Rafail Ostrovsky
Department of Computer Science
AD
2.8
Overall Rating
Based on 24 User s
Easiness 2.2 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 2.2 / 5 How clear the professor is, 1 being extremely unclear and 5 being very clear.
Workload 2.5 / 5 How light the workload is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 2.9 / 5 How helpful the professor is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tolerates Tardiness
  • Issues PTEs
  • Needs Textbook
  • Useful Textbooks
  • Often Funny
  • Appropriately Priced Materials
  • Tough Tests

GRADE DISTRIBUTIONS

27.0%
22.5%
18.0%
13.5%
9.0%
4.5%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

28.3%
23.6%
18.9%
14.2%
9.4%
4.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

25.4%
21.1%
16.9%
12.7%
8.5%
4.2%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

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Reviews (15)

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Quarter: Winter 2018
Grade: A
April 8, 2018

I would say CS 180 is definitely one of the most useful and interesting classes I've ever taken at UCLA. HOWEVER, as for the professor himself, I would say he's not helpful at all. I stopped going to lectures after like 2nd or 3rd week bc his lectures suck. And since he strictly followed the textbook I just decided to study the textbook myself instead of wasting time attending lectures(btw the textbook is great as it provides you an overall skeleton of how different algorithmic paradigms work, and gives you abundant examples showing how to apply those different algorithms).
The workload is chill. You only have around 5 hw problems every week. However, some of the problems can be really hard, even impossible to do on ur own. But anyways there are solutions available online and it seems that as long as you write something on each problem you'll get 100...
The midterm was hard with average around 40%. The final on the other hand was much better(at least compared with the midterm).

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Quarter: Spring 2019
Grade: A+
June 5, 2019

Contrary to older reviews, Ostrovsky seems to have gotten better in terms of teaching. After a confusing beginning to class where he spent 2+ weeks talking about NP-completeness (a topic barely covered in other 180 lectures) as well as unclear lectures, he settled down quite a bit after week 4-ish and delivered lectures that are worth going to. This quarter, he decided to write on the blackboard instead of using slides, which has its pros and cons. A big pro is that he would talk slightly slower, but unfortunately he does not have the best handwriting, nor is he the clearest. Reading the textbook is essential in most cases.

Homework is definitely intended to challenge the students, but unfortunately most of them are basically un-doable without the solutions manual. That's not really a trait about his class though, as I hear this is the case with other professors too. (The textbook just has hard problems in general.) I'd still recommend doing them as much as possible on your own – and start early, as nothing beats the feeling of coming up with a solution yourself after thinking about it through over multiple days.

Exams are exponentially easier than the homework. Even so, this year the average for the midterm was in the 60s, though have actually gotten gradually easier over the past years. Most past midterms with Ostrovsky had averages in the 40s.

In general, not as horrible as other reviews make it out, but if you have the option of waiting one more quarter to get Sarrafzadeh, wait.

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Quarter: Spring 2019
Grade: A
June 27, 2019

Ostrovsky’s lectures are often hit or miss. He is good at explaining some topics and awful at some others (such as NP-Completeness).

Make sure you read the formal proofs in the textbook and go over as many different problems as possible. This increases your chances of seeing a similar problem on the midterm/final (which was hard).

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Quarter: Spring 2019
Grade: A
June 24, 2019

If you care about getting a good grade in CS 180, I'd say Ostrovsky is the best professor to take the class with. He gives the most amount of A's out of all the other professors. However, he is not a good lecturer. Personally, I don't care if a professor is good at teaching or not because there are plenty of online resources (Geeks for Geeks) and YouTube videos (Tushar Roy, Back to Back SWE, etc.) that explain the material much better than most professors can. I did close to 200 leetcode problems the summer before, so I had good algorithm knowledge before coming in, but it is not necessary to do well in the class as long as you study hard.

Don't even bother going to class. Just go the first week when he talks about the class, the class before the midterm, and the last week when he talks about the final. What I did most of the time was skip class and then ask my friend what was covered and then self study the material. It was often more efficient to learn on my own since Ostrovsky does not explain things well. Here's some of the material I used to do well in the class. Discussion were a hit or a miss. This quarter, all of the TAs were not good. Discussion is a hit or a miss, but usually a miss. Maybe in another quarter the TAs will be good.

Homework assignments are often free 100%. Don't even bother spending much time on these. Attempt the problems as best as you can, and if you can't get it, just copy the solution manual or some old homework on GitHub. I only got marked off on two assignments, but still got a 95/100 on those. One of the mistakes was not writing the runtime, so always write the runtime if it asks you to write a polynomial time solutions or something. Other than that, as long as you write something that sort of makes sense, you are good. The homework questions are often way harder than the exam questions, so it is not worth it to study the homework that hard. Even the TAs don't know how to do most of the homework questions. I often went to office hours to understand some of the homework problems and even they couldn't do them.

As far as his exams, I suggest doing most extra problems in the beginning of each chapter. As you go to the later numbered problems, they get much harder. Often, very convoluted and long questions won't show up on the exam. I found that Geeks for Geeks was the best way to prepare for the exams. A good amount of problems were pulled straight from Geeks for Geeks word for word. For the midterm, from what I heard, the TAs each picked one question to put on the midterm, and then Ostrovsky put one. The midterm was 6 questions. The final was 10 questions. I also found doing some extra problems in the CLRS textbook helpful. This CLRS textbook was more readable than the textbook we used in this class. The textbook we use in class is not that good in my opinion. I would just skim that book and then get a general idea on how to write proofs for each type of problem. The hardest part of the class was not really writing a proof for the questions on the exams. It was coming up with a solution. As long as you wrote some sort of proof that followed the format, it was usually good enough.

Ostrovsky gives PTEs to everyone, so you shouldn't worry about getting into his class, so don't even bother first passing this class. Everyone gets in, but people end up dropping anyways, so it doesn't really matter.

Here are some good resources to help you get through the class:
http://www.cs.princeton.edu/~wayne/cs423/

https://web.stanford.edu/class/archive/cs/cs161/cs161.1138/

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/lecture-videos/

https://www.youtube.com/user/purpongie/playlists

https://www.youtube.com/user/mikeysambol/videos

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Quarter: Spring 2019
Grade: A
June 23, 2019

Alright, Ostrovsky's lectures are getting better than what the reviews said, but I'd still read the textbook instead. The textbook explains everything in detail, and is pretty straight-forward except for the chapter with NP-Completeness.

Contrary to what other reviews say, I'd say the tip to doing well in this class is reading the textbook until you understand the material. (And proofs - you need to explain why your method is the most efficient). Solving more problems isn't necessarily the answer. I came in with no previous knowledge, just tried my best at understanding the material though the four HWs, and got an A. Please just don't copy the answers from online for the homework (you won't be prepared for the exam if you do!)

I personally feel like that the students who will do the best in this class would be Math majors who have experience with proofs. TAs are CS TAs so they don't fully expect full-math proofs. Just try to get your answer look like a Math-proof.

There are only 4 HW problems assigned per week but, it's gonna take quite some time. Many people suggest you to start early, but Ostrovsky often didn't cover the material until the day before the due date (at 8AM). I always ended up doing CS 180 homework at 2AM, though the TAs are pretty generous with grading the HW.

But to be honest, if you have a tight courseload, save yourself time by just reading the textbook and skipping the lecture. The only merit of going to his lecture is that Ostrovsky often hints what exam question will be on the exam (and might not be a freebie if you don't show up to class... Master's Theorem and Directed Acyclic Graphs for this year). I personally only showed up for lectures during Week 1 and Week 10, occasionally checking what the class is going over. Just ask a friend who's attending the lecture.

If you have a light courseload, I'd recommend you to read the textbook first, and just listen to Ostrovsky's lecture.

CS 180 really isn't a class where you can take good notes. It's more about understanding a concept and applying it. Proofs are the tools that help you understand why an algorithm works such way or why it's the most efficient.

And for Exams... It's really you see it or you don't.
You want to do some priming so you have a better chance of solving his problems. The exam questions however, aren't as difficult as the homework problems, and can be solved in given amount of time. (but your hand will hurt from writing a lot).

Read the example from textbooks as it helps you to understand the concept. Don't get too focused on proof of one example, since Ostrovsky's exams aren't about memorization. Try to learn how the process works. (Network-flow, Divide and Conquer, Dynamic programming)

He's a very kind professor though. Doesn't want many students stressed about his grades so his curve is always more lenient. I'd actually recommend taking CS180 with Ostrovsky if you are inclined to self-learn.

TL DR; Read the textbook (until you understand them). Kind professor with generous curve, but not the best lectures. Learn the concepts rather than memorizing examples.

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Quarter: Spring 2019
Grade: A+
June 23, 2019

This professor is really passionate about the subject which is great and wholesome but he isn't the best. I learned way more from discussion than from lecture. The homework is pretty hard but there are solutions online and if you do it you pretty much get full credit. The midterm was medium difficulty but I did super bad on it because I didn't read the book. Once I started reading the book everything changed and I started really understanding the material. He offered to drop the midterm and make the final worth more if it helps you and as a result my bad midterm grade was effectively erased and I got an A+! I cannot stress this enough, but the key to doing good in this class is reading the book and doing practice problems. Do problems on Geeks for Geeks, that website saved me. I cannot stress how much doing those practice problems prepared me for the final.

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Quarter: Spring 2019
Grade: A
June 22, 2019

I think Ostrovsky is definitely getting better at teaching! This quarter he started writing out his lectures on the board instead of reading off of his slides (which is what I'm guessing he used to do based on previous reviews). This slowed down his pace a lot and made his lectures more interactive.
However, compared to other professors, he is still not the best lecturer. His handwriting on the board is almost illegible and a lot of the times he goes on tangents that are somewhat irrelevant to the class. He's really good at explaining things but it's really hard to survive this class without reading the book because the notes that he writes on the board aren't really "notes"...they're more like pictures/diagrams to help explain what he is saying. He rarely provides concrete definitions for mathematical terms/algorithms, and given the fact that this course is a very theory-intensive course, it's difficult to solely rely on his lectures to study.
For me, I just stopped taking notes after the 1st or 2nd week and tried my best to listen to what he was saying in class. I just read the chapters beforehand and his lectures made a lot more sense. Just read the book and you'll do fine.

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Quarter: Spring 2019
Grade: NR
June 12, 2019

My experience with this class was a little unconventional, as I was taking a very heavy courseload and had less time to dedicate to it early on in the quarter. Still, I found that this class wasn't that bad, and you could skip classes and just read the textbook without missing a beat.

Homeworks are annoyingly difficult at times, but doable if you form a study group. However, homeworks only compose 15% of the grade, with 40% being the midterm and 45% being the final, so your final grade will be determined pretty much from those two.

My main issue with this course was the hike in difficulty between the midterm and the final. The midterm was generally easy, with an average score of 60% and std. dev. of about 10%. The final, however, was unbelievably harder in comparison. I studied for two days straight before the final, and a minimum of 3 hours a day starting 10 days before the final, and I had no idea how to approach a majority of the problems. I assume there will be a much lower average and std. dev. on this final, and given the midterm reflected the material better I'd say it's better to study for the midterm more than the final honestly.

Anyways, the course isn't that bad, and Ostrovsky may be the most competent professor to teach the class of all professors who do. However, from my experience, I urge those taking it to treat the midterm like a final, as it could prove extremely difficult to set yourself apart from the rest of the class on the actual final, even if you study a ton.

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Quarter: Spring 2019
Grade: A
June 5, 2019

Professor Ostrovsky is a great teacher! Though he can ramble off sometimes, I found that his passion for the subject really showed and it made me want to learn as well. Algorithms is a very interesting but difficult subject. He made it simple and easy to learn. And because he bases most of his lectures off of the textbook, you know exactly what to study. The midterm was really easy, requiring you to just think a little bit to apply the concepts you learned in class. All of the questions on the midterm/final were easier than the homework problems he assigned(about 4 a week). In general, great class as opposed to what other reviews on this site may say.

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Quarter: Winter 2018
Grade: B-
March 30, 2018

I learned nothing from his lectures. I have to self study by reading the textbook which thankfully is a saving grace at least for the midterm, but I just feel why would I take this class instead of just reading the textbook? His lecture slides have some errors, which for those who solely study the slides will not do so well unless they are smart enough or work hard enough to realize the mistakes.

Discussion sections do not really help at all. Most of the information I know is because I prepared leetcode problems over the summer, and because I am a junior, already am familiar with all types of problems. The grading for the exams seems to be arbitrary at best, where I either get full points or a big fat zero with obscure explanations as to why I lost those points. Asking for a regrade only yielded yet another obscure description without bumping my already abysmal exam scores.

The class itself depends way too heavily on the exams, which means if you are like me who perform somehow super badly on the exams, it is game over. By the way, I am in no way dumb, I am interning in the Big 4 this summer and know how to solve all these problems in the midterm and final, not to sound pretentious. I just lose almost all the points on the exam just because of obscure reasons even my friends do not know why, and I am just not a bright student academically.

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Quarter: Winter 2018
Grade: A
April 8, 2018

I would say CS 180 is definitely one of the most useful and interesting classes I've ever taken at UCLA. HOWEVER, as for the professor himself, I would say he's not helpful at all. I stopped going to lectures after like 2nd or 3rd week bc his lectures suck. And since he strictly followed the textbook I just decided to study the textbook myself instead of wasting time attending lectures(btw the textbook is great as it provides you an overall skeleton of how different algorithmic paradigms work, and gives you abundant examples showing how to apply those different algorithms).
The workload is chill. You only have around 5 hw problems every week. However, some of the problems can be really hard, even impossible to do on ur own. But anyways there are solutions available online and it seems that as long as you write something on each problem you'll get 100...
The midterm was hard with average around 40%. The final on the other hand was much better(at least compared with the midterm).

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Quarter: Spring 2019
Grade: A+
June 5, 2019

Contrary to older reviews, Ostrovsky seems to have gotten better in terms of teaching. After a confusing beginning to class where he spent 2+ weeks talking about NP-completeness (a topic barely covered in other 180 lectures) as well as unclear lectures, he settled down quite a bit after week 4-ish and delivered lectures that are worth going to. This quarter, he decided to write on the blackboard instead of using slides, which has its pros and cons. A big pro is that he would talk slightly slower, but unfortunately he does not have the best handwriting, nor is he the clearest. Reading the textbook is essential in most cases.

Homework is definitely intended to challenge the students, but unfortunately most of them are basically un-doable without the solutions manual. That's not really a trait about his class though, as I hear this is the case with other professors too. (The textbook just has hard problems in general.) I'd still recommend doing them as much as possible on your own – and start early, as nothing beats the feeling of coming up with a solution yourself after thinking about it through over multiple days.

Exams are exponentially easier than the homework. Even so, this year the average for the midterm was in the 60s, though have actually gotten gradually easier over the past years. Most past midterms with Ostrovsky had averages in the 40s.

In general, not as horrible as other reviews make it out, but if you have the option of waiting one more quarter to get Sarrafzadeh, wait.

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Quarter: Spring 2019
Grade: A
June 27, 2019

Ostrovsky’s lectures are often hit or miss. He is good at explaining some topics and awful at some others (such as NP-Completeness).

Make sure you read the formal proofs in the textbook and go over as many different problems as possible. This increases your chances of seeing a similar problem on the midterm/final (which was hard).

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Quarter: Spring 2019
Grade: A
June 24, 2019

If you care about getting a good grade in CS 180, I'd say Ostrovsky is the best professor to take the class with. He gives the most amount of A's out of all the other professors. However, he is not a good lecturer. Personally, I don't care if a professor is good at teaching or not because there are plenty of online resources (Geeks for Geeks) and YouTube videos (Tushar Roy, Back to Back SWE, etc.) that explain the material much better than most professors can. I did close to 200 leetcode problems the summer before, so I had good algorithm knowledge before coming in, but it is not necessary to do well in the class as long as you study hard.

Don't even bother going to class. Just go the first week when he talks about the class, the class before the midterm, and the last week when he talks about the final. What I did most of the time was skip class and then ask my friend what was covered and then self study the material. It was often more efficient to learn on my own since Ostrovsky does not explain things well. Here's some of the material I used to do well in the class. Discussion were a hit or a miss. This quarter, all of the TAs were not good. Discussion is a hit or a miss, but usually a miss. Maybe in another quarter the TAs will be good.

Homework assignments are often free 100%. Don't even bother spending much time on these. Attempt the problems as best as you can, and if you can't get it, just copy the solution manual or some old homework on GitHub. I only got marked off on two assignments, but still got a 95/100 on those. One of the mistakes was not writing the runtime, so always write the runtime if it asks you to write a polynomial time solutions or something. Other than that, as long as you write something that sort of makes sense, you are good. The homework questions are often way harder than the exam questions, so it is not worth it to study the homework that hard. Even the TAs don't know how to do most of the homework questions. I often went to office hours to understand some of the homework problems and even they couldn't do them.

As far as his exams, I suggest doing most extra problems in the beginning of each chapter. As you go to the later numbered problems, they get much harder. Often, very convoluted and long questions won't show up on the exam. I found that Geeks for Geeks was the best way to prepare for the exams. A good amount of problems were pulled straight from Geeks for Geeks word for word. For the midterm, from what I heard, the TAs each picked one question to put on the midterm, and then Ostrovsky put one. The midterm was 6 questions. The final was 10 questions. I also found doing some extra problems in the CLRS textbook helpful. This CLRS textbook was more readable than the textbook we used in this class. The textbook we use in class is not that good in my opinion. I would just skim that book and then get a general idea on how to write proofs for each type of problem. The hardest part of the class was not really writing a proof for the questions on the exams. It was coming up with a solution. As long as you wrote some sort of proof that followed the format, it was usually good enough.

Ostrovsky gives PTEs to everyone, so you shouldn't worry about getting into his class, so don't even bother first passing this class. Everyone gets in, but people end up dropping anyways, so it doesn't really matter.

Here are some good resources to help you get through the class:
http://www.cs.princeton.edu/~wayne/cs423/

https://web.stanford.edu/class/archive/cs/cs161/cs161.1138/

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/lecture-videos/

https://www.youtube.com/user/purpongie/playlists

https://www.youtube.com/user/mikeysambol/videos

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Quarter: Spring 2019
Grade: A
June 23, 2019

Alright, Ostrovsky's lectures are getting better than what the reviews said, but I'd still read the textbook instead. The textbook explains everything in detail, and is pretty straight-forward except for the chapter with NP-Completeness.

Contrary to what other reviews say, I'd say the tip to doing well in this class is reading the textbook until you understand the material. (And proofs - you need to explain why your method is the most efficient). Solving more problems isn't necessarily the answer. I came in with no previous knowledge, just tried my best at understanding the material though the four HWs, and got an A. Please just don't copy the answers from online for the homework (you won't be prepared for the exam if you do!)

I personally feel like that the students who will do the best in this class would be Math majors who have experience with proofs. TAs are CS TAs so they don't fully expect full-math proofs. Just try to get your answer look like a Math-proof.

There are only 4 HW problems assigned per week but, it's gonna take quite some time. Many people suggest you to start early, but Ostrovsky often didn't cover the material until the day before the due date (at 8AM). I always ended up doing CS 180 homework at 2AM, though the TAs are pretty generous with grading the HW.

But to be honest, if you have a tight courseload, save yourself time by just reading the textbook and skipping the lecture. The only merit of going to his lecture is that Ostrovsky often hints what exam question will be on the exam (and might not be a freebie if you don't show up to class... Master's Theorem and Directed Acyclic Graphs for this year). I personally only showed up for lectures during Week 1 and Week 10, occasionally checking what the class is going over. Just ask a friend who's attending the lecture.

If you have a light courseload, I'd recommend you to read the textbook first, and just listen to Ostrovsky's lecture.

CS 180 really isn't a class where you can take good notes. It's more about understanding a concept and applying it. Proofs are the tools that help you understand why an algorithm works such way or why it's the most efficient.

And for Exams... It's really you see it or you don't.
You want to do some priming so you have a better chance of solving his problems. The exam questions however, aren't as difficult as the homework problems, and can be solved in given amount of time. (but your hand will hurt from writing a lot).

Read the example from textbooks as it helps you to understand the concept. Don't get too focused on proof of one example, since Ostrovsky's exams aren't about memorization. Try to learn how the process works. (Network-flow, Divide and Conquer, Dynamic programming)

He's a very kind professor though. Doesn't want many students stressed about his grades so his curve is always more lenient. I'd actually recommend taking CS180 with Ostrovsky if you are inclined to self-learn.

TL DR; Read the textbook (until you understand them). Kind professor with generous curve, but not the best lectures. Learn the concepts rather than memorizing examples.

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Quarter: Spring 2019
Grade: A+
June 23, 2019

This professor is really passionate about the subject which is great and wholesome but he isn't the best. I learned way more from discussion than from lecture. The homework is pretty hard but there are solutions online and if you do it you pretty much get full credit. The midterm was medium difficulty but I did super bad on it because I didn't read the book. Once I started reading the book everything changed and I started really understanding the material. He offered to drop the midterm and make the final worth more if it helps you and as a result my bad midterm grade was effectively erased and I got an A+! I cannot stress this enough, but the key to doing good in this class is reading the book and doing practice problems. Do problems on Geeks for Geeks, that website saved me. I cannot stress how much doing those practice problems prepared me for the final.

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Quarter: Spring 2019
Grade: A
June 22, 2019

I think Ostrovsky is definitely getting better at teaching! This quarter he started writing out his lectures on the board instead of reading off of his slides (which is what I'm guessing he used to do based on previous reviews). This slowed down his pace a lot and made his lectures more interactive.
However, compared to other professors, he is still not the best lecturer. His handwriting on the board is almost illegible and a lot of the times he goes on tangents that are somewhat irrelevant to the class. He's really good at explaining things but it's really hard to survive this class without reading the book because the notes that he writes on the board aren't really "notes"...they're more like pictures/diagrams to help explain what he is saying. He rarely provides concrete definitions for mathematical terms/algorithms, and given the fact that this course is a very theory-intensive course, it's difficult to solely rely on his lectures to study.
For me, I just stopped taking notes after the 1st or 2nd week and tried my best to listen to what he was saying in class. I just read the chapters beforehand and his lectures made a lot more sense. Just read the book and you'll do fine.

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Quarter: Spring 2019
Grade: NR
June 12, 2019

My experience with this class was a little unconventional, as I was taking a very heavy courseload and had less time to dedicate to it early on in the quarter. Still, I found that this class wasn't that bad, and you could skip classes and just read the textbook without missing a beat.

Homeworks are annoyingly difficult at times, but doable if you form a study group. However, homeworks only compose 15% of the grade, with 40% being the midterm and 45% being the final, so your final grade will be determined pretty much from those two.

My main issue with this course was the hike in difficulty between the midterm and the final. The midterm was generally easy, with an average score of 60% and std. dev. of about 10%. The final, however, was unbelievably harder in comparison. I studied for two days straight before the final, and a minimum of 3 hours a day starting 10 days before the final, and I had no idea how to approach a majority of the problems. I assume there will be a much lower average and std. dev. on this final, and given the midterm reflected the material better I'd say it's better to study for the midterm more than the final honestly.

Anyways, the course isn't that bad, and Ostrovsky may be the most competent professor to teach the class of all professors who do. However, from my experience, I urge those taking it to treat the midterm like a final, as it could prove extremely difficult to set yourself apart from the rest of the class on the actual final, even if you study a ton.

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Quarter: Spring 2019
Grade: A
June 5, 2019

Professor Ostrovsky is a great teacher! Though he can ramble off sometimes, I found that his passion for the subject really showed and it made me want to learn as well. Algorithms is a very interesting but difficult subject. He made it simple and easy to learn. And because he bases most of his lectures off of the textbook, you know exactly what to study. The midterm was really easy, requiring you to just think a little bit to apply the concepts you learned in class. All of the questions on the midterm/final were easier than the homework problems he assigned(about 4 a week). In general, great class as opposed to what other reviews on this site may say.

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Quarter: Winter 2018
Grade: B-
March 30, 2018

I learned nothing from his lectures. I have to self study by reading the textbook which thankfully is a saving grace at least for the midterm, but I just feel why would I take this class instead of just reading the textbook? His lecture slides have some errors, which for those who solely study the slides will not do so well unless they are smart enough or work hard enough to realize the mistakes.

Discussion sections do not really help at all. Most of the information I know is because I prepared leetcode problems over the summer, and because I am a junior, already am familiar with all types of problems. The grading for the exams seems to be arbitrary at best, where I either get full points or a big fat zero with obscure explanations as to why I lost those points. Asking for a regrade only yielded yet another obscure description without bumping my already abysmal exam scores.

The class itself depends way too heavily on the exams, which means if you are like me who perform somehow super badly on the exams, it is game over. By the way, I am in no way dumb, I am interning in the Big 4 this summer and know how to solve all these problems in the midterm and final, not to sound pretentious. I just lose almost all the points on the exam just because of obscure reasons even my friends do not know why, and I am just not a bright student academically.

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2.8
Overall Rating
Based on 24 Users
Easiness 2.2 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 2.2 / 5 How clear the professor is, 1 being extremely unclear and 5 being very clear.
Workload 2.5 / 5 How light the workload is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 2.9 / 5 How helpful the professor is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tolerates Tardiness
    (10)
  • Issues PTEs
    (5)
  • Needs Textbook
    (8)
  • Useful Textbooks
    (8)
  • Often Funny
    (9)
  • Appropriately Priced Materials
    (5)
  • Tough Tests
    (7)
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