Deep Learning is one of the most highly sought after skills in AI. In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more.

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 1 – Class Introduction and Logistics

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 2 – Deep Learning Intuition

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 3 – Full-Cycle Deep Learning Projects

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 4 – Adversarial Attacks / GANs

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 5 – AI + Healthcare

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 6 – Deep Learning Project Strategy

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 – Interpretability of Neural Network

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 – Career Advice / Reading Research Papers

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 9 – Deep Reinforcement Learning

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 10 – Chatbots / Closing Remarks

Source: http://onlinehub.stanford.edu/cs230