COMS BC1016

assignments had nothing to do with the lectures and vice versa so i taught myself all of the content, grading was different compared to which TA you got, he never gave me feedback on my final project

You will end with an A if you get a 92 or above. I ended with an A, but regardless, the professor was terrible and did not help at all no matter what (office hours, after class, via email, etc.). We had no homework for the first four weeks and the rest of the term was disorganized. She was never clear about what the midterm would be and kept changing her answer about it until two weeks before. Because of this, the workload was usually light besides overstudying for a mystery midterm and dealing with a final project without help or guidance (and being completely new to coding---this class is intended for new coders). The final project is worth 50% of the grade which added to the stress of this course. I don't think she will be teaching this class again, so at least for the next term, people can actually learn from a professor and not have to figure it out on their own and be extremely frustrated with this professor's incompetence the entire term.

No final exam but a final group project worth 45%. Midterm is worth 20%, 35% HW assignments. Labs are 50% the actual lab and 50% attendance. The class took up way more of my week than I had realized.

this guy absolutely sucks never take his classes he does not know how to teach and he is infuriating

I expected the professor to show up to class and know how to teach---Lisa Soros did not meet these expectations. She consistently did not show up to class without warning so my classmates and I would sit there for an hour doing other work and complaining about her incompetence. This class felt like a waste of tuition because it was an online Berkeley course and the professor didn't teach us anyway (could have easily learned the limited Python we did by myself). Honestly, the worst teacher I have ever had because even when she did show up, she did NOT want to be there and would mumble through information we were already self-teaching ourselves with (so not helpful at all). Class attendance was low because of this but I showed up alongside a few other students just to see if we did something helpful (we never did).

The professor is really nice and some of the content is interesting! It's mainly for people who don't know CS and the class moves quite fast for an intro-level course. For me, the midterm was really difficult, and not like the practice midterms at all. The average brought the curve up and some people did well but it was just much more difficult than anything we had done in class. Attendance isn't counted and you can tell the prof is really excited about data science. My issue with this class was just the amount of work you have to do and understand at once. Beyond the class twice a week is a 1.5 hour lab (attendance mandatory) which is due every Sunday, and HW due every Wednesday.

Average workload 10 HWs, 1 every week 2 projects (basically like longer more complicated hws) capstone project - pick a dataset and do some analysis on it (not a lot of guidelines, very open ended) weekly lab participation

Ten weekly homeworks and ten assignments completed in the lab section that were the same format as the homework. Everything is graded by the TAs, who also maintain the Ed discussion board. Some assignments were definitely easier than others and could be completed in less than an hour, while others were tedious because of small mistakes with nondescript errors from the Jupyter auto-grader.

Agree with the previous review; Professor Moretti is a really nice guy, but what he goes over in lecture is confusing rarely related to data science. He mostly taught derivations and linear algebra. It can be intimidating, especially for someone with no coding background even though this class doesn't have any prerequisites. However, if you read the text book, you should be fine. The textbook was developed specifically for this course so all of the information in there is relevant to the HWs and Projects. You actually learn tons of useful skills in this class by reading the textbook and doing the homeworks. The final project was really fun. We got to pick any dataset we wanted and analyze it in whatever way we chose.

I have very mixed feelings about this class. Soros is nice and helpful in office hours, but the dwindling attendance throughout the semester should tell you that she's not the most engaging lecturer. The curriculum is imported from Berkeley and available completely online, so the only incentive to go to class is the small participation credit. Overall, the professor is just okay, and the course needs serious restructuring.