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Advanced Algorithms and Complexity(으)로 돌아가기

캘리포니아 샌디에고 대학교의 Advanced Algorithms and Complexity 학습자 리뷰 및 피드백

4.6
별점
432개의 평가
88개의 리뷰

강좌 소개

You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others. Next we discuss inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice. We finish with a soft introduction to streaming algorithms that are heavily used in Big Data processing. Such algorithms are usually designed to be able to process huge datasets without being able even to store a dataset....

최상위 리뷰

EM

Jan 04, 2018

As usual, complex arguments explained in simple terms!\n\nSome problems are really tough! (e.g. there's a problem from Google Code Jam).\n\nThank you for this course!

CS

Aug 26, 2019

Very Very Challenging Course , it test your patience and rewards is extremely satisfying. Lot of learning on a complicated subject of NP-Hard problems.

필터링 기준:

Advanced Algorithms and Complexity의 86개 리뷰 중 26~50

교육 기관: Hidetake T

Aug 15, 2019

This course is very difficult. Possible to pass programming assignments only after finishing previous courses.

교육 기관: Tamas S

Jun 08, 2019

Very good collection of advanced topics, even useful for the 6th course in the specialization!

교육 기관: Quynh V

Sep 15, 2019

I am not good in this course. But I'm always try the best! Awesome course, thank you so much!

교육 기관: Vedant B K

Apr 04, 2020

It has been a great experience learning with coursera !!!

교육 기관: Prathmesh S J

May 22, 2020

Most Difficult Course but It develops mankind Power

교육 기관: b s v

Oct 19, 2017

Need more test cases for assignments.

교육 기관: Raunak N

Jul 31, 2018

this course gave me hell of a time

교육 기관: Ayran T O

Sep 12, 2019

Very difficult but challenging!

교육 기관: Shaashwat A

Apr 09, 2019

amazing course well detailed

교육 기관: Arjun N

Mar 13, 2018

Amazing set of problems.

교육 기관: Lie C

Jul 11, 2018

hard coursers, but good

교육 기관: Pradyumn A

May 28, 2017

Indeed a great course!

교육 기관: Archak D

Apr 11, 2019

VERY GOOD KNOWLEDGE.

교육 기관: Mahmmoud M

Dec 27, 2019

Very helpful

Thanks

교육 기관: Padmakumar N

Aug 05, 2017

Very good course

교육 기관: Aman A

Jul 14, 2018

Challenging!

교육 기관: Xi Y

Feb 16, 2017

illuminative

교육 기관: Akash k y

Jun 10, 2019

Best course

교육 기관: Chin J C

Nov 06, 2018

really hard

교육 기관: Ştefan B

Mar 08, 2017

Nice one.

교육 기관: ritik r

Mar 29, 2019

SUPER

교육 기관: Liu Y

Dec 17, 2017

Great

교육 기관: RAHUL B

Mar 14, 2019

GOOD

교육 기관: SHREYAS S

Mar 27, 2019

aa

교육 기관: Greg G

Apr 03, 2020

An incredibly challenging course with a lot of juicy content. Builds heavily on previous courses in the Data Structures and Algorihms specialization such as hashing, graph searching, data structures, stress testing, algorithmic complexity etc. But given you completed those, you already know how to solve such problems, and it's rewarding to see all the pieces working as you put them together. Also, this course requires some additional maths knowledge such as linear algebra, logic and probability theory. All in all, the "advanced" attribute fits well.

Assignments are wildly varying in difficulty - completing one took me 3 days, another was done in just 30 minutes. They were mostly fine (except for the simplex linear programming solver which I haven't even attempted) and forums were very useful for guidance.

The videos themselves are usually okay, the only seriously lacking area is the linear programming week with Daniel Kane. LP (a fundamental subject in computer science) in itself could fill a whole course, but simply put, his explanations and examples fell short, it was very hard to understand them. So refer to the additional readings there if you are interested. On the other hand, the rest of the course is nice.

Week 1 (flow networks) with Daniel was also kind of hard, but not impossible to understand. Alexander Kulikov's 2 weeks on NP-completeness are the high mark of the course, with engaging and clear explanations. Michael Kapralov's optional 'heavy hitters problem' videos are also interesting and pretty well explained.