I haven't seen everything, but here's a review of the course first.. [Advantages] 1. It organizes the prerequisite knowledge well at the beginning 2. The lecture name is CNN, but it is not limited to CNN, and it explains the basics of deep learning (SGD, Backprop, etc.) in detail, so it is easy to understand even if there are some difficult applications later 3. The image preprocessing is also detailed, so even those without basic vision skills can try it (I also recommend listening to Professor Kwon Cheol-min's vision lecture) 4. It is not just a simple CNN image classification, but also a detailed explanation of how CNN has developed recently 5. There are many pictures in the lecture materials for easy understanding [Disappointing points] 1. It is a TF-based lecture, but torch is also...ㅎㅎ [Overall] 5 points. Those who are new to deep learning in the image field should definitely listen to it, and those who are just new to deep learning should also listen to it because the basics of deep learning are explained in detail. CNN itself is honestly being used not only for images these days, but also for NLP and predictive modeling, so it is good to understand CNN deeply and utilize it.