John Cunningham

I learned a lot from one of the best professors in the department. Besides the theory you get a better understanding of how to think and tackle problems in real world which I find extremely interesting. We speak about the things and prepare for every class, which I really like.

20% - Weekly Homework - 2-3 hours a week, lowest two grades dropped. 40% - Midterm - 2 easy questions 1 hard - average 55% 40% - Final - 3 easy questions 1 hard Very Generous Curve. One standard deviation above the average is an A+.

6 homeworks with math and code. 2 exams with a cheatsheet.

TLDR: Take him if you want to have a good mathematical intuition of stats and like challenges. If you hate math and thinking, then take the others. The Good: Professor Cunningham is the best professor to have if you're genuinely interested in Statistics. He makes sure that the class understands the mathematical intuition behind concepts like linear regression and hypothesis tests. He's extremely good at answering questions. I once asked a completely nonsensical question in class and his answer somehow made complete sense. His jokes are as dry as the subject material, but they're still funny. He's also always willing to talk with students. Stay after class and sometimes you can ask him about his time in Wall Street or general career advice that's very helpful. It's very obvious he cares about teaching and he goes out of his way to make very good practice finals and study guides. I've also heard that he's pretty good looking; so that's an added plus if that helps you pay attention during lecture. The midterms and finals are a set of easy questions (reworded versions of problems explained in class) followed by a question that nearly no one gets and requires you to extrapolate from concepts in lecture. Finally, there's a great curve. So even if the class is kind of hard, the class will still inflate your gpa. The Bad: The homework is really random and obnoxiously tedious. Zero tol…

Comparatively speaking, this course has been a superior experience in terms of imparting knowledge and tools in introductory statistics from any predecessor that I have taken. Professor Cunningham possesses an unmatched passion for his field that is as refreshingly tangible as it is infectious. The curriculum is crafted in a structured, organized, and accessible manner and Cunningham’s lectures are delightfully animated by his witty antics and desire to thoroughly communicate the topics at hand. Through adjustments implemented during the semester, Cunningham has demonstrated that he is both receptive and encouraging when it comes to feedback from his students. There was, however, an illusion at certain points in the semester, (that existed predominantly in the first half) that I was taking two courses instead of one due to the large disparity between what we were being taught in lecture and what the readings and assignments were on. By its nature, this class is oftentimes heavily bogged down with mathematical proofs and intricate notation. Cunningham was mostly able to navigate this well, though he tends to sacrifice simplicity by heavily embellishing points that could otherwise be delivered far more optimally. If he were to thoroughly follow through on some of the exercises he had inventively illustrated in his lecture slides, I feel students would be better able to intuit co…

A fun class in machine learning. We covered a lot of basic algorithms that are important to machine learning, and we did it through a statistical lens, learning a lot about statistical modelling. One of the goals was building intuition for machine learning, and I would say it was achieved successfully. However, at times, I felt this came at the cost of skipping formal proofs. Although the algorithms seem to work in reasonable cases, there is never a real definition of the learning problem we are trying to solve. In this way, the classes seemed more about applying machine learning algorithms than proving their correctness. The homeworks were reasonable, each had some math and some programming. We worked in R, and it was fairly easy to translate mathematical notation into code. The first exam was extremely challenging, the second was very easy. Presumably professor Cunningham is still trying to strike a balance there. You need to know linear algebra to take this course. Some statistics and programming wouldn't hurt either.

1 Midterm (Hard as ****. Average around 55). One final. 10 homeworks that drive you insane, but he drops two.

5 homeworks (if you use the allotted two weeks, then it is light. Otherwise it is heavy), 20% 1 midterm, 40% 1 non cumulative final, 40%

The worst class I've ever taken at Columbia! First of all, the homework material does not reflect what we cover in class (when we asked him if we have to know the material that was covered in the homework, Cunningham had no idea what the hell we were talking about because he is not the one assigning the homeworks--the TAs do that). Secondly, he mostly covers proofs and concepts in class rather than solving problems. Although I am perfectly okay with that, as a consequence of his homework not being reflective of the material we must know for the class, we get absolutely no practice for preparing for the exams (Oh btw, his exams are probably one of the most hardest exams I have ever taken at Columbia so far). It's a sign that there's something wrong with the professor when he covers concepts like Poisson distributions, ANOVA, logistic regression that even people taking higher level statistics classes right now had not yet learned or had just covered them in their 4000 level classes. If you want to keep your sanity, avoid Cunningham. His class is five times harder than intermediate level CS and Econ. classes I'm taking right now, COMBINED.

This class was easily one of my favorite classes I have taken at Columbia. As an undergrad who is not in the statistics department, I sometimes had to play some catch up on some of the statistical background, but it was totally worth it. Cunningham is, in my view, the ideal Columbia professor. He expects a lot of his students, he won’t be easy on you, he doesn’t put up with student bullshit (turning in homework late, cheating on exams, etc.), but is extremely good at teaching the material, and always happy to answer questions. He is also insanely hot. The pace of the class is heavily dictated by students asking questions to slow him down. For the first 3 weeks or so, people wouldn’t raise their hands when Cunningham stopped for questions, so he would move on assuming we were ready to go. Once people got comfortable asking questions in a large classroom, the pace slowed, he reviewed stuff that people were confused about, and things hit their stride. He is extremely good at explaining the concepts of the various algorithms through examples, diagrams, demonstrations, etc. As such, one walks away with a very good understanding of what the pros and cons of various algorithms are. His slides are quite detailed, and if you take the time to understand everything on there you will be golden. He supplements the slides with hand written examples and notes when necessary. This isn’t a pro…