This is the program I followed in the last year to learn Machine Learning, especially Deep Learning and gain an in-depth knowledge in each and every of the most common AI fields, namely Computer Vision, Natural Language Processing and Deep Reinforcement Learning. All the material is taught by top world experts and researchers.

I hope that it'll be of any help to those of you who want to have a full and in-depth overview of these amazing field.

NB: all the lectures are free except for the Deep Learning Specialization by Andrew Ng but that I highly recommend.

To get a full overview of each 'chapter' and test my skills, I did a project that required a few months of work. They have been extremely important to get the hands dirty on each subject and to develop the skills required in the ML projects. I highly advise you to do the same.

Artificial Intelligence is the New Electricity — Andrew Ng

• Lectures: MIT 6.034 Artificial Intelligence

• Lectures: Machine Learning, Coursera-Stanford
• Book: Hand-On Machine Learning with Scikit-learn and Tensorflow, Aurélien Géron

• TrackML Particle Tracking Challenge

• Lectures: Deep Learning Specialization, Coursera-deeplearning.AI
  • Neural Networks and Deep Learning
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
  • Structuring Machine Learning Projects
  • Convolutional Neural Networks
• Book: Deep Learning, Ian Goodfellow

• Lectures: Natural Language Processing with Deep Learning, Stanford

• Quora Question Pairs

• Lectures: Convolutional Neural Networks for Visual Recognition, Stanford
• Lectures: MIT 6.S094: Deep Learning for Self-Driving Cars

• Statoil/C-CORE Iceberg Classifier Challenge

• 60 Days RL Challenge
  • Lectures: Deep Reinforcement Learning, Berkley
  • Lectures: Reinforcement Learning, DeepMind
  • Book: Reinforcement learning, Sutton

• 60 Days RL Challenge
• Pommerman

• Lectures: MIT 6.S099: Artificial General Intelligence