Repository files navigation

Please readcontribution guidelines before contributing.

• Algorithms
• Artificial Intelligence
• Business
• Chemistry
• Compilers
• Computer Science
• Computer vision
• Cryptocurrency
• Cryptography
• CSS
• Decentralized systems
• Deep Learning
• Discrete math
• Functional programming
• Game development
• Haskell
• Investing
• iOS
• Machine learning
• Math
• Networking
• Neuroscience
• Natural Language Processing
• Operating systems
• Programming
• React
• ReasonML
• Rust
• Scala
• Security
• Statistics
• Swift
• Type theory
• Vim
• Web Development
• Related

• Algorithmic thinking 💰
• Algorithms (2010) - Taught by Manuel Blum who has a Turing Award due to his contributions to algorithms. 🆓
• Algorithms specialization
• Algorithms: Part 1 🆓
• Algorithms: Part 2 🆓
• Data structures (2016) 🆓
• Data structures (2017) 🆓
• Design and analysis of algorithms (2012) 🆓
• Evolutionary computation (2014) 🆓
• Introduction to programming contests (2012) 🆓
• MIT advanced data structures (2014) 🆓
• MIT introduction to algorithms 🆓

• Berkeley intro to ai (2014) 🆓
• MIT artificial intelligence (2010) 🆓
• The society of mind (2011) 🆓

• Gamification 💰

• Bioinformatics specialization 💰

• Principles of compiler design (2016) 🆓
• Stanford compiler construction (2016) 🆓

• Computational complexity (2008) 🆓
• Computer science 101 🆓
• Data structures 💰
• Great ideas in computer architecture (2015) 🆓
• Information retrieval (2013) 🆓
• MIT great ideas in theoretical computer science 🆓
• MIT Mathematics for Computer Science (2010) 🆓
• MIT Structure and Interpretation of Programs (1986) 🆓
• Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexity (2018) 🆓
• Software foundations (2014) 🆓
• The art of recursion (2012) 🆓

• Computer vision 🆓
• Introduction to computer vision (2015) 🆓
• Programming computer vision with python (2012) 🆓

• Bitcoin and Cryptocurrency Technologies 🆓

• Stanford cryptography I 💰
• Stanford cryptography II (2017) 💰

• CSS Grid by Wes Bos 🆓

• MIT Decentralized Applications (2018) 🆓

• Advanced Deep Learning & Reinforcement Learning (2018) 🆓
• Berkeley deep reinforcement learning (2017) 🆓
• Deep learning (2017) 🆓
• Stanford natural language processing with deep learning (2017) 🆓
• Deep learning at Oxford (2015) 🆓
• Lectures 🆓
• Oxford CS Deep NLP (2017) 🆓
• Ucl reinforcement learning (2015)
• Stanford convolutional neural networks for visual recognition 🆓
• Stanford deep learning for natural language processing 🆓

• Discrete Mathematics and Probability Theory 🆓

• Course in functional programming by KTH 🆓
• Functional Programming Course 🆓
• Programming paradigms (2018) 🆓
• Functional Programming in OCaml (2019)

• HTML5 game development 🆓

• Advanced Programming (2017) 🆓
• Haskell ITMO (2017) 🆓
• Introduction to Haskell (2016) 🆓
• Stanford functional systems in Haskell (2014) 🆓

• Computational investing 💰

• Developing iOS 10 apps with Swift (2017) 🆓

• MIT Deep Learning (2019)
• Amazon’s Machine Learning University course (2018) 🆓
• Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization - Get hands-on experience optimizing, deploying, and scaling production ML models. 💰
• Artificial intelligence for robotics 🆓
• Coursera machine learning 💰
• Introduction to Deep Learning (2018) - Introductory course on deep learning algorithms and their applications. 🆓
• Introduction to Machine Learning for Coders - The course covers the most important practical foundations for modern machine learning. 🆓
• Introduction to matrix methods (2015) 🆓
• Learning from data (2012) 🆓
• Machine Learning Crash Course (2018) - Google's fast-paced, practical introduction to machine learning. 🆓
• Machine learning for data science (2015) 🆓
• Machine learning in Python with scikit-learn 🆓
• Machine Learning with TensorFlow on Google Cloud Platform Specialization - Learn ML with Google Cloud. Real-world experimentation with end-to-end ML. 💰
• Mathematics of Deep Learning, NYU, Spring (2018) 🆓
• mlcourse.ai - Open Machine Learning course by OpenDataScience. 🆓
• Neural networks for machine learning 💰
• Notes 🆓
• Practical Deep Learning For Coders (2018) - Learn how to build state of the art models without needing graduate-level math. 🆓
• Statistical learning (2015) 🆓
• Tensorflow for deep learning research (2017) 🆓

• Abstract algebra (2019) 🆓
• MIT linear algebra (2010) 🆓
• MIT multivariable calculus (2007) 🆓
• MIT multivariable calculus by Prof. Denis Auroux 🆓
• MIT multivariable control systems (2004) 🆓
• MIT singlevariable calculus (2006) 🆓
• Nonlinear dynamics and chaos (2014) 🆓
• Stanford mathematical foundations of computing (2016) 🆓
• Types, Logic, and Verification (2013)

• Introduction to computer networking 🆓
• Introduction to EECS II: digital communication systems (2012) 🆓

• The Human Brain (2018) 🆓

• YSDA Natural Language Processing course (2018) 🆓

• Computer Science 162 🆓
• Computer science from the bottom up 🆓
• How to make a computer operating system (2015) 🆓
• Operating system engineering 🆓

• Build a modern computer from first principles: from nand to tetris 💰
• Introduction to programming with matlab 💰
• MIT software construction (2016) 🆓
• MIT structure and interpretation of computer programs (2005) 🆓
• Stanford C Programming 🆓
• Structure and interpretation of computer programs (in Python) (2017) 🆓
• Unix tools and scripting (2014) 🆓
• Composing Programs - Free online introduction to programming and computer science.

• Advanced React Patterns (2017) 🆓
• Beginner's guide to React (2017) 🆓
• Survive JS: React, From apprentice to master 🆓
• Building React Applications with Idiomatic Redux 🆓
• Building React Applications with Redux 🆓
• Complete intro to React v4 (2018) 🆓
• Leverage New Features of React 16 (2018) 🆓
• React Holiday (2017) - React through examples. 🆓

• Get Started with Reason (2018) 🆓

• Rust programming (2016) 🆓

• Functional programming principles in scala 💰

• Computer and network security (2013) 🆓
• Hacker101 (2018) - Free class for web security. 🆓

• Introduction to probability - the science of uncertainty 🆓
• MIT probabilistic systems analysis and applied probability (2010) 🆓
• Statistical Learning (2016) 🆓
• Statistics 110 🆓

• Hacking with Swift (2018) 🆓

• Homotopy Type Theory (2014) 🆓

• Vim valley 💰

• Cutting-edge web technologies (2015) 🆓
• Interactive Flexbox course (2018) 🆓

• Awesome artificial intelligence 🆓
• Awesome courses 🆓
• CS video courses 🆓
• Data science courses 🆓
• Dive into machine learning 🆓