professor
Kathleen McKeown

Apr 2021

There is absolutely no reason you should take this course unless you want to have the most miserable semester of your life.

Feb 2020

Both the professor and the class materials are awesome. This is one of the best courses I have taken in Columbia. Professor McKeown’s class provides a very comprehensive overview of NLP. Topics include language models, neural networks, word embeddings, sentimental analysis, POS tagging, parsing, semantics, machine translation, summarization. The class materials and the homework assignments are a very good combination of theory and coding. For theory, we learn parsing algorithms, read word embedding papers, study the math formula behind those frequently used neural networks. For practice, we implement our own model to do stance prediction, sentimental analysis and machine translation. Assignments often go beyond simple code implementation. Instead, most of the assignment focuses on analysis of the models that we built – analysis of model performance, error analysis on frequent mistakes made by the model, comparison of different methods and models. These analysis techniques turn out to be very useful in real-word applications, and really distinguish those who know NLP from those who only know how to use packages. Professor McKeown is a very nice person who actually cares about every student that she teaches. She is the first professor that I’ve met with in Columbia who does her best to really remember almost everyone’s name in the classroom (it’s a class of approximately 100 students!) She enjoys meeting with students during office hours, providing not only help for class materials/assignments but also invaluable discussions about students’ future career development and general academic interest. Professor McKeown also knows well about how to teach. She does her best to make the class to interesting to everyone. She is a professor who really does her best to make sure everyone is following and understanding her lectures. She highly values class participation and interaction between professor and students, but speaking up in class is not mandatory for students to get participation points. Fully recognizing that some students may be shy about asking questions or speaking up publicly in class, she uses poll everywhere instead in class to collect students’ feedback and questions to see if anything is unclear to the students. The course materials are very interesting in itself, and I’m especially amazed by the guest lectures of the course. Professor McKeown invited some of her former students who are now working in the industry to give guest lectures. One lecture that is especially inspiring is on dialog systems, where we get to know how dialog systems such as Siri and Alexa are built. Guest lectures from distinguished industry pioneers give the students another perspective on NLP from the industry. The professor also makes sure that the class materials are up-to-date. NLP is a fast-changing field with lots of new concepts and techniques invented each year. Besides the basic materials and concepts of NLP, she also provides a brief walkthrough of a few recent breakthroughs in the academia. For example, we read together in class papers on BERT (a really cool and useful tool that’s very famous) and papers on biases (a really cool and influential topic that appeared in recent years). Students interested in going to the academia or industry get to know these state-of-the-art results and techniques, which bridge the gap between school and future career. Overall, I highly recommend Professor Kathy McKeown’s class to anyone interested in NLP or anyone interested in knowing more about computer science. The class materials are awesome. The professor is extremely amazing. You will learn a huge amount out of this class.

Nov 2019

Horrible Horrible Class. Homework is almost completely unrelated to what is gone over in class. Class is boring and long with PollEverywhere scattered here and there. Homework basically consists of throwing a bunch of model at a wall and see what sticks, can be fast if you have some applied machine learning background but you literally learn nothing from the homework other than getting frustrated with the libraries. Only upside is Kathy is a great human being who genuinely cares about her students - she literally remembers everyone's name, but that's about it. She doesn't make the course any more interesting.

Mar 2009

She did a good job of covering the material and explaining what she expected for the midterms. About what you'd expect for this level class. There was a curve. http://www1.cs.columbia.edu/~kathy/NLP/

Jan 2006

A very good class and professor. Taking Artificial Intelligence with Professor Mckeown convinced me to pursue AI and computer science further. Very highly recommended.

Jan 2006

I took this course in the Spring of 2004 and found it challenging and useful. The course covered the requisite material thoroughly, and offered intriguing (and sometimes quite difficult) programming assignments. Other reviewers complain about the focus on 'boring algorithmic parts' and lack of attention to philosophical implications. This is both ironic and inaccurate on a number of counts. First, the early part of the course was dedicated to a thorough consideration of the difference between human-like and rational behavior; in addition, a number of readings were posted over the term that addressed just these issues. Second, this course is offered in a computer science department; the capacity of computer scientists to have impact on scientific or philosophical problems is founded in the algorithmic details. Glossing over this material would cheat serious students who are willing to do the work. I enjoyed the course and still discuss and apply the material I learned.

Apr 2005

Prof McKeown is a nice lady. Let's say that first. She's a pretty lousy professor, though. It's hard to tell whether she's just bored with the material, or doesn't know how to make it interesting, or just doesn't care. In any event, her classes consist of a series of slides that are pretty much straight from the textbook, and a lecture delivered in monotone. She seems actively disinterested in any of the interesting intellectual, scientific, or philosophical implications of the material, and instead grinds through the most boring algorithmic parts, yet without enough detail or mathematical sophistication to make it worthwhile. Avoid if possible.

Jul 2004

A very nice professor who cares enough to learn everyones name in the relatively large class. But I don't think she was born to teach. She is very well prepared in that she has everything on powerpoint, but she's not so great at answering questions that aren't in the powerpoint plan. She's also rather bad at coming up with good test questions, asking students to go through every step of an algorithm that is easy for computers, but painfully tedius for humans, and making that worth almost half the midterm. (And giving a full blue book for it). The subject is fascinating, and if no one else is teaching it, I still highly recommend taking it. Kathleen Mckeown is a great professor if you want a friend and a nice office hours buddy, is knowledgeable and cares, but just isn't a born teacher.