Professor
Quanquan Gu
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Most Helpful Review
Winter 2019 - I can see where the negative reviews come from regarding the course content since ppl would expect AI courses to be modern and fun instead of theories. While I agree with that, I do want to add my personal thoughts regarding the problem. There are also other professors besides prof. Gu who teach this course and cs department requires them to teach the same materials (otherwise it would be unfair for both teachers and students in different quarters). this intro level AI course was designed years ago and ofc it is a little outdated, but the content can hardly be changed unless the department decides to. I guess for ppl complaining here, it would be better if you talk to cs dept directly instead of giving a low rating for some professors... Regarding the professor, I took the course when the pandemic hit in 2020 and everything was a mess. I think the professor is knowledgeable and cared a lot about course quality and did a great job accommodating students' needs. I do agree that sometimes the slides are too brief and the textbook definitely gives a more thorough explanation. BUT that is based on if you don't listen to the lecture at all and just reading the slides. Based on my personal experience, it is easier to understand the materials when I went to the lecture with professor's demo. For TAs, I would agree that they were not that helpful comparing with TAs from other courses. but I do not think they were being lazy (at least mine wasn't) Their speaking skills are not too good so it's difficult to understand, but they were willing to stay after discussion with me to make sure my concerns were resolved. The HWs and tests are doable as other comments said. In general, I think this course is a descent intro-level AI course that shows/prepares you the fundamentals behind the fancy side of AI/ML. I also consider it as a good elective with very manageable workload and easy A.
Winter 2019 - I can see where the negative reviews come from regarding the course content since ppl would expect AI courses to be modern and fun instead of theories. While I agree with that, I do want to add my personal thoughts regarding the problem. There are also other professors besides prof. Gu who teach this course and cs department requires them to teach the same materials (otherwise it would be unfair for both teachers and students in different quarters). this intro level AI course was designed years ago and ofc it is a little outdated, but the content can hardly be changed unless the department decides to. I guess for ppl complaining here, it would be better if you talk to cs dept directly instead of giving a low rating for some professors... Regarding the professor, I took the course when the pandemic hit in 2020 and everything was a mess. I think the professor is knowledgeable and cared a lot about course quality and did a great job accommodating students' needs. I do agree that sometimes the slides are too brief and the textbook definitely gives a more thorough explanation. BUT that is based on if you don't listen to the lecture at all and just reading the slides. Based on my personal experience, it is easier to understand the materials when I went to the lecture with professor's demo. For TAs, I would agree that they were not that helpful comparing with TAs from other courses. but I do not think they were being lazy (at least mine wasn't) Their speaking skills are not too good so it's difficult to understand, but they were willing to stay after discussion with me to make sure my concerns were resolved. The HWs and tests are doable as other comments said. In general, I think this course is a descent intro-level AI course that shows/prepares you the fundamentals behind the fancy side of AI/ML. I also consider it as a good elective with very manageable workload and easy A.
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Most Helpful Review
Spring 2020 - The professor is truly knowledgeable on the theory of machine learning. The first part of the class, regarding the theory and the proof is interesting, where he successfully made the rigorous mathematical proof easy to follow and enhanced our understanding of Machine Learning. The second part is more practical comparing to the first half of the class.
Spring 2020 - The professor is truly knowledgeable on the theory of machine learning. The first part of the class, regarding the theory and the proof is interesting, where he successfully made the rigorous mathematical proof easy to follow and enhanced our understanding of Machine Learning. The second part is more practical comparing to the first half of the class.
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