Courses 
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- 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
Algorithms
- 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
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Artificial Intelligence
Business
Chemistry
Compilers
Computer Science
- 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)
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Computer vision
- Computer vision
🆓 - Introduction to computer vision (2015)
🆓 - Programming computer vision with python (2012)
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Cryptocurrency
Cryptography
CSS
Decentralized systems
Deep Learning
- 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
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Discrete math
Functional programming
- Course in functional programming by KTH
🆓 - Functional Programming Course
🆓 - Programming paradigms (2018)
🆓 - Functional Programming in OCaml (2019)
Game development
Haskell
- Advanced Programming (2017)
🆓 - Haskell ITMO (2017)
🆓 - Introduction to Haskell (2016)
🆓 - Stanford functional systems in Haskell (2014)
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Investing
iOS
Machine learning
- 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)
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Math
- Abstract algebra (2014)
🆓 - 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)
Networking
- Introduction to computer networking
🆓 - Introduction to EECS II: digital communication systems (2012)
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Neuroscience
Natural Language Processing
Operating systems
- Computer Science 162
🆓 - Computer science from the bottom up
🆓 - How to make a computer operating system (2015)
🆓 - Operating system engineering
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Programming
- 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.
React
- 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.
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ReasonML
Rust
Scala
Security
- Computer and network security (2013)
🆓 - Hacker101 (2018) - Free class for web security.
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Statistics
- Introduction to probability - the science of uncertainty
🆓 - MIT probabilistic systems analysis and applied probability (2010)
🆓 - Statistical Learning (2016)
🆓 - Statistics 110
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Swift
Type theory
Vim
Web Development
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🆓 - Dive into machine learning
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