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[Update April 15, 2019] This blog post covers the 2018 course which you can find here. (Copyright fast.ai) Most approaches teaching machine and deep learning can be cumbersome and time-consuming: Stepping through all the details of (basic) linear algebra, activation functions and slowly building a neural network, so that after a few weeks/months, you are able to build an image classifier, if you have actually powered through… Do not get me wrong, understanding the intuition and fundamentals of linear algebra and neural networks are an important and invaluable asset in achieving great results.

Course: Deep Learning Specialization By: Andrew Ng - Deeplearning.ai (Stanford, Coursera, ex-Google Brain, ex-Baidu, landing.ai) Six years to the day - 15 August 2017 - after releasing his first Machine Learning course, Andrew Ng launched the Deep Learning Specialization on Coursera, with the ambitious goal: I hope we can build an AI-powered society that gives everyone affordable healthcare, provides every child a personalized education, makes inexpensive self-driving cars available to all, and provides meaningful work for every man and woman.