Coursera has been offering this course since a couple days ago…on Deep Learning Specialization. This is something that will be part of all online learning components. It’s a very large challenge for those who understand learning from a traditional and conventional context. Not to say everyone doing online course development will have or need a deep understanding of Deep Learning, but someone on the “development team” will need to have at least a solid grasp of what is going on.
A larger “understanding challenge” for all using Deep Learning, is that if it’s really good, we probably won’t understand how it works down deep, at least some of the time. AI and machine learning come to output through their own process, and they respond to patterns we might never see or grasp. They can provide us with RTL outputs of great value, but how they get there from a sea of Big Data will be obscure at best, and unfathomable quite often.
Which is one of the reasons for fear of AI…by definition it’s a machine’s logic, not human logic. Kudos to Gary for link.
In five courses, 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.
You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.