Sorry, it may just be issues with your English, but I don’t understand most of your questions.
I don’t have enough information based on what you’ve said to say anything about that quiz question (item 2 in your original post), but Prof Ng does mention in the lectures that there are some types of predictions where human performance is not very good compared to what is possible with ML models. Examples that I remember are recommender systems and predicting which link on a webpage a user will click next. Bayes Error is the lowest error that is possible on the task and all we can say is that both Human Error and Model Error are greater than or equal to the Bayes Error. For image classification tasks (does this picture contain a cat?) the human visual cortex is pretty hard to beat so HE \leq ME in most of those cases. But there are cases in which HE > ME, as in the recommender system case that Prof Ng mentioned and one other example that comes to mind is the famous Google AI model that can detect the sex of patients from their retinal scans, which human opthalmologists had previously thought was impossible.
It might be worth just watching the lectures again.