Professor
Raghu Meka
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Most Helpful Review
Meka is organized and nice, but he assumed we knew a lot more coming into the class than we actually did. He would present topics without a lot of lead-up, so you'd be suddenly looking at things like advanced probability without having taken any statistics classes (and even the people who had taken those classes said that they'd never seen before the material Meka was presenting). Classes are all about new material, but there wasn't a very cohesive chain of applicability for all the different topics, so it made it hard to absorb the info; it just seemed like a big bag of difficult, seemingly disjointed material. Meka's a nice guy, but he tended to not tell you how to do things for fear of "giving away the answer". Consequently, any methods you developed to solve any questions was of your own doing. If Sean is still TAing, he's a big help. Overall, I feel like the class was unnecessarily hard and you didn't leave feeling like you had new tools in your coding arsenal; you just left feeling glad that it was all over. If you are in this class, here are some things that can help: He sticks fairly close to the book, so if you can read the chapters before lecture, you’ll be ready to hear his advanced versions of the material. The homeworks were ridiculously hard, but once you have the answers (TA help…), really understand how you got there, because his exam questions are often just versions of those HW questions (and/or versions of some proof he did in class). He really expected us to reference algorithms/proofs he did in lecture. If you can remember all those, you only need to add “blah blah algorithm/proof, as shown in lecture” much of the time for full points. In fact, NOT referencing one of those can often wipe points off your HW/exam even though you did everything else right. Overall, the HW grading was up and down (high average for the class on one assignment, then an inexplicably, drastically low average on the next) and we often weren’t sure what constituted a “correct answer” because the instructions were vague, yet the grading was very specific, like a N Campus class looking for you to mention key words to match the grading rubric. Like I said, perhaps his teaching methods will change and he did grade fairly with the final grades, but I would recommend someone else if you want to really “get” algorithms.
Meka is organized and nice, but he assumed we knew a lot more coming into the class than we actually did. He would present topics without a lot of lead-up, so you'd be suddenly looking at things like advanced probability without having taken any statistics classes (and even the people who had taken those classes said that they'd never seen before the material Meka was presenting). Classes are all about new material, but there wasn't a very cohesive chain of applicability for all the different topics, so it made it hard to absorb the info; it just seemed like a big bag of difficult, seemingly disjointed material. Meka's a nice guy, but he tended to not tell you how to do things for fear of "giving away the answer". Consequently, any methods you developed to solve any questions was of your own doing. If Sean is still TAing, he's a big help. Overall, I feel like the class was unnecessarily hard and you didn't leave feeling like you had new tools in your coding arsenal; you just left feeling glad that it was all over. If you are in this class, here are some things that can help: He sticks fairly close to the book, so if you can read the chapters before lecture, you’ll be ready to hear his advanced versions of the material. The homeworks were ridiculously hard, but once you have the answers (TA help…), really understand how you got there, because his exam questions are often just versions of those HW questions (and/or versions of some proof he did in class). He really expected us to reference algorithms/proofs he did in lecture. If you can remember all those, you only need to add “blah blah algorithm/proof, as shown in lecture” much of the time for full points. In fact, NOT referencing one of those can often wipe points off your HW/exam even though you did everything else right. Overall, the HW grading was up and down (high average for the class on one assignment, then an inexplicably, drastically low average on the next) and we often weren’t sure what constituted a “correct answer” because the instructions were vague, yet the grading was very specific, like a N Campus class looking for you to mention key words to match the grading rubric. Like I said, perhaps his teaching methods will change and he did grade fairly with the final grades, but I would recommend someone else if you want to really “get” algorithms.
Most Helpful Review
Fall 2022 - meka is amazing. his lectures are super insightful and genuinely thought provoking. i came in expecting to hate 181 but it ended up being one my favorite ucla cs classes. his exams aren't necessarily easy but i felt that they were fair. biggest tips for success in the class: 1. do all of the practice exams since your exams will have a similar structure 2. do the practice problems on the hw to the best of your ability. even if you can't do them completely on your own, make sure you understand the solutions. a similar problem usually comes up on the exam!
Fall 2022 - meka is amazing. his lectures are super insightful and genuinely thought provoking. i came in expecting to hate 181 but it ended up being one my favorite ucla cs classes. his exams aren't necessarily easy but i felt that they were fair. biggest tips for success in the class: 1. do all of the practice exams since your exams will have a similar structure 2. do the practice problems on the hw to the best of your ability. even if you can't do them completely on your own, make sure you understand the solutions. a similar problem usually comes up on the exam!
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