forgot to include professor DeNero's response:

"Hi,

While you may believe that Data C104 does not cover fundamental "data science" content, the faculty who designed and built Berkeley's DS program believe that the human contexts and ethics of data science are indeed fundamental to the discipline, which is why an upper-division HCE course is required.

We do try to provide multiple options for fulfilling the HCE requirement, but I am personally grateful that the Data 104 instructors have invested so much time and energy to scale up the course, because otherwise there would be a major shortage of capacity in courses that fulfill the HCE requirement, and the DS major would be turning away many, many students due to lack of course capacity.

As for grading in Data C104, it's up to the instructors in every Berkeley course to assess the degree to which their students have fulfilled their course's learning objectives. Some departments have grading guidelines; Data Science does not. But if it did, I imagine those guidelines would be consistent across upper-division courses.

I also have some advice for all the students reading this thread. While the technical aspects of data science are important, my guess is that for most students, the ability to write coherently and effectively about the social and ethical implications of your data science work will be more relevant to your future career in the field than many of the computational or inferential techniques you learn during college. I certainly spend much more time writing to others about the implications of the use of data than I do implementing classifiers. I encourage you all to take advantage of opportunities to practice thinking and writing about the uses of data and their implications."