IEOR E3608

10 Problem Sets (20%) - Most easy and helpful Midterm I (20%) - A little tricky Midterm II (20%) - Very straightforward Final (40%) - Cumulative, but focused more on LP formulation and second part of the semester's algorithms

We had 9 graded HW assignments (syllabus states it can be anywhere from 8 to 10), a midterm, and a final. The HW is only worth 10%, so every pset is about 1% of your grade, while the final is worth 55% which is definitely substantial. Many assignments had both a theory and coding component. The midterm and final are very straightforward and tend to have high averages, though there is definitely a curve at the end of the semester.

9 Homeworks. 3-4 hours each, occasionally 5. All fair. (1 equivalent total) 2 Midterms. (1 equivalent each) Final (2 equivalents) The top 4 equivalents constitute your grade. Curve seems to be a high B+, not 100% sure.

challenging/long homeworks (don't start them the night before), pretty challenging midterm and final. you will do well if you go to class, take notes, and actually do the homeworks.

Mathematical Programming is conceptually easy, but the graders and TA's will take off a lot of points for mistakes. I actually enjoyed going to lectures except when we did proofs that were never seen again for the whole hour, which you can just read and understand on your own. Grades seem to be too subjective in the sense there are several ways to approach a problem so TA's are likely to give back points for regrade. The first average of the midterm was an 80, the second was a 90, and then final was an 80. Obviously the material is not difficult, but you have to work to keep up with the average. Curve was nice: final grade >= 96 ---> A+ 90<=final grade<96 ---->A 84.5<=final grade<90--->A- 80<=final grade<84.5--->B+ 75.5<=final grade<80--->B 69<=final grade<75.5--->B- 65<=final grade<69 ---->C final grade<65 ----->C-

Balkanski is a great lecturer and generally the kind of professor you want if you like a class with a well-defined structure, and exams and homeworks assignments that test exactly what you learn and do not throw curveballs at you. He lectures well, provides annotated slides, and BEST OF ALL records his lectures which is rare for IEOR profs. Honestly, just having a well-structured class is already rare for IEOR profs! This class starts by discussing graph algorithms and other leftover data structures & algorithms topics not covered in IEOR 2000. Then, you move into linear programming, simplex, duality, complementary slackness, (ie. regular intro optimization stuff). Towards the end of the class, you finish off data structures & algorithms by covering dynamic programming and dip your toes into Analysis of Algorithms by discussing Set Cover (ie. NP-hard problems and how you can use graph algos, dynamic programming, and LP for approximation algorithms). Most people taking this class are taking the IEOR junior fall core, and this class is almost certainly the easiest. If you already took COMS 3134 you're pretty much set. You also don't have much of a choice, but I actually enjoyed the class and thought that a lot of it was good review. I also enjoyed that the homework assignments had a lot of real applications.

I honestly don't understand the poor reviews of this professor. Perhaps he was not good at teaching other classes but, as far as the undergraduate version of Math Programming is concerned, he was one of the best teachers I have had. Professor Sethuraman is very good and providing the conceptual/economic explanation for the math that you do in this class, and he goes to great lengths to ensure that you understand this base intuition. This is extremely valuable in a class that would otherwise seem to be a class where one blindly applies algorithms. Jay realizes that computers can do the ugly computations nowadays, and so, rather than spending time on 9x9 matrices, we only do small computation to get an idea for how a specific algorithm works, and then we spend lots of time discussing the underlying methodology of an algorithm, situation in which it might no work, and what certain states of the algorithm can tell us. While Jay is not a ball of energy in the room, he has his own personality that makes class enjoyable, and he does a good job of raising interesting questions about the material that make you think about the nuances or corner cases of the algorithms. Unlike most professors, Jay appears to understand his students. He can tell when his students are confused and is willing to repeat a concept or explain it in a different manner if students don't get it. He also understan…

Okay, Cliff Stein is by far one of the clearest and most concise professors in the IEOR department. The formula for success in this class (and in Integer Programming) is simple: go to class, take notes, do the homework. After reading the other reviews for Stein, I can see that CLEARLY this is too much for a professor to ask of his students. Oh wait, aren't these the BARE minimum class expectations? Yea, that's what I thought. It may be possible that Cliff just works better with a smaller class. For Integer Programming, we even had snack time. In any case, Stein's a great guy. He always responds to emails and is willing to talk to you during office hours. The head TA, Shiqian, is really helpful as well.

11 Problem Sets (10 required, 1 optional), no dropping lowest 2 midterms: 1st was very easy, 2nd covered more material but was still very manageable. Both in first half of class Cumulative final, very manageable.

HW take 2-4 hours average to complete, Exams are easier than HW.