It is a cool class and you learn quite a lot. The professor is fairly ok at explaining concepts; however, the guest lecturer was bad (who lectures 2 weeks). Some of the big data algos near the end were interesting and pretty relevant. We start off with clustering and classification, mainly going into the different types of algos you wouldnt see in undergrad, like DBSCAN, CLARA, etc. Then we move to the interesting topics like graph learning, language models and pattern mining. And then we have a final at the end of week 7, which was a bit too tough and probably double the length of the practice. Then followed by weeks of Paper and Project presentations. Imo I dont think we need so much time for Paper presentations. The TAs were very good. The grading was very slow.
• Assignments 30% (2 big homeworks)
• Exam 25%
• Paper presentation 10%
• Final project 35%
I think the curve was very generous, given the shitty final scores.

We were given plenty of time for each homework assignment, which is great because each assignment was 15% of our grade. The midterm was difficult and mostly reflected the lecture materials, but some questions seemed unrelated to the lecture topics. It has been taking a very long time to receive our grades back, which is difficult because we don't know where we stand in the class and the final is in a week! It was difficult/slow to get a response from the TA or professor for help with the homework assignments. A sample midterm and final was provided but was not representative of the difficulty of the exam at all.