DS 1001

I would not recommend this class if you're not interested in applying to the School of DS. It's incredibely boring and, quite honestly, useless even if you are applying. The material seems random and not applicable. I took it because it's a required course to apply for the school, but after taking it, I'm not even going to bother to apply anymore. There are 4 modules throughout the semester, with 2 very sweet professors teaching 2 modules each. The workload isn't anyhting crazy: 1 reading assignment and lab per week, 4 big writing assignments for the semester, and a final essay. It's doable, but boring.

This course was an easy A but not super interesting. I honestly did not pay attention basically at all in class. There are weekly assignments which typically involve a short reading or video and is the same assignment format for each one. There are labs every Friday that are sometimes confusing but the TAs are very helpful at answering questions. There are a few large assignments all due at the end of the semester, so if you start early they aren't an issue. Overall, it's an easy A but if you are not required to take it, you're not really getting anything out of it.

This course was fantastic. It served as an excellent introduction to the field of data science. I found many of the topics we covered to be interesting, but they generally gave a shallow intro to the content in DS. The guest speakers were the most exciting part of this course - their lectures provided insights on the work and the career paths of data scientists. This course consists of weekly assignments, weekly labs, 4 larger projects, and a final paper. I recommend completing the assignments and projects as they are assigned so that they don't pile up at the end of the semester when they are due.

Alonzi was an excellent instructor. He was engaging and witty, and his style allowed the course to be fun and easy-going.

#tCFF23

I took this class because it's a prereq to apply to the DS major. Its a really easy A because there are no exams and every single assignment is graded for completion with a clear rubric on how to achieve completion. If you get an incomplete grade, you have a whole week to revise and resubmit with 0 penalty (I only had to do this once on the first week). Lab is also really easy and several are skippable and can just be done online.
In terms of the lectures, you could probably skip every single one and still get an A. The lecture slides are posted so if you need a little bit of jargon to complete the assignments, you can just reference those. Professor Alonzi and Wright both seem extremely knowledgeable about the subject and are very open to talking with students outside of class.
The one true drawback of this class is that I didn't get a very good sense of what being a DS major would actually be like. There is very little hands-on application of the stuff we learn (though I guess that happens more in DS 1002) and this course did not do much to help me decide if DS would actually be something I am good at and enjoy.
Overall, you should take this class as an easy-A GPA boost, regardless of whether you are considering pursuing data science.