List:
- 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
Algorithms
- Algorithmic thinking 14
- Algorithms (2010) 5 – Taught by Manuel Blum who has a Turing Award due to his contributions to algorithms.
- Algorithms specialization 4
- Algorithms: Part 1 5
- Algorithms: Part 2 3
- Data structures (2016) 3
- Data structures (2017) 3
- Design and analysis of algorithms (2012) 2
- Evolutionary computation (2014) 3
- Introduction to programming contests (2012) 2
- MIT advanced data structures (2014) 5
- MIT introduction to algorithms 5
Artificial Intelligence
Business
Chemistry
Compilers
Computer Science
- Computational complexity (2008) 2
- Computer science 101 2
- Data structures 2
- Great ideas in computer architecture (2015)
- Information retrieval (2013)
- MIT great ideas in theoretical computer science
- MIT Mathematics for Computer Science (2010) 1
- 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) 1
Computer vision
- Computer vision
- Introduction to computer vision (2015) 1
- Programming computer vision with python (2012) 1
Cryptocurrency
Cryptography
CSS
Decentralized systems
Deep Learning
- Advanced Deep Learning & Reinforcement Learning (2018) 4
- Berkeley deep reinforcement learning (2017)
- Deep learning (2017) 1
- Stanford natural language processing with deep learning (2017)
- Deep learning at Oxford (2015) 1
- 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 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) 1
- Stanford functional systems in Haskell (2014)
Investing
iOS
Machine learning
- MIT Deep Learning (2019) 4
- Amazon’s Machine Learning University course (2018) 2
- Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization 2 – 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) 1
- 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 1 – 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 1
- 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) 1
Math
- Abstract algebra (2019) 2
- MIT linear algebra (2010) 1
- MIT multivariable calculus (2007)
- MIT multivariable calculus by Prof. Denis Auroux 2
- 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 7
- Introduction to EECS II: digital communication systems (2012) 1
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
Programming
- Build a modern computer from first principles: from nand to tetris 1
- Introduction to programming with matlab 1
- MIT software construction (2016)
- MIT structure and interpretation of computer programs (2005)
- Stanford C Programming 1
- Structure and interpretation of computer programs (in Python) (2017) 1
- Unix tools and scripting (2014) 2
- Composing Programs – Free online introduction to programming and computer science.
React
- Advanced React Patterns (2017) 2
- Beginner’s guide to React (2017) 2
- Survive JS: React, From apprentice to master
- Building React Applications with Idiomatic Redux 2
- Building React Applications with Redux 2
- Complete intro to React v4 (2018)
- Leverage New Features of React 16 (2018)
- React Holiday (2017) – React through examples.
ReasonML
Rust
Scala
Security
- Computer and network security (2013) 1
- Hacker101 (2018) 3 – Free class for web security.
Statistics
- Introduction to probability – the science of uncertainty
- MIT probabilistic systems analysis and applied probability (2010)
- Statistical Learning (2016) 1
- Statistics 110
Swift
Type theory
Vim
Web Development
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