Definitely a great class if you're looking to gain some practical IT skills (Data mining). This class is fairly intense, and lots of group work is required, especially for the big project. You have some small quizzes during the year that are pretty easy as well as some reviews of some articles you will have to read (as long as you do it relatively correctly you will get the maximum grade).
You will definitely learn a lot during this class and the project is pretty good to put on resume or to discuss during your interviews.
Regarding grading, Pr. Li is quite a tough grader when it comes to giving A, so most people will end up getting A- or B+.
Again, I could not recommend enough this class, especially if you're specializing in IT.

Professor Li is a very committed professor. She helps whenever she can and is really passionate about her field. This course is recommended for people interested in quantitative methods. However, the course has a tremendous workload. I spent a big part of my time during the semester on this class.

Big Data Analytics is a topic with increasing relevance, which makes the course attractive already. In class, almost all theory (in my eyes too much) is skipped and the focus is on the practical application and development of predictive models, cost-benefit analysis and clustering of customers. Therefore, the open-source software RapidMiner is used. No coding is necessary, the program has a good user interface. In both individual assignments and the group project, students create predictive models. The workload should not be underestimated. However, all in all, it is a highly recommendable and unique class for people who want to get an overview of how to concretely conduct big data analysis. The fact that the group project was a partnership with an online company and that this firm will implement some recommendations increased the (perceived) real-world relevance of the class.