Fundamentals of programming for data science using R. Descriptive statistics, distributions and graphics in R. Relational database management systems including the relational model, relational algebra, database design principles and data manipulation using SQL. An introduction to the concept of big data.
5
UnitsOptional
Grading1, 2
PasstimeNone
Level LimitLetters and science
CollegeOverall really nice prof, cares to get to know her students. The disrespect doesn't make sense on here
Great prof over all, really cares about her students well being. Talked about wanting to help students get into research and was very willing to give career advice outside of class time. You can tell teaching is her passion, and although her style isnt for everyone I think she was great. Don't understand the negative comments, it's unwarranted.
The only thing that mattered about this class was the weekly two sections. I found her lecture to be hard to understand but easy to learn on my own or through my TA. The majority of the grade is fluff which is nice however I felt unprepared for the final which is our only test. Take her class though because I heard the other ones are harder.
She's fine. If you are planning to take pstat 10, I would recommend her. She talks a lot about how to become a data engineer, which is not so related to this course but related to your future job.
Professor Ravat's PSTAT 10 course was well-structured and easy to do well in. Section attendance is mandatory and very helpful. The only issue is her (optional) lectures are very boring and often not helpful. I suspect this may change in the future, so I see no issue with enrolling in her courses.
Genuinely don't understand the Ravat hate on RMP, I thought she was perfect for this course. Lectures and course structure were very organized. No midterm - just biweekly quizzes that could ALL be retaken at the end. Final was not bad either. Only one hw assignment per week. Made the course very approachable and was always asking for feedback!