Machine Learning (English): Very pitiful, and the course arrangement is unreasonable. You should spend 5/6 of the time talking about various models and 1/6 of the time showing it, otherwise you won't learn anything at all. There is too much difference in capacity, svm, decision tree, and gmm are not mentioned at all.
Data Mining: Not being able to use python for big jobs is disgusting. Lack of engineering explanations. Others are fine.
Artificial Intelligence: Being overly rigid in textbooks, talking about things that used to be useful but are now overturned. I talked about many aspects of the reinforcement learning model, but it is not a system. After reading it, I cannot do a reinforcement learning project by myself.
Neural computing: I talked about differential manifolds. This thing does not belong to neural networks, it is difficult to understand, and the effect is not as good as rbm. Others are fine.
Formal language: lack of engineering explanations, such as how fsm is used for json parsing. Others are fine.
Software protection: It only talks about institutional protection, not technical aspects (such as reinforcement and reverse engineering).
Introduction to Information Security: It is completely about cutting-edge, reading papers, without any introductory meaning. In addition, the practice of ctf questions is lacking.