DS 2006

I would advise students not to take this class unless they have prior experience with R. I had taken CS 1110 and STAT 1602 prior (both python), and even still I struggled to keep up. While Prof Stewart was such a sweet man, he did not take time to explain how to code in R, the applications were advanced (and therefore really difficult to understand without a foundation in R), and the exams were astronomically difficult where perhaps one student (maximum) finished before the class period was over. While the structure of the class was forgiving (the exam grades could replace each other), it still was extremely difficult to score well on the exams without the heavy curve applied. I'm sure this class would have been fascinating had it been available to only students further in their data science career, but when advertised as a introductory course, it was a headache and totally pushed me away from taking further courses.

Overall, I think my success in the class came from already knowing programming and probability concepts which are what this class is all about. I think if I didn't know these two things beforehand, the class would be a bit more challenging, as he didn't really go too in-depth with coding in R, and I found he explained mathematical concepts a bit too abstractly, which I could tell made it hard for other students to grasp at times. Fortunately, the course is structured in a forgiving way (e.g. midterms can replace each other, being able to resubmit projects, etc.). #tCFS24

Do not take this course under any circumstance.

Instructor mentioned needing no prior knowledge to succeed in this class, however, you can only do well on exams if you have past coding knowledge. We have exam prep questions, but actual exams are much harder

Complete shitshow.