Hi, I have a simple question: I want to master AI at the state of the art with a deep understanding of it. Do I take Machine Learning course first or directly go to Deep Learning course?
Does ‘Machine Learning Course’ teach state of the art methods or they are not used anymore ?
I am a beginner so please take my advice with a grain of salt.
As far as I understand, deep learning is only useful if you have a lot of data. For smaller amount of data you should be using traditional machine-learning.
So it depends on you. Jeremy mentions that you can go to deep learning course without machine learning one and if you want to do so you can
Thank you Artur. So you know when it becames more interesting to use deep learning instead of classical machine learning? How big the data should be?
Both of them are about state of the art algorithms I think. Just pick one (or even 2) and follow. In ML course, Jeremy clarify more the basic function from the beginning while in DL course, he uses top-down approach and at the first class, you don’t know what exactly going on in the function.
Deep Learning is not exactly for only massif data. I am doing the Deep Learning v3 and with transfer learning, someone can create a model with >90% accuracy with only about hundred of pictures. 
it is for computer vision, I don’t have much experience in other fields without transfer learning.
So the choice is yours, if you are comfortable with understand deeply what you are doing so take the ML course first. If you consider more about the result and from time to time you will review the concept, then take DL
Hope that helps,
I found a decent article where I found the answer for this question: https://towardsdatascience.com/deep-learning-vs-classical-machine-learning-9a42c6d48aa