A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers
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Awesome Artificial Intelligence (AI)

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Contributions most welcome.


Online Courses

  • MIT Artifical Intelligence Videos - MIT AI Course
  • Intro to Artificial Intelligence - Learn the Fundamentals of AI. Course run by Peter Norvig
  • EdX Artificial Intelligence - The course will introduce the basic ideas and techniques underlying the design of intelligent computer systems
  • Artificial Intelligence Planning - Planning is a fundamental part of intelligent systems. In this course, for example, you will learn the basic algorithms that are used in robots to deliberate over a course of actions to take
  • Artificial Intelligence for Robotics - This class will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics
  • Machine Learning - Basic machine learning algorithms for supervised and unsupervised learning
  • Neural Networks for Machine Learning - Algorithmic and practical tricks for artifical neural networks.
  • Stanford Statistical Learning - Introductory course on machine learning focusing on: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.

Books About Artificial Intelligence


Philosophy of AI

Free Content




  • Deep Learning. Methods and Applications Free book from Microsoft Research
  • Neural Networks and Deep Learning - Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning
  • Machine Learning: A Probabilistic Perspective - This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach
  • Deep Learning - Yoshua Bengio, Ian Goodfellow and Aaron Courville put together this currently free (and draft version) book on deep learning. The book is kept up-to-date and covers a wide range of topics in depth (up to and including sequence-to-sequence learning).