MATH 170A
Probability Theory
Description: Lecture, three hours; discussion, one hour. Requisites: courses 32B, 33A. Not open to students with credit for Electrical Engineering 131A or Statistics 100A. Probability distributions, random variables and vectors, expectation. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Winter 2016 - Professor Heilman is a very organized and engaging instructor. All lecture notes are posted online before the first day of class. All relevant topics are carefully discussed, and practice problems are well designed to help students master the material. Lecture notes and homework problems are very helpful when preparing for exams. In office hours, Professor Heilman is very willing to clarify concepts and answer questions regarding homework problems. Even though the exams are a little challenging, Professor Heilman will provide a very generous curve for the class. I would highly recommend taking any math class with him!
Winter 2016 - Professor Heilman is a very organized and engaging instructor. All lecture notes are posted online before the first day of class. All relevant topics are carefully discussed, and practice problems are well designed to help students master the material. Lecture notes and homework problems are very helpful when preparing for exams. In office hours, Professor Heilman is very willing to clarify concepts and answer questions regarding homework problems. Even though the exams are a little challenging, Professor Heilman will provide a very generous curve for the class. I would highly recommend taking any math class with him!
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Spring 2021 - *Also for 170E* If I can sum up this class and this professor in three words it'll be: easy but tedious As the other reviewer stated, be prepared for hours and hours and hours of homework. In fact, I noticed that the professor simply assigns EVERY SINGLE ODD IN THE BOOK for the homework. Since every single odd is assigned, the hw sets will almost always include some of the stupidly hard proof problems that you have no choice but to look up the solution for. I didn't find lectures to be that helpful for the hw as Professor Needell gives fairly simple examples that do not help at all for the more difficult problems in the book. In addition, every now and then a coding problem is assigned IN ADDITION TO EVERY SINGLE ODD IN THE BOOK, but I didn't find them to be that hard, and they were actually pretty fun to do. The tedious part of the coding is that if you don't know Matlab, you have to figure out how to do the equivalent in the language of your choice. The reason there is so much hw assigned is due to the fact that there are no exams in this class. Instead of exams, you have two projects to do that replace both the midterm and final respectively. This sounds great until you get the project and realize its just a take home exam. The take home exam was long and tedious, with some coding problems. Sometimes I wished that we just had exams instead, as I would much rather take a 24 hour exam (COVID) than an exam that I have to do over a course of a couple weeks. That being said, the projects weren't hard, just tedious. Overall, my review may sound like a lot of complaining, but I'm just saying it how it is. It's easy for me to look back and say "oh the class wasn't that bad" but in reality, I and probably every other person in my class had to spend way more time on this class than is necessary for 170E. So yeah, easy class, most people probably got A's, but it comes at a huge time committment. So you decide if it's worth it or not. TLDR: EASY BUT TEDIOUS
Spring 2021 - *Also for 170E* If I can sum up this class and this professor in three words it'll be: easy but tedious As the other reviewer stated, be prepared for hours and hours and hours of homework. In fact, I noticed that the professor simply assigns EVERY SINGLE ODD IN THE BOOK for the homework. Since every single odd is assigned, the hw sets will almost always include some of the stupidly hard proof problems that you have no choice but to look up the solution for. I didn't find lectures to be that helpful for the hw as Professor Needell gives fairly simple examples that do not help at all for the more difficult problems in the book. In addition, every now and then a coding problem is assigned IN ADDITION TO EVERY SINGLE ODD IN THE BOOK, but I didn't find them to be that hard, and they were actually pretty fun to do. The tedious part of the coding is that if you don't know Matlab, you have to figure out how to do the equivalent in the language of your choice. The reason there is so much hw assigned is due to the fact that there are no exams in this class. Instead of exams, you have two projects to do that replace both the midterm and final respectively. This sounds great until you get the project and realize its just a take home exam. The take home exam was long and tedious, with some coding problems. Sometimes I wished that we just had exams instead, as I would much rather take a 24 hour exam (COVID) than an exam that I have to do over a course of a couple weeks. That being said, the projects weren't hard, just tedious. Overall, my review may sound like a lot of complaining, but I'm just saying it how it is. It's easy for me to look back and say "oh the class wasn't that bad" but in reality, I and probably every other person in my class had to spend way more time on this class than is necessary for 170E. So yeah, easy class, most people probably got A's, but it comes at a huge time committment. So you decide if it's worth it or not. TLDR: EASY BUT TEDIOUS
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Fall 2020 - No exaggeration, this is definitely the hardest Math class I've taken at UCLA - much moreso than 115A, 131A, 164, etc. After the math department reworked Math 170A/B, I was definitely taken aback! That being said, Iseli is a great professor. She's super engaging and cares a lot about student learning. She is really helpful with office hours, runs extra workshops for students, and really responds to student feedback. In general, I think she's an amazing professor and would strongly recommend her as a math prof! But, the workload and tests were really rough. Iseli does try her best to prepare you for the class, but if you don't have as strong of a math background - in competitive math, etc. - I think this class will definitely be tough.
Fall 2020 - No exaggeration, this is definitely the hardest Math class I've taken at UCLA - much moreso than 115A, 131A, 164, etc. After the math department reworked Math 170A/B, I was definitely taken aback! That being said, Iseli is a great professor. She's super engaging and cares a lot about student learning. She is really helpful with office hours, runs extra workshops for students, and really responds to student feedback. In general, I think she's an amazing professor and would strongly recommend her as a math prof! But, the workload and tests were really rough. Iseli does try her best to prepare you for the class, but if you don't have as strong of a math background - in competitive math, etc. - I think this class will definitely be tough.
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Winter 2024 - In terms of lectures, I liked Prof. Killip's teaching. I generally found him quite clear, and his lecturing style does have quite a bit of personality. My impression is that in terms of course content, we hit all the points, and then some; in particular, I appreciated how Prof. Killip would sometimes talk (both briefly, or to some length) about probability topics that may not have been in the course description, but were often relevant/important nonetheless. In terms of formality, I didn't find the class to be especially formal, though we did still do a fair number of proofs & convergence analyses. [A shout-out, also, to our TA James Hogan.] I did admittedly have some trouble following Prof. Killip during the last week of the course, while he was covering multivariate normal distributions; other than that, however, I found everything else understandable. As far as homeworks go, though...woof. To play the devil's advocate, the homework was very helpful in getting a better understanding of course info and practicing the various concepts covered. Even certain ideas/topics that were only briefly mentioned in class, got a fair share of attention and expanding-upon in the homework; some of the homework questions also touched on more application-relevant topics, such as estimation and sampling. That being said, there was a lot of it. A lo-o-ot lot. The homeworks were generally 5-6 questions, very slightly computation-leaning, and took me maybe 6-8? hours on average. That alone doesn't sound too bad...except there were 10 of them, one a week (including midterm week + and week 10), which basically means there is no such thing as a break with this class. To be fair, we did get 2 homework drops; that being said, all questions were graded on correctness, and some of the homework questions were legitimately difficult. To rub extra salt in the wound, all homeworks were posted on Saturdays and due 9 AM the following Friday, which meant we actually had 6 days for each homework...assuming all the requisite knowledge had been covered, otherwise it was more like 4 days. To Prof. Killip's credit, he was generally helpful and did a good job answering questions during office hours. As far as exams go, I personally thought they were okay. They thankfully weren't as difficult as the homeworks, and I found them to be fairly reasonable for the most part, though the timing was a little tight. We did have averages in the mid 70s for both the midterm and the final; that being said, I believe there was also a fairly generous curve. (I made some pretty dumb mistakes on the final, ended with a raw score of ~89%, and got an A.) As a side note, our class only had 15 people in it by week 6, which was kinda strange; I don't recall us ever having too many people, so it wasn't necessarily an attrition thing, but I can't say if the small class size ended up affecting grading somehow.
Winter 2024 - In terms of lectures, I liked Prof. Killip's teaching. I generally found him quite clear, and his lecturing style does have quite a bit of personality. My impression is that in terms of course content, we hit all the points, and then some; in particular, I appreciated how Prof. Killip would sometimes talk (both briefly, or to some length) about probability topics that may not have been in the course description, but were often relevant/important nonetheless. In terms of formality, I didn't find the class to be especially formal, though we did still do a fair number of proofs & convergence analyses. [A shout-out, also, to our TA James Hogan.] I did admittedly have some trouble following Prof. Killip during the last week of the course, while he was covering multivariate normal distributions; other than that, however, I found everything else understandable. As far as homeworks go, though...woof. To play the devil's advocate, the homework was very helpful in getting a better understanding of course info and practicing the various concepts covered. Even certain ideas/topics that were only briefly mentioned in class, got a fair share of attention and expanding-upon in the homework; some of the homework questions also touched on more application-relevant topics, such as estimation and sampling. That being said, there was a lot of it. A lo-o-ot lot. The homeworks were generally 5-6 questions, very slightly computation-leaning, and took me maybe 6-8? hours on average. That alone doesn't sound too bad...except there were 10 of them, one a week (including midterm week + and week 10), which basically means there is no such thing as a break with this class. To be fair, we did get 2 homework drops; that being said, all questions were graded on correctness, and some of the homework questions were legitimately difficult. To rub extra salt in the wound, all homeworks were posted on Saturdays and due 9 AM the following Friday, which meant we actually had 6 days for each homework...assuming all the requisite knowledge had been covered, otherwise it was more like 4 days. To Prof. Killip's credit, he was generally helpful and did a good job answering questions during office hours. As far as exams go, I personally thought they were okay. They thankfully weren't as difficult as the homeworks, and I found them to be fairly reasonable for the most part, though the timing was a little tight. We did have averages in the mid 70s for both the midterm and the final; that being said, I believe there was also a fairly generous curve. (I made some pretty dumb mistakes on the final, ended with a raw score of ~89%, and got an A.) As a side note, our class only had 15 people in it by week 6, which was kinda strange; I don't recall us ever having too many people, so it wasn't necessarily an attrition thing, but I can't say if the small class size ended up affecting grading somehow.
Most Helpful Review
Professor Kim is a very professional instructor. His lecture is very organized and easy to follow. By using enough examples, the concept he taught are easy to be grasped. He replies the emails on time and gives a lot of hint on his homework. Most importantly, he provides practice exam and study guide for midterm and finals which are extremely helpful. As a student in UCLA, I do feel flattered to have a math professor who provides study guide and a whole lecture for review without any students ask for it! Overall, he is a good professor and I would not mind to choose him again if possible.
Professor Kim is a very professional instructor. His lecture is very organized and easy to follow. By using enough examples, the concept he taught are easy to be grasped. He replies the emails on time and gives a lot of hint on his homework. Most importantly, he provides practice exam and study guide for midterm and finals which are extremely helpful. As a student in UCLA, I do feel flattered to have a math professor who provides study guide and a whole lecture for review without any students ask for it! Overall, he is a good professor and I would not mind to choose him again if possible.
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