Please read the contribution guidelines before contributing.
The number after the course name stands for the year in which the course was made in. All courses are put in their respective category and are sorted from oldest to newest. If no year was found for the course, it is put in the end of the list.
- Compilers
- Statistics
- iOS
- Investing
- Security
- Business
- Cryptography
- Web Development
- Game development
- Chemistry
- Operating systems
- Algorithms
- Functional programming
- Math
- Networking
- Neuroscience
- Computer vision
- Artificial Intelligence
- Machine learning
- Computer Science
- Deep Learning
- Haskell
- Rust
- Scala
- Programming
- CSS
- Related
- Introduction to probability - the science of uncertainty
- MIT probabilistic systems analysis and applied probability (2010)
- Statistics 110
- Computer and network security (2013)
- Hacker101 (2018) - Free class for web security.
- Advanced React Patterns (2017)
- Beginner's guide to React (2017)
- React Holiday (2017) - React through examples.
- Leverage New Features of React 16 (2018)
- Building React Applications with Redux
- Building React Applications with Idiomatic Redux
- How to make a computer operating system (2015)
- Operating system engineering
- Computer science from the bottom up
- Computer Science 162
- Algorithms (2010) - Taught by Manuel Blum who has a Turing Award due to his contributions to algorithms.
- Design and analysis of algorithms (2012)
- Introduction to programming contests (2012)
- MIT advanced data structures (2014)
- Evolutionary computation (2014)
- Data structures (2016)
- Data structures (2017)
- Algorithms: Part 1
- MIT introduction to algorithms
- Algorithms: Part 2
- Algorithmic thinking
- Algorithms specialisation
- MIT multivariable control systems (2004)
- MIT singlevariable calculus (2006)
- MIT multivariable calculus (2007)
- MIT linear algebra (2010)
- Nonlinear dynamics and chaos (2014)
- Abstract algebra (2014)
- Stanford mathematical foundations of computing (2016)
- MIT multivariable calculus by Prof. Denis Auroux
- Programming computer vision with python (2012)
- Introduction to computer vision (2015)
- Computer vision
- Learning from data (2012)
- Machine learning for data science (2015)
- Introduction to matrix methods (2015)
- Statistical learning (2015)
- Tensorflow for deep learning research (2017)
- Practical Deep Learning For Coders (2018) - Learn how to build state of the art models without needing graduate-level math.
- Introduction to Deep Learning (2018) - Introductory course on deep learning algorithms and their applications.
- Machine Learning Crash Course (2018) - Google's fast-paced, practical introduction to machine learning.
- Mathematics of Deep Learning, NYU, Spring (2018)
- Coursera machine learning
- Artificial intelligence for robotics
- Neural networks for machine learning
- Machine learning in Python with scikit-learn
- Computational complexity (2008)
- The art of recursion (2012)
- Information retrieval (2013)
- Software foundations (2014)
- Great ideas in computer architecture (2015)
- Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexity (2018)
- MIT great ideas in theoretical computer science
- Computer science 101
- Data structures
- Deep learning at Oxford (2015)
- Ucl reinforcement learning (2015)
- Oxford cs deep nlp (2017)
- Deep learning (2017)
- Berkeley deep reinforcement learning (2017)
- Stanford natural language processing with deep learning (2017)
- Stanford deep learning for natural language processing
- Stanford convolutional neural networks for visual recognition
- Stanford functional systems in haskell (2014)
- Introduction to haskell (2016)
- Advanced Programming (2017)
- Haskell ITMO (2017)
- Unix tools and scripting (2014)
- MIT structure and interpretation of computer programs (2005)
- MIT software construction (2016)
- Structure and interpretation of computer programs (in Python) (2017)
- Build a modern computer from first principles: from nand to tetris
- Introduction to programming with matlab
- Stanford C Programming
- Awesome courses
- Data science courses
- CS video courses
- Awesome artificial intelligence
- Dive into machine learning
For more lists like this, see here.
