├── contributing.md └── readme.md /contributing.md: -------------------------------------------------------------------------------- 1 | # Contributing 2 | 3 | Thank you for taking the time to contribute! ♥️ Ensure your PR adheres to following guidelines: 4 | 5 | - Search included courses before adding a new one, as yours may be a duplicate. 6 | - Only add courses you think are great! Feel welcome to remove entries that you think aren't great! 7 | - Use the following format: `[Name (Year) <🆓 or 💰>](link) - Description.` 8 | - If you can't find the year the course was made in, you can skip adding the year. 9 | - If the course is free, link to free course and add 🆓 emoji. 10 | - If course if paid, link to paid course and add 💰 emoji. 11 | - The course should be put into its appropriate category. Pick one you think is closest if you are not sure. 12 | - If you want to add a link to notes for the course, add it to Description inbetween `()`. i.e. `(Notes[link])` 13 | - Start the description with a capital and end with a full stop. 14 | - Don't start the description with `A` or `An`. 15 | - Check your spelling and grammar. 16 | - New categories or improvements to the existing categorization are welcome. 17 | - You can also add related links and repositories in the end. 18 | 19 | [All suggestions are welcome](../../edit/master/readme.md). 20 | -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # Courses [![Lists](https://img.shields.io/badge/-more%20lists-0a0a0a.svg?style=flat&colorA=0a0a0a)](https://github.com/learn-anything/curated-lists) 2 | 3 | _Please read [contribution guidelines](contributing.md) before contributing._ 4 | 5 | - [Algorithms](#algorithms) 6 | - [Artificial Intelligence](#artificial-intelligence) 7 | - [Business](#business) 8 | - [Chemistry](#chemistry) 9 | - [Compilers](#compilers) 10 | - [Computer Science](#computer-science) 11 | - [Computer vision](#computer-vision) 12 | - [Cryptocurrency](#cryptocurrency) 13 | - [Cryptography](#cryptography) 14 | - [CSS](#css) 15 | - [Decentralized systems](#decentralized-systems) 16 | - [Deep Learning](#deep-learning) 17 | - [Discrete math](#discrete-math) 18 | - [Functional programming](#functional-programming) 19 | - [Game development](#game-development) 20 | - [Haskell](#haskell) 21 | - [Investing](#investing) 22 | - [iOS](#ios) 23 | - [Machine learning](#machine-learning) 24 | - [Math](#math) 25 | - [Networking](#networking) 26 | - [Neuroscience](#neuroscience) 27 | - [Natural Language Processing](#natural-language-processing) 28 | - [Operating systems](#operating-systems) 29 | - [Programming](#programming) 30 | - [React](#react) 31 | - [ReasonML](#reasonml) 32 | - [Rust](#rust) 33 | - [Scala](#scala) 34 | - [Security](#security) 35 | - [Statistics](#statistics) 36 | - [Swift](#swift) 37 | - [Type theory](#type-theory) 38 | - [Vim](#vim) 39 | - [Web Development](#web-development) 40 | - [Related](#related) 41 | 42 | ## Algorithms 43 | 44 | - [Algorithmic thinking](https://www.coursera.org/learn/algorithmic-thinking-1) 💰 45 | - [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. 🆓 46 | - [Algorithms specialization](https://www.coursera.org/specializations/algorithms) 47 | - [Algorithms: Part 1](https://www.coursera.org/learn/algorithms-part1/home/welcome) 🆓 48 | - [Algorithms: Part 2](https://www.coursera.org/learn/algorithms-part2) 🆓 49 | - [Data structures (2016)](http://datastructur.es/sp16/) 🆓 50 | - [Data structures (2017)](http://datastructur.es/sp17/) 🆓 51 | - [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/) 🆓 52 | - [Evolutionary computation (2014)](https://courses2.cit.cornell.edu/cs5724/) 🆓 53 | - [Introduction to programming contests (2012)](http://web.stanford.edu/class/cs97si/) 🆓 54 | - [MIT advanced data structures (2014)](http://courses.csail.mit.edu/6.851/spring14/index.html) 🆓 55 | - [MIT introduction to algorithms](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/) 🆓 56 | 57 | ## Artificial Intelligence 58 | 59 | - [Berkeley intro to ai (2014)](http://ai.berkeley.edu/home.html) 🆓 60 | - [MIT artificial intelligence (2010)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/) 🆓 61 | - [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) 🆓 62 | 63 | ## Business 64 | 65 | - [Gamification](https://www.coursera.org/learn/gamification) 💰 66 | 67 | ## Chemistry 68 | 69 | - [Bioinformatics specialization](https://www.coursera.org/specializations/bioinformatics) 💰 70 | 71 | ## Compilers 72 | 73 | - [Principles of compiler design (2016)](https://www.cs.swarthmore.edu/%7Ejpolitz/cs75/s16/s_schedule.html) 🆓 74 | - [Stanford compiler construction (2016)](https://web.stanford.edu/class/cs143/) 🆓 75 | 76 | ## Computer Science 77 | 78 | - [Computational complexity (2008)](https://people.eecs.berkeley.edu/~luca/cs278-08/) 🆓 79 | - [Computer science 101](https://lagunita.stanford.edu/courses/Engineering/CS101/Summer2014/about) 🆓 80 | - [Data structures](https://www.coursera.org/learn/data-structures) 💰 81 | - [Great ideas in computer architecture (2015)](http://www-inst.eecs.berkeley.edu/%7Ecs61c/sp15/) 🆓 82 | - [Information retrieval (2013)](http://www.cs.cornell.edu/courses/cs4300/2013fa/) 🆓 83 | - [MIT great ideas in theoretical computer science](https://stellar.mit.edu/S/course/6/sp15/6.045/materials.html) 🆓 84 | - [MIT Mathematics for Computer Science (2010)](https://www.youtube.com/playlist?list=PLB7540DEDD482705B) 🆓 85 | - [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/) 🆓 86 | - [Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexity (2018)](https://www.edx.org/course/efficient-quantum-computing-fault-tolerance-and-complexity) 🆓 87 | - [Software foundations (2014)](http://www.seas.upenn.edu/%7Ecis500/cis500-f14/index.html) 🆓 88 | - [The art of recursion (2012)](http://www.cis.upenn.edu/~cis39903/) 🆓 89 | 90 | ## Computer vision 91 | 92 | - [Computer vision](http://crcv.ucf.edu/courses/CAP5415/) 🆓 93 | - [Introduction to computer vision (2015)](http://www.cs.cornell.edu/courses/cs4670/2015sp/lectures/lectures.html) 🆓 94 | - [Programming computer vision with python (2012)](http://programmingcomputervision.com/) 🆓 95 | 96 | ## Cryptocurrency 97 | 98 | - [Bitcoin and Cryptocurrency Technologies](https://www.coursera.org/learn/cryptocurrency) 🆓 99 | 100 | ## Cryptography 101 | 102 | - [Stanford cryptography I](https://www.coursera.org/learn/crypto) 💰 103 | - [Stanford cryptography II (2017)](https://www.coursera.org/learn/crypto2) 💰 104 | 105 | ## CSS 106 | 107 | - [CSS Grid by Wes Bos](https://github.com/wesbos/css-grid) 🆓 108 | 109 | ## Decentralized systems 110 | 111 | - [MIT Decentralized Applications (2018)](http://nil.lcs.mit.edu/6.S974/papers.html) 🆓 112 | 113 | ## Deep Learning 114 | 115 | - [Advanced Deep Learning & Reinforcement Learning (2018)](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) 🆓 116 | - [Berkeley deep reinforcement learning (2017)](http://rll.berkeley.edu/deeprlcourse/) 🆓 117 | - [Deep learning (2017)](http://deeplearning.cs.cmu.edu/) 🆓 118 | - [Stanford natural language processing with deep learning (2017)](https://www.youtube.com/watch?v=OQQ-W_63UgQ&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) 🆓 119 | - [Deep learning at Oxford (2015)](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu) 🆓 120 | - [Lectures](https://www.youtube.com/watch?v=2pWv7GOvuf0&feature=youtu.be&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT) 🆓 121 | - [Oxford CS Deep NLP (2017)](https://github.com/oxford-cs-deepnlp-2017/lectures) 🆓 122 | - [Ucl reinforcement learning (2015)](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) 123 | - [Stanford convolutional neural networks for visual recognition](http://cs231n.stanford.edu/syllabus.html) 🆓 124 | - [Stanford deep learning for natural language processing](http://cs224d.stanford.edu/syllabus.html) 🆓 125 | 126 | ## Discrete math 127 | 128 | - [Discrete Mathematics and Probability Theory](http://www-inst.eecs.berkeley.edu/%7Ecs70/archives.html) 🆓 129 | 130 | ## Functional programming 131 | 132 | - [Course in functional programming by KTH](https://github.com/ID1019/functional-programming) 🆓 133 | - [Functional Programming Course](https://github.com/data61/fp-course) 🆓 134 | - [Programming paradigms (2018)](http://www.cs.nott.ac.uk/~pszgmh/pgp.html) 🆓 135 | - [Functional Programming in OCaml (2019)](http://www.cs.cornell.edu/courses/cs3110/2019sp/textbook/) 136 | 137 | ## Game development 138 | 139 | - [HTML5 game development](https://www.udacity.com/course/html5-game-development--cs255) 🆓 140 | 141 | ## Haskell 142 | 143 | - [Advanced Programming (2017)](https://www.seas.upenn.edu/~cis552/current/index.html) 🆓 144 | - [Haskell ITMO (2017)](https://github.com/jagajaga/FP-Course-ITMO) 🆓 145 | - [Introduction to Haskell (2016)](http://www.seas.upenn.edu/%7Ecis194/spring13/) 🆓 146 | - [Stanford functional systems in Haskell (2014)](http://www.scs.stanford.edu/14sp-cs240h/) 🆓 147 | 148 | ## Investing 149 | 150 | - [Computational investing](https://www.coursera.org/learn/computational-investing) 💰 151 | 152 | ## iOS 153 | 154 | - [Developing iOS 10 apps with Swift (2017)](https://itunes.apple.com/us/course/developing-ios-10-apps-with-swift/id1198467120) 🆓 155 | 156 | ## Machine learning 157 | 158 | - [MIT Deep Learning (2019)](https://github.com/lexfridman/mit-deep-learning) 159 | - [Amazon’s Machine Learning University course (2018)](https://aws.amazon.com/blogs/machine-learning/amazons-own-machine-learning-university-now-available-to-all-developers/) 🆓 160 | - [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. 💰 161 | - [Artificial intelligence for robotics](https://www.udacity.com/course/artificial-intelligence-for-robotics--cs373) 🆓 162 | - [Coursera machine learning](https://www.coursera.org/learn/machine-learning) 💰 163 | - [Introduction to Deep Learning (2018)](http://introtodeeplearning.com/) - Introductory course on deep learning algorithms and their applications. 🆓 164 | - [Introduction to Machine Learning for Coders](http://course.fast.ai/ml.html) - The course covers the most important practical foundations for modern machine learning. 🆓 165 | - [Introduction to matrix methods (2015)](http://stanford.edu/class/ee103/) 🆓 166 | - [Learning from data (2012)](https://work.caltech.edu/telecourse.html) 🆓 167 | - [Machine Learning Crash Course (2018)](https://developers.google.com/machine-learning/crash-course/) - Google's fast-paced, practical introduction to machine learning. 🆓 168 | - [Machine learning for data science (2015)](http://www.cs.cornell.edu/courses/cs4786/2015sp/index.htm) 🆓 169 | - [Machine learning in Python with scikit-learn](https://github.com/justmarkham/scikit-learn-videos) 🆓 170 | - [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. 💰 171 | - [Mathematics of Deep Learning, NYU, Spring (2018)](https://joanbruna.github.io/MathsDL-spring18/) 🆓 172 | - [mlcourse.ai](http://mlcourse.ai) - Open Machine Learning course by OpenDataScience. 🆓 173 | - [Neural networks for machine learning](https://www.coursera.org/learn/neural-networks) 💰 174 | - [Notes](https://github.com/1094401996/machine-learning-coursera) 🆓 175 | - [Practical Deep Learning For Coders (2018)](http://course.fast.ai/) - Learn how to build state of the art models without needing graduate-level math. 🆓 176 | - [Statistical learning (2015)](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) 🆓 177 | - [Tensorflow for deep learning research (2017)](http://web.stanford.edu/class/cs20si/index.html) 🆓 178 | 179 | ## Math 180 | 181 | - [Abstract algebra (2019)](https://www.math.upenn.edu/~ted/502F19//math502.html) 🆓 182 | - [MIT linear algebra (2010)](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/) 🆓 183 | - [MIT multivariable calculus (2007)](https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/) 🆓 184 | - [MIT multivariable calculus by Prof. Denis Auroux](https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/index.htm) 🆓 185 | - [MIT multivariable control systems (2004)](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-245-multivariable-control-systems-spring-2004/) 🆓 186 | - [MIT singlevariable calculus (2006)](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/) 🆓 187 | - [Nonlinear dynamics and chaos (2014)](https://www.youtube.com/playlist?list=PLbN57C5Zdl6j_qJA-pARJnKsmROzPnO9V) 🆓 188 | - [Stanford mathematical foundations of computing (2016)](http://web.stanford.edu/class/cs103/) 🆓 189 | - [Types, Logic, and Verification (2013)](https://www.fcs.uoregon.edu/research/summerschool/summer13/curriculum.html) 190 | 191 | ## Networking 192 | 193 | - [Introduction to computer networking](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about) 🆓 194 | - [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) 🆓 195 | 196 | ## Neuroscience 197 | 198 | - [The Human Brain (2018)](https://nancysbraintalks.mit.edu/course/9-11-the-human-brain) 🆓 199 | 200 | ## Natural Language Processing 201 | 202 | - [YSDA Natural Language Processing course (2018)](https://github.com/yandexdataschool/nlp_course) 🆓 203 | 204 | ## Operating systems 205 | 206 | - [Computer Science 162](https://www.youtube.com/watch?v=feAOZuID1HM&list=PLggtecHMfYHA7j2rF7nZFgnepu_uPuYws) 🆓 207 | - [Computer science from the bottom up](http://www.bottomupcs.com/) 🆓 208 | - [How to make a computer operating system (2015)](https://github.com/SamyPesse/How-to-Make-a-Computer-Operating-System) 🆓 209 | - [Operating system engineering](https://pdos.csail.mit.edu/6.828/2016/schedule.html) 🆓 210 | 211 | ## Programming 212 | 213 | - [Build a modern computer from first principles: from nand to tetris ](https://www.coursera.org/learn/build-a-computer) 💰 214 | - [Introduction to programming with matlab](https://www.coursera.org/learn/matlab) 💰 215 | - [MIT software construction (2016)](http://web.mit.edu/6.005/www/fa16/) 🆓 216 | - [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) 🆓 217 | - [Stanford C Programming](https://www.youtube.com/playlist?list=PLjn3WmBeabPOUzxcCkzk4jYMGRZMZ6ylF&app=desktop) 🆓 218 | - [Structure and interpretation of computer programs (in Python) (2017)](https://cs61a.org/) 🆓 219 | - [Unix tools and scripting (2014)](http://www.cs.cornell.edu/courses/cs2043/2014sp/) 🆓 220 | - [Composing Programs](https://composingprograms.com/) - Free online introduction to programming and computer science. 221 | 222 | ## React 223 | 224 | - [Advanced React Patterns (2017)](https://github.com/kentcdodds/advanced-react-patterns) 🆓 225 | - [Beginner's guide to React (2017)](https://egghead.io/courses/the-beginner-s-guide-to-react) 🆓 226 | - [Survive JS: React, From apprentice to master](https://survivejs.com/react/introduction/) 🆓 227 | - [Building React Applications with Idiomatic Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) 🆓 228 | - [Building React Applications with Redux](https://egghead.io/courses/building-react-applications-with-idiomatic-redux) 🆓 229 | - [Complete intro to React v4 (2018)](https://btholt.github.io/complete-intro-to-react-v4/) 🆓 230 | - [Leverage New Features of React 16 (2018)](https://egghead.io/courses/leverage-new-features-of-react-16) 🆓 231 | - [React Holiday (2017)](https://react.holiday/) - React through examples. 🆓 232 | 233 | ## ReasonML 234 | 235 | - [Get Started with Reason (2018)](https://egghead.io/courses/get-started-with-reason) 🆓 236 | 237 | ## Rust 238 | 239 | - [Rust programming (2016)](http://cis198-2016s.github.io/) 🆓 240 | 241 | ## Scala 242 | 243 | - [Functional programming principles in scala](https://www.coursera.org/learn/progfun1) 💰 244 | 245 | ## Security 246 | 247 | - [Computer and network security (2013)](https://courseware.stanford.edu/pg/courses/lectures/349991) 🆓 248 | - [Hacker101 (2018)](https://github.com/Hacker0x01/hacker101) - Free class for web security. 🆓 249 | 250 | ## Statistics 251 | 252 | - [Introduction to probability - the science of uncertainty](https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2) 🆓 253 | - [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) 🆓 254 | - [Statistical Learning (2016)](https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about) 🆓 255 | - [Statistics 110](https://www.youtube.com/watch?v=KbB0FjPg0mw&list=EC2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) 🆓 256 | 257 | ## Swift 258 | 259 | - [Hacking with Swift (2018)](https://www.hackingwithswift.com/read) 🆓 260 | 261 | ## Type theory 262 | 263 | - [Homotopy Type Theory (2014)](https://www.cs.cmu.edu/%7Erwh/courses/hott/) 🆓 264 | 265 | ## Vim 266 | 267 | - [Vim valley](https://vimvalley.com/) 💰 268 | 269 | ## Web Development 270 | 271 | - [Cutting-edge web technologies (2015)](http://inst.eecs.berkeley.edu/%7Ecs294-101/sp15/) 🆓 272 | - [Interactive Flexbox course (2018)](https://scrimba.com/g/gflexbox) 🆓 273 | 274 | ## Related 275 | 276 | - [Awesome artificial intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) 🆓 277 | - [Awesome courses](https://github.com/prakhar1989/awesome-courses) 🆓 278 | - [CS video courses](https://github.com/Developer-Y/cs-video-courses) 🆓 279 | - [Data science courses](https://github.com/DataScienceSpecialization/courses) 🆓 280 | - [Dive into machine learning](https://github.com/hangtwenty/dive-into-machine-learning) 🆓 281 | 282 | [![CC4](https://img.shields.io/badge/license-CC4-0a0a0a.svg?style=flat&colorA=0a0a0a)](https://creativecommons.org/licenses/by/4.0/) 283 | [![Lists](https://img.shields.io/badge/-more%20lists-0a0a0a.svg?style=flat&colorA=0a0a0a)](https://github.com/learn-anything/curated-lists) 284 | [![Contribute](https://img.shields.io/badge/-contribute-0a0a0a.svg?style=flat&colorA=0a0a0a)](contributing.md) 285 | [![Twitter](http://bit.ly/latwitt)](https://twitter.com/learnanything_) 286 | --------------------------------------------------------------------------------