Teaching yourself ML
The following are good resources to learn AI. I know it is tempting to watch a youtube video and move to the next topic, but it is important to take the courses, solve the homework and try to develop a deep understanding. You are not taking the course for a grade, but for deeper learning (pun intended). I have met many people who talk about ML like it is magic and even use it without understanding the basics of the inner working of an ML algorithm. Given my ties to Stanford university, I am leaning toward resources from there.
Machine Learning (CS229) taught by Andrew Ng of Stanford University: course website, Videos on Youtube
Deep Learning (CS230) taught by Andrew Ng of Stanford University: course website, videos. This course combines 5 courses of DL and it is detailed, with two hours a day, you might need 2-3 months to finish the course.
Convolutional Neural Networks for Visual Recognition (CS231n) taught by Fei-Fei Li of Stanford University: Link to the course website, Link to videos on youtube
Natural Language Processing with Deep Learning (CS224n) taught by Chris Manning of Stanford University: Link to the course, Link to videos on Youtube
Generative Adversarial Networks (GANs), Coursera link
The Computer science department at Stanford University offers a lot of good courses, have a look at the courses here