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Divide and Conquer, Sorting and Searching, and Randomized Algorithms(으)로 돌아가기

스탠퍼드 대학교의 Divide and Conquer, Sorting and Searching, and Randomized Algorithms 학습자 리뷰 및 피드백

4.8
별점
4,260개의 평가
802개의 리뷰

강좌 소개

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts)....

최상위 리뷰

KS
2018년 9월 13일

Well researched. Topics covered well, with walkthrough for exam.le cases for each new introduced algorithm. Great experience, learned a lot of important algorithms and algorithmic thinking practices.

DT
2020년 5월 26일

Thank you for teaching me this course. I learned a lot of new things, including Divide-and-Conquer, MergeSort, QuickSort, and Randomization Algorithms, along with proof for their asymptotic runtime

필터링 기준:

Divide and Conquer, Sorting and Searching, and Randomized Algorithms의 782개 리뷰 중 26~50

교육 기관: Nikolaos E

2016년 11월 7일

Personally, I would recommend this course to anyone who really wants to learn how things work in that sort of algorithms. I found the assignments a little difficult, but also extremely helpful.

교육 기관: Ferdinando I

2020년 4월 24일

I think the course is really good. Enough mathematics to make things more rigorous, but not too much that it is hard to follow (for a MOOC). The questions make you think about the material.

교육 기관: Akshath M

2020년 4월 23일

Made notes, watched optional videos, re-watched the content till I understood and aced the tests! :)

It's fairly challenging but also do-able if you put your mind to it

교육 기관: QJJ

2020년 4월 25일

Should really work hard to pass... But anyway, I appreciate the changes that the teacher brings to me. Really really a nice lesson the join!

교육 기관: Deeksha S

2020년 4월 28일

Little bit tough but if you learn this honestly then you will gain much knowledge.

교육 기관: Shikhir G

2020년 4월 22일

Brilliant course with proper explanations. Totally worth your time.

교육 기관: Sankalp D

2020년 5월 1일

very truthful and everything thoroughly explained

교육 기관: Jakub K

2020년 4월 29일

Very hard. Unique knowledge and skills.

교육 기관: Vaibhav K

2020년 4월 25일

bets for analyzing the algorithm

교육 기관: Parsa N

2020년 4월 29일

Interesting course and huge amount of knowledge

교육 기관: Anguzu V J

2020년 4월 30일

i loved it so much

교육 기관: Farrukh M

2019년 1월 1일

Very basic. Only good for people without CS degree.

교육 기관: Ivan Y J

2020년 7월 26일

As an auditing student it is extremely difficult to access course content ahead of time. I have finished my week 1 contents but cannot go forward to week 2.

교육 기관: abusaleh i

2019년 3월 14일

Just mere waste of time and money. Only suitable for Stanford student

교육 기관: Nadim H

2017년 9월 11일

Challenging and highly informative course. Professor Roughgarden has a concise and candid lecturing style that I found easy and pleasant to follow.

Make sure you're comfortable with one programming language, and have some experience in writing programs. There is a lot of math, and while not super advanced, make sure you've brushed up on: logarithmic identities, infinite sums, and counting (permutations and combinations). The course dives into some probability, but Professor Roughgarden will walk you through some optional (and very instructive) review lectures.

I'm looking to finishing the specialization, but I'll take some time off to review my discrete mathematics, and strengthen my programming first. This is my first MOOCS course, and I'm hoping all my future experiences will be as great. I highly recommend the course and Professor Roughgarden's lectures.

교육 기관: zeinab s

2019년 5월 2일

I audited this course and I believe this course is going to help me build my future career. I'm in transition between my original degree (engineering) to computer science, and I want to build a great foundation of my knowledge. For me, with little computer knowledge, this course was great. The syllabus is complete and covers essential material. The instructor explains everything clearly. although he talks a bit fast for me (I'm not native but I'm studying in an english language school).

It is a good combination of the algorithms and the math behind them. not too much math. The homework at the end of each week is also helpful to practice what you learned in videos. (Although I couldn't see the answers)

in Overall, it's a great course, and I recommend it to anyone with a passion for computer science.

교육 기관: Steve J

2018년 9월 20일

I found this course to be an ideal mix of abstract theory and practical application. Professor Roughgarden is quite adept at presenting in depth analyses of algorithms in a way that does not shy away from formal mathematics but also does not require a degree in mathematics to understand. For me, whose prior math coursework was mainly focused on areas of math not as prevalent in computer science as other in disciplines (e.g. calculus vs. discrete math), Professor Roughgarden's approach is ideal and opened up the door to a much deeper understanding of algorithms than I've acquired on my own over a multi-decade career in programming.

Highly recommend this course for anyone who, like me, has a lot of experience with programming, but no formal training on algorithms.

교육 기관: Cliff C

2017년 11월 25일

Loved the clarity and enthusiasm. The proofs and algorithm implementations shared in this class are often simpler and more elegant than the proofs and implementations I've found in other textbooks.

Just a few examples: 1. The proof of Quicksort's expected comparisons count was great. The course used a beautiful, simple proof summing the values of indicator variables whereas other proofs I've seen use a messy inductive approach. 2. The implementation of partition was much simpler than most other partition implementations I've seen, which tend to walk from the left and right swapping items.

The simplicity of the proofs and algorithm implementations make the material more beautiful. Thank you!

교육 기관: Kalema A B

2020년 7월 11일

This was my first time diving into algorithms, it was indeed challenging as my math skills had been long kept in the dark since my Computer Eng. Diploma, it sent me doing research that in turn expanded my understanding of the concepts, I almost felt frustrated especially with the analysis videos, probability concepts were a challenge and I intend to take a detailed math refresher course as I continue with the remaining courses, hopefully after this I will keep my math alive for life. Thanks for the challenge in this course, it kept me pacing and it was indeed worth it, i hope to research other algorithm in sorting and other concepts discussed here, Thanks.

교육 기관: Alexander L

2019년 11월 11일

Very interesting. I learned a lot of new things. 5 stars!

Just a few things that could be improved:

-- The video and its audio are not really synchronized (maybe because the video is pretty old)

-- The Quicksort programming assignment was like: 1 hour to program a working Quicksort + 4 hours figuring out how the course creator wants me to count the compares of it as that's dependent from the implementation.

Nowadays there are better solutions to validate whether someone solved a programming task. geeksforgeeks.org and hackerrank.com for example just execute the program with test input.

But all in all: Very positive experience.

교육 기관: Angel M P

2020년 9월 4일

The Course is very challenging and also very rewarding! The professor motivate you showing real applications about the algorithms he talk about. This course review the math analysis of the algorithms and also require that you implement some of these algorithms. The course required me dedicate many hours during week (some weeks more than 15 hours) but each programming assignment done is very rewarding and I could learn better some of these topics which I took last semester at my university. Thanks professor Tim Roughgarden!! and thanks to all the team behind this course!

교육 기관: francisco i

2016년 12월 24일

Excellent course. What I valued most about this course was the clarity with which proofs and algorithms are explained. In learning algorithms one really profits from a great professor. Keep in mind that this course involves mathematics for proofs and I believe one has to be really curious about algorithms and dive into proofs to take full advantage of this course. Regarding assignments they are challenging but definitely approachable if you have some experience in programming. My advice: do not get discouraged, this is all about resilience!

교육 기관: Frank J M

2019년 2월 25일

lectures were great. Pace was just right. It is great being able to repeat parts of the lecture to improve your understanding. I only wish the Part 1: Basics books covered the week on graphs and the contraction algorithm. The Algorithms Illustrated book was a great companion for the course. Not having a book companion made the graphs and contraction algorithm material a little more difficult.

I like the the lectures are not copies of the book. The flow of topics match, but the explanations in lecture are often different.

교육 기관: Benoit P

2016년 12월 29일

This is a great course. The teacher is very clear, and the material is very interesting. The programming assignments are interesting: the problems asked are very simple, but the input is generally too large to use brute force: you really have to implement the algorithms presented in the videos. This makes you realize how much smart algorithms can make a difference.

The level of the class is relatively high, compared to other Coursera courses I've taken. If you want some serious training on algorithms, look no further.

교육 기관: Jason H

2018년 7월 29일

This is the place to start upgrading your programming skills to the next level. If you have some prior programming experience solving problems with data, but have never rigorously looked at the efficiency of your algorithm and wondered "Can this be better?" this course is designed for you. You'll learn to think and talk like a software engineer and not just a computer programmer. The course has some very practical problems to solve, which will give you a sense of empowerment to tackle big data sets with ease.