryptocurrency) - [Cryptography](https://github.com/learn-anything/courses#cryptography) - [CSS](https://github.com/learn-anything/courses#css) - [Decentralized systems](https://github.com/learn-anything/courses#decentralized-systems) - [Deep Learning](https://github.com/learn-anything/courses#deep-learning) - [Discrete math](https://github.com/learn-anything/courses#discrete-math) - [Functional programming](https://github.com/learn-anything/courses#functional-programming) - [Game development](https://github.com/learn-anything/courses#game-development) - [Haskell](https://github.com/learn-anything/courses#haskell) - [Investing](https://github.com/learn-anything/courses#investing) - [iOS](https://github.com/learn-anything/courses#ios) - [Machine learning](https://github.com/learn-anything/courses#machine-learning) - [Math](https://github.com/learn-anything/courses#math) - [Networking](https://github.com/learn-anything/courses#networking) - [Neuroscience](https://github.com/learn-anything/courses#neuroscience) - [Natural Language Processing](https://github.com/learn-anything/courses#natural-language-processing) - [Operating systems](https://github.com/learn-anything/courses#operating-systems) - [Programming](https://github.com/learn-anything/courses#programming) - [React](https://github.com/learn-anything/courses#react) - [ReasonML](https://github.com/learn-anything/courses#reasonml) - [Rust](https://github.com/learn-anything/courses#rust) - [Scala](https://github.com/learn-anything/courses#scala) - [Security](https://github.com/learn-anything/courses#security) - [Statistics](https://github.com/learn-anything/courses#statistics) - [Swift](https://github.com/learn-anything/courses#swift) - [Type theory](https://github.com/learn-anything/courses#type-theory) - [Vim](https://github.com/learn-anything/courses#vim) - [Web Development](https://github.com/learn-anything/courses#web-development) - [Related](https://github.com/learn-anything/courses#related) ## Algorithms - [Algorithmic thinking](https://www.coursera.org/learn/algorithmic-thinking-1) πŸ’° - [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. πŸ†“ - [Algorithms specialization](https://www.coursera.org/specializations/algorithms) - [Algorithms: Part 1](https://www.coursera.org/learn/algorithms-part1/home/welcome) πŸ†“ - [Algorithms: Part 2](https://www.coursera.org/learn/algorithms-part2) πŸ†“ - [Data structures (2016)](http://datastructur.es/sp16/) πŸ†“ - [Data structures (2017)](http://datastructur.es/sp17/) πŸ†“ - [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/) πŸ†“ - [Evolutionary computation (2014)](https://courses2.cit.cornell.edu/cs5724/) πŸ†“ - [Introduction to programming contests (2012)](http://web.stanford.edu/class/cs97si/) πŸ†“ - [MIT advanced data structures (2014)](http://courses.csail.mit.edu/6.851/spring14/index.html) πŸ†“ - [MIT introduction to algorithms](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/) πŸ†“ ## Artificial Intelligence - [Berkeley intro to ai (2014)](http://ai.berkeley.edu/home.html) πŸ†“ - [MIT artificial intelligence (2010)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/) πŸ†“ - [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) πŸ†“ ## Business - [Gamification](https://www.coursera.org/learn/gamification) πŸ’° ## Chemistry - [Bioinformatics specialization](https://www.coursera.org/specializations/bioinformatics) πŸ’° ## Compilers - [Principles of compiler design (2016)](https://www.cs.swarthmore.edu/~jpolitz/cs75/s16/s_schedule.html) πŸ†“ - [Stanford compiler construction (2016)](https://web.stanford.edu/class/cs143/) πŸ†“ ## Computer Science - [Computational complexity (2008)](https://people.eecs.berkeley.edu/~luca/cs278-08/) πŸ†“ - [Computer science 101](https://lagunita.stanford.edu/courses/Engineering/CS101/Summer2014/about) πŸ†“ - [Data structures](https://www.coursera.org/learn/data-structures) πŸ’° - [Great ideas in computer architecture (2015)](http://www-inst.eecs.berkeley.edu/~cs61c/sp15/) πŸ†“ - [Information retrieval (2013)](http://www.cs.cornell.edu/courses/cs4300/2013fa/) πŸ†“ - [MIT great ideas in theoretical computer science](https://stellar.mit.edu/S/course/6/sp15/6.045/materials.html) πŸ†“ - [MIT Mathematics for Computer Science (2010)](https://www.youtube.com/playlist?list=PLB7540DEDD482705B) πŸ†“ - [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/) πŸ†“ - [Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexity (2018)](https://www.edx.org/course/efficient-quantum-computing-fault-tolerance-and-complexity) πŸ†“ - [Software foundations (2014)](http://www.seas.upenn.edu/~cis500/cis500-f14/index.html) πŸ†“ - [The art of recursion (2012)](http://www.cis.upenn.edu/~cis39903/) πŸ†“ ## Computer vision - [Computer vision](http://crcv.ucf.edu/courses/CAP5415/) πŸ†“ - [Introduction to computer vision (2015)](http://www.cs.cornell.edu/courses/cs4670/2015sp/lectures/lectures.html) πŸ†“ - [Programming computer vision with python (2012)](http://programmingcomputervision.com/) πŸ†“ ## Cryptocurrency - [Bitcoin and Cryptocurrency Technologies](https://www.coursera.org/learn/cryptocurrency) πŸ†“ ## Cryptography - [Stanford cryptography I](https://www.coursera.org/learn/crypto) πŸ’° - [Stanford cryptography II (2017)](https://www.coursera.org/learn/crypto2) πŸ’° ## CSS - [CSS Grid by Wes Bos](https://github.com/wesbos/css-grid) πŸ†“ ## Decentralized systems - [MIT Decentralized Applications (2018)](http://nil.lcs.mit.edu/6.S974/papers.html) πŸ†“ ## Deep Learning - [Advanced Deep Learning & Reinforcement Learning (2018)](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) πŸ†“ - [Berkeley deep reinforcement learning (2017)](http://rll.berkeley.edu/deeprlcourse/) πŸ†“ - [Deep learning (2017)](http://deeplearning.cs.cmu.edu/) πŸ†“ - [Stanford natural language processing with deep learning (2017)](https://www.youtube.com/watch?v=OQQ-W_63UgQ&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) πŸ†“ - [Deep learning at Oxford (2015)](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu) πŸ†“ - [Lectures](https://www.youtube.com/watch?v=2pWv7GOvuf0&feature=youtu.be&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT) πŸ†“ - [Oxford CS Deep NLP (2017)](https://github.com/oxford-cs-deepnlp-2017/lectures) πŸ†“ - [Ucl reinforcement learning (2015)](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) - [Stanford convolutional neural networks for visual recognition](http://cs231n.stanford.edu/syllabus.html) πŸ†“ - [Stanford deep learning for natural language processing](http://cs224d.stanford.edu/syllabus.html) πŸ†“ ## Discrete math - [Discrete Mathematics and Probability Theory](http://www-inst.eecs.berkeley.edu/~cs70/archives.html) πŸ†“ ## Functional programming - [Course in functional programming by KTH](https://github.com/ID1019/functional-programming) πŸ†“ - [Functional Programming Course](https://github.com/data61/fp-course) πŸ†“ - [Programming paradigms (2018)](http://www.cs.nott.ac.uk/~pszgmh/pgp.html) πŸ†“ - [Functional Programming in OCaml (2019)](http://www.cs.cornell.edu/courses/cs3110/2019sp/textbook/) ## Game development - [HTML5 game development](https://www.udacity.com/course/html5-game-development--cs255) πŸ†“ ## Haskell - [Advanced Programming (2017)](https://www.seas.upenn.edu/~cis552/current/index.html) πŸ†“ - [Haskell ITMO (2017)](https://github.com/jagajaga/FP-Course-ITMO) πŸ†“ - [Introduction to Haskell (2016)](http://www.seas.upenn.edu/~cis194/spring13/) πŸ†“ - [Stanford functional systems in Haskell (2014)](http://www.scs.stanford.edu/14sp-cs240h/) πŸ†“ ## Investing - [Computational investing](https://www.coursera.org/learn/computational-investing) πŸ’° ## iOS - [Developing iOS 10 apps with Swift (2017)](https://itunes.apple.com/us/course/developing-ios-10-apps-with-swift/id1198467120) πŸ†“ ## Machine learning - [MIT Deep Learning (2019)](https://github.com/lexfridman/mit-deep-learning) - [Amazon’s Machine Learning University course (2018)](https://aws.amazon.com/blogs/machine-learning/amazons-own-machine-learning-university-now-available-to-all-developers/) πŸ†“ - [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. πŸ’° - [Artificial intelligence for robotics](https://www.udacity.com/course/artificial-intelligence-for-robotics--cs373) πŸ†“ - [Coursera machine learning](https://www.coursera.org/learn/machine-learning) πŸ’° - [Introduction to Deep Learning (2018)](http://introtodeeplearning.com/) - Introductory course on deep learning algorithms and their applications. πŸ†“ - [Introduction to Machine Learning for Coders](http://course.fast.ai/ml.html) - The course covers the most important practical foundations for modern machine learning. πŸ†“ - [Introduction to matrix methods (2015)](http://stanford.edu/class/ee103/) πŸ†“ - [Learning from data (2012)](https://work.caltech.edu/telecourse.html) πŸ†“ - [Machine Learning Crash Course (2018)](https://developers.google.com/machine-learning/crash-course/) - Google’s fast-paced, practical introduction to machine learning. πŸ†“ - [Machine learning for data science (2015)](http://www.cs.cornell.edu/courses/cs4786/2015sp/index.htm) πŸ†“ - [Machine learning in Python with scikit-learn](https://github.com/justmarkham/scikit-learn-videos) πŸ†“ - [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. πŸ’° - [Mathematics of Deep Learning, NYU, Spring (2018)](https://joanbruna.github.io/MathsDL-spring18/) πŸ†“ - [mlcourse.ai](http://mlcourse.ai/) - Open Machine Learning course by OpenDataScience. πŸ†“ - [Neural networks for machine learning](https://www.coursera.org/learn/neural-networks) πŸ’° - [Notes](https://github.com/1094401996/machine-learning-coursera) πŸ†“ - [Practical Deep Learning For Coders (2018)](http://course.fast.ai/) - Learn how to build state of the art models without needing graduate-level math. πŸ†“ - [Statistical learning (2015)](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) πŸ†“ - [Tensorflow for deep learning research (2017)](http://web.stanford.edu/class/cs20si/index.html) πŸ†“ ## Math - [Abstract algebra (2019)](https://www.math.upenn.edu/~ted/502F19//math502.html) πŸ†“ - [MIT linear algebra (2010)](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/) πŸ†“ - [MIT multivariable calculus (2007)](https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/) πŸ†“ - [MIT multivariable calculus by Prof. Denis Auroux](https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/index.htm) πŸ†“ - [MIT multivariable control systems (2004)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-245-multivariable-control-systems-spring-2004/) πŸ†“ - [MIT singlevariable calculus (2006)](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/) πŸ†“ - [Nonlinear dynamics and chaos (2014)](https://www.youtube.com/playlist?list=PLbN57C5Zdl6j_qJA-pARJnKsmROzPnO9V) πŸ†“ - [Stanford mathematical foundations of computing (2016)](http://web.stanford.edu/class/cs103/) πŸ†“ - [Types, Logic, and Verification (2013)](https://www.fcs.uoregon.edu/research/summerschool/summer13/curriculum.html) ## Networking - [Introduction to computer networking](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about) πŸ†“ - [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) πŸ†“ ## Neuroscience - [The Human Brain (2018)](https://nancysbraintalks.mit.edu/course/9-11-the-human-brain) πŸ†“ ## Natural Language Processing - [YSDA Natural Language Processing course (2018)](https://github.com/yandexdataschool/nlp_course) πŸ†“ ## Operating systems - [Computer Science 162](https://www.youtube.com/watch?v=feAOZuID1HM&list=PLggtecHMfYHA7j2rF7nZFgnepu_uPuYws) πŸ†“ - [Computer science from the bottom up](http://www.bottomupcs.com/) πŸ†“ - [How to make a computer operating system (2015)](https://github.com/SamyPesse/How-to-Make-a-Computer-Operating-System) πŸ†“ - [Operating system engineering](https://pdos.csail.mit.edu/6.828/2016/schedule.html) πŸ†“ ## Programming - [Build a modern computer from first principles: from nand to tetris](https://www.coursera.org/learn/build-a-computer)πŸ’° - [Introduction to programming with matlab](https://www.coursera.org/learn/matlab) πŸ’° - [MIT software construction (2016)](http://web.mit.edu/6.005/www/fa16/) πŸ†“ - [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) πŸ†“ - [Stanford C Programming](https://www.youtube.com/playlist?list=PLjn3WmBeabPOUzxcCkzk4jYMGRZMZ6ylF&app=desktop) πŸ†“ - [Structure and interpretation of computer programs (in Python) (2017)](https://cs61a.org/) πŸ†“ - [Unix tools and scripting (2014)](http://www.cs.cornell.edu/courses/cs2043/2014sp/) πŸ†“ - [Composing Programs](https://composingprograms.com/) - Free online introduction to programming and computer science. ## React - [Advanced React Patterns (2017)](https://github.com/kentcdodds/advanced-react-patterns) πŸ†“ - [Beginner’s guide to React (2017)](https://egghead.io/courses/the-beginner-s-guide-to-react) πŸ†“ - [Survive JS: React, From apprentice to master](https://survivejs.com/react/introduction/) πŸ†“ - [Building React Applications with Idiomatic Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) πŸ†“ - [Building React Applications with Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) πŸ†“ - [Complete intro to React v4 (2018)](https://btholt.github.io/complete-intro-to-react-v4/) πŸ†“ - [Leverage New Features of React 16 (2018)](https://egghead.io/courses/leverage-new-features-of-react-16) πŸ†“ - [React Holiday (2017)](https://react.holiday/) - React through examples. πŸ†“ ## ReasonML - [Get Started with Reason (2018)](https://egghead.io/courses/get-started-with-reason) πŸ†“ ## Rust - [Rust programming (2016)](http://cis198-2016s.github.io/) πŸ†“ ## Scala - [Functional programming principles in scala](https://www.coursera.org/learn/progfun1) πŸ’° ## Security - [Computer and network security (2013)](https://courseware.stanford.edu/pg/courses/lectures/349991) πŸ†“ - [Hacker101 (2018)](https://github.com/Hacker0x01/hacker101) - Free class for web security. πŸ†“ ## Statistics - [Introduction to probability - the science of uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) πŸ†“ - [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) πŸ†“ - [Statistical Learning (2016)](https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about) πŸ†“ - [Statistics 110](https://www.youtube.com/watch?v=KbB0FjPg0mw&list=EC2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) πŸ†“ ## Swift - [Hacking with Swift (2018)](https://www.hackingwithswift.com/read) πŸ†“ ## Type theory - [Homotopy Type Theory (2014)](https://www.cs.cmu.edu/~rwh/courses/hott/) πŸ†“ ## Vim - [Vim valley](https://vimvalley.com/) πŸ’° ## Web Development - [Cutting-edge web technologies (2015)](http://inst.eecs.berkeley.edu/~cs294-101/sp15/) πŸ†“ - [Interactive Flexbox course (2018)](https://scrimba.com/g/gflexbox) πŸ†“ ## Related - [Awesome artificial intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) πŸ†“ - [Awesome courses](https://github.com/prakhar1989/awesome-courses) πŸ†“ - [CS video courses](https://github.com/Developer-Y/cs-video-courses) πŸ†“ - [Data science courses](https://github.com/DataScienceSpecialization/courses) πŸ†“ - [Dive into machine learning](https://github.com/hangtwenty/dive-into-machine-learning) πŸ†“ [![CC4](https://camo.githubusercontent.com/389811476c6cbd50210f9aa7a0495f452125cbb83946dd8d03c3539e1d92e496/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6c6963656e73652d4343342d3061306130612e7376673f7374796c653d666c617426636f6c6f72413d306130613061)](https://creativecommons.org/licenses/by/4.0/)[![Contribute](https://camo.githubusercontent.com/fd959d68c9d6841fab3fbec33c0768d417d8889543735548f3dcf48dd8876f8b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f2d636f6e747269627574652d3061306130612e7376673f7374796c653d666c617426636f6c6f72413d306130613061)](https://github.com/learn-anything/courses/blob/master/contributing.md) [![Twitter](https://camo.githubusercontent.com/ef73f400c27e1cc76d32c09d4a2c8a0b1fc6a6ac322663d497771e6a7796f3c5/687474703a2f2f6269742e6c792f6c617477697474)](https://twitter.com/learnanything_) `Source: GitHub` ## ENJOY & HAPPY LEARNING! ❀ ---
**Author:** ![Aina](https://onehack.st/user_avatar/onehack.st/aina/32/167469_2.png) [@Aina](https://onehack.st/u/Aina)\ **Post date:** [January 17, 2021, 1:35pm UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/2 "2021-01-17T13:35:05Z")
---
**Author:** ![surya77](https://onehack.st/letter_avatar_proxy/v4/letter/s/c0e974/32.png) [@surya77](https://onehack.st/u/surya77)\ **Post date:** [January 18, 2021, 3:41am UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/3 "2021-01-18T03:41:51Z")
Thank you so very much! πŸ™ ---
**Author:** ![slimjval](https://onehack.st/user_avatar/onehack.st/slimjval/32/30254_2.png) [@slimjval](https://onehack.st/u/slimjval)\ **Post date:** [January 18, 2021, 4:40am UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/4 "2021-01-18T04:40:38Z")
thanks so much. you’re the bestEST ---
**Author:** ![quick-learner](https://onehack.st/user_avatar/onehack.st/quick-learner/32/43997_2.png) [@quick-learner](https://onehack.st/u/quick-learner)\ **Post date:** [January 18, 2021, 5:47am UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/5 "2021-01-18T05:47:30Z")
thanks for this massive list sam, you the man, will help many peoples. ---
**Author:** ![Huteng\_Batute](https://onehack.st/user_avatar/onehack.st/huteng_batute/32/12321_2.png) [@Huteng\_Batute](https://onehack.st/u/Huteng_Batute)\ **Post date:** [January 20, 2021, 2:09am UTC](https://onehack.st/t/learn-anything-massive-courses-resources/170133/6 "2021-01-20T02:09:25Z")
Thank you very much Chief @Aina