Introduction to data science. Concepts of statistical thinking. Topics include random variables, sampling distributions, hypothesis testing, correlation and regression. Visualizing, analyzing and interpreting real world data using Python. Computing labs required.
5
UnitsOptional
Grading1, 2
PasstimeNone
Level LimitLetters and science
CollegeYour TA really determines how well you do in the class, and it feels like you teach yourself throughout the entire course with the way it is structured.
SO sweet, can tell she genuinely cares about the success of her students. Go to her office hours! Even if you don't have a question, learning from other people's questions helped me do really well in this course.
Swenson is super caring and is very accessible if you have questions. If you can, attend office hours for more personalized teaching. The class gets a bit tricky later on with a lot of methods/formulas to memorize but an A is very achievable with good effort.
Lectures are online, section is learning basic Python and doing worksheets based off the (optional) homework. The material itself was moderate in difficulty. Math required for the class is just simple Algebra and factorials, and a good calculator. Midterms/quizzes were very similar to the homework. If you ACTUALLY do the homework, youll be fine.
Professor seems sweet, but if you don't have a good TA you're screwed. She posts lecture videos then recaps them (at a snails pace) during the weekly lecture, but it feels as though you're expected to teach yourself. Learned practically nothing about Python, the class was math heavy. Can't emphasize enough that your experience depends on your TA.
great lecturer, extremely helpful online videos, quizzes are basically the same as homework so easy points. The two midterms are easy, the final was a bit hard