Itshack Pe'er

Computing in Context, in case you are unfamiliar, is a class lectured primarily by Adam Cannon but has different sections, much like UWriting. There are three undergrad contexts available: Humanities, Finance, and Biology. I was under the naive and optimistic that, as a biochemistry major, the biology section was going to teach me useful skills and techniques in Python that I could use to both complete the class and do better as a scientist. Unfortunately, Pe'er is the lecturer for the biology context. I should have seen the first red flag for what it was: when Cannon informed us that there was only one recitation section (per week) and one TA for the bio section, while humanities and finance have at least 15 of each, due to the lack of people who choose to take the bio context. I thought it was because not many people in the class are interested in bio, but of course that doesn't make much sense considering CS is a STEM field. Instead, it turned out to be because Pe'er is undoubtedly, unequivocally, the worst lecturer I have ever had the displeasure of witnessing. Of the 6 or 7 lectures he gave throughout the semester, not one was well-thought out or lectured intuitively. He seemed to not know where his own PowerPoint was going, and was entirely too often surprised by what the next slide showed. He has a heavy accent, which in itself would not be a problem if he didn't have a…

I took Machine Learning with Professor Pe'er in Spring 2017 - I've been tardy about writing a review, but I feel it is necessary. I am genuinely in awe at how bad my experience in this class was, in seemingly every way. To start: Professor Pe'er. It is fortunate that this man is, in fact, a professor - were I to call him "Instructor Pe'er", one may get the false impression that he is capable of instructing anyone. He is not. I have never seen a human so uniquely unsuited for pedagogy as this man. His classroom delivery is a complete trainwreck - when he's not stumbling over his words or saying "ehm" for 15 seconds, the words he does say are incomprehensible, even when explaining material that is clearly within students' grasp. Unfortunately, most of his lectures did not fall into this category, as the prerequisites for this class grossly understate the necessary statistical background. As a CS student with only an intro-level stats background, I rarely had any idea what the hell was going on in lecture. Professor Pe'er's attempt to bridge this gap was laughably insufficient: he spent one day at the beginning of the semester attempting to speed through all of statistics. It didn't play well. Here is how Pe'er explained what a convex surface was: he brought a muffin into class, and passed it around the room. Here is how he explained differences in dimensionality: he printed out…

This review ended up rather long, so TL;DR: this class is hard and confusing- do not take it! Unfortunately, I strongly do not recommend taking this class. It was probably my least favorite class I ever had to take at Columbia (disclaimer: I just took it as a second semester senior so I may be biased, but I still think this is a very honest assessment). I wanted to avoid taking Machine Learning because I was trying to have a chill semester, but I wish I had instead. Professor Pe’er is an extremely nice guy, which makes me hesitant to write a poor review, but I had a very bad experience with this class. The material is hard, but what truly made this class truly difficult is the lack of resources to learn from. Usually, I can rely on the lectures, class notes, or the textbook to learn the material for a class. However, I could not understand the lectures due to Professor Pe’er’s delivery and stuttering, the class notes were confusing and extremely difficult to study from, and there was no textbook. Professor Pe’er has an accent, but it is the stammering and stuttering that made it almost impossible for me to understand what was going on in class. He also spoke through a microphone which further distorted his sentences. I’m not trying to exaggerate, but it took intense concentration and patience during lecture to make sense of each sentence for me (moreso than any lecture I’ve ev…

HORRIBLE lecturer (cannot complete a sentence without stuttering and "ehhhh" every other word). Also, he put his one office hour on Tuesday mornings at 8:30-9:30 am. First of all who is gonna wake up that early... not to mention the comp sci building doesn't even open til 9am. So good luck getting help from him in person, and his responses to email were often curt and unhelpful as well. The TAs were alright... nothing amazing and when they made a program to check our programs A LOT of people had to go for regrades that weren't very liberal at all. Most of the grading was done without taking into account how horribly written and ambiguous the problem sets were. Covers recursion and GUIs... which are definitely NOT supposed to be a part of the intro class curriculum. I didn't bother buying the book for the class and ended up with an A-... But that A- was the result of literally 20+ hours each week on the problem sets. And I guess I got REALLY lucky on the midterms and final... Be happy if you can stay average in the class. The class started out with over a hundred students and ended with only 60ish students. In short... try your best to avoid this class at any cost. And if you must take this teacher, don't be afraid to harass the TAs with questions and give yourself PLENTY of time to finish the problem sets!

6 projects, 3 easy ones before the contexts start midway through the semester, then 3 context-specific projects of which one is "supposed" to be harder than the rest. for the bio section, the 3 last projects are much harder than anything seen in the rest of the class.

I cannot stress enough how awful this teacher truly is. He will teach you absolutely nothing. He does not explain anything thoroughly. He cannot answer any questions. His slides are a total mess. If you can avoid taking this class with this teacher, I highly recommend you do.

Everyone kind of sits on the continuum between weeding out people, and helping them learn. Professor Pe'er is definitely on the latter. Here's why: 1) Only 80% completion of your homework is required, i.e. an 80% translates to 100%. Now, I'll caveat this by saying these assignments are done weekly for the first half, and some of them are pretty tough if you weren't paying careful attention in class. 2) Feedback, feedback, and feedback. Every homework assignment you turn in gets notes meant solely for you. Your final project will have presentations, and you will get feedback from both classmates AND the professor and/or TA, each time. 3) A steady/reliable pace with a very welcoming attitudes towards questions. He leaves his cell phone, personal email, and allows skype sessions over the weekend - just to help you learn or get help with your project. 4) Cameron (the TA) is super nice and adopts the same attitude as Professor Pe'er - he only wants you to learn. In addition to that, this course is heavily front-loaded - it's going to be a sprint the first half. I can't speak for everyone else, but I really appreciated this - it gave me more time to work on my project (the last half of the semester), and deal with the impending deadlines for all my other classes. Now, some caveats: 1) His lecture style is pseudo-interactive, or at least tries to be. He asks a lot of questions to che…

This guy may be a genius in programming, but has no concept of how to teach properly. He can't finish one sentence without stuttering, loves to pick on students during lecture to make them feel embarrassed, and gives poor/dismissive responses to students' questions and concerns. Good luck surviving his useless, boring lectures - you'll be staring at the room's clock almost every second, dreadfully hoping and praying that the class gets dismissed early or ends soon enough (which takes like a millennium). Time dilation effect, anybody? You will definitely come out of lectures more confused about the concepts than before - attending them was almost a complete waste of time and do nothing to help with his crazy problem sets, in which you're not even allowed to discuss/brainstorm any ideas with classmates before submission. This would make sense if the homeworks were doable alone, and didn't incorporate higher level comp sci topics like recursion and GUI that no other computer science teacher covers in an intro course (for non-cs majors!!!). Ultimately, this may possibly be the most horrible experience ever at Columbia with a professor (not friendly and gives terse replies to emails). Avoid him at all costs or prepare to suffer like never before. Very mentally draining and the only salvation is when the course finally ends (but not everybody can make it to the finish line unscathed…

Pros: I thought the assignments were good, but super time consuming and there was one every week, that will squeeze all the time out of you, but in a way you learn. Midterm fair and final was ok. Grading was reasonable. Cons: The worst classroom delivery I have ever seen in my entire life including school anywhere. Machine learning is no doubt fascinating but does require some foundation, but his classroom delivery is some of the worst I have ever seen, stammering, stuttering, is ok for CS 101, in a community college but totally unacceptable for a graduate level course in such a esteemed institution where the pay for professors is high and the fees are exorbitant. On top of his inaudible and cringe inducing voice the material is complex but no doubt interesting. Professor needs to desperately address this and take a look at videos of himself on how to improve for future classes or otherwise just stay a researcher and not lecture. Just look at the how well Andrew Ng did his course in Coursera on Machine Learning. Because of the above it felt a waste of the money we spend on course here. I think Jebara would be much better, understandable and you would feel your moneys worth. But if you can bear and listen to him maybe the course is made for you.

8 problem sets (30%)- need to get 80% for full credit over the semester. They are long, confusing, and difficult! 1 midterm (30%)- open note, answer 3/8 questions. Difficult, but he may offer an extra credit assignment. 1 project (30%)- done with a partner. Don't need to make it too hard, but probably should be somewhat substantial. Class partication (10%)- barely anyone participated, there were a lot of awkward silences.