Chevron Left
Volver a Optimización discreta

Opiniones y comentarios de aprendices correspondientes a Optimización discreta por parte de Universidad de Melbourne

539 calificaciones
132 reseña

Acerca del Curso

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming. Optimization technology is ubiquitous in our society. It schedules planes and their crews, coordinates the production of steel, and organizes the transportation of iron ore from the mines to the ports. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people. It organizes kidney exchanges and cancer treatments and helps scientists understand the fundamental fabric of life, control complex chemical reactions, and design drugs that may benefit billions of individuals. This class is an introduction to discrete optimization and exposes students to some of the most fundamental concepts and algorithms in the field. It covers constraint programming, local search, and mixed-integer programming from their foundations to their applications for complex practical problems in areas such as scheduling, vehicle routing, supply-chain optimization, and resource allocation....

Principales reseñas

29 de may. de 2019

Exceptional coverage of optimization fundamentals. Learning of practical applied methods. Real university level course, no water down "data science". Absolutely love it! Thank you professor Pascal.

21 de jul. de 2017

Great course, the teacher is very clear and often goes into sufficient depth for the student to understand concepts.\n\nAssignments are challenging and help understanding course content.

Filtrar por:

101 - 125 de 127 revisiones para Optimización discreta

por Adam K

20 de nov. de 2016

Great course, enjoyed each hour.

por Josep d R

15 de nov. de 2016

Really interesting and engaging

por Lê B C

2 de oct. de 2018

useful for optimize researcher

por Meytal L

21 de nov. de 2017

Great course! Very challenging

por 臧泽林

1 de ago. de 2017

good, good, but some difficult

por Blas R M

10 de feb. de 2021

Very interesting and useful


26 de abr. de 2020

This course is very good

por Shinny H

16 de oct. de 2016

Great course!! Love it!!

por Kamen P

18 de oct. de 2017

greatest course ever

por Xushegndong

17 de abr. de 2018

I love this course!

por Roberto p g j

29 de jul. de 2017

Very good course.

por Анисимов М И

26 de abr. de 2020

Nice hats though

por Serhat G

23 de ene. de 2020


por Marcin K

9 de oct. de 2017

superb !!!!!!!

por Priidik V

13 de ago. de 2020

Pretty cool

por Yury G

30 de abr. de 2017


por Bjarki Þ H

19 de may. de 2020

Very good

por Stefano M

12 de feb. de 2020

The quality of the lectures, as well as of the teaching material (slides, exercises, etc.), is just excellent. Thanks a lot to the instructors for putting so much effort in preparing it! Although having worked with optimization for a few years, I could learn a lot from this course. For someone aiming at learning optimization, there are not many well-structured courses/resources available; and this is surely one of the best resources I have found in years.

The course is difficult - much more difficult than other data science courses on Coursera - and thus requires many hours, good programming skills, and some dedication. But for me it was surely worth it!

My only remark/negative feedback is the lack of guidance - especially at the very beginning - on what external resources students are supposed to use for the assignments. I understand that this is in part intentional in order to make the course more challenging; however, compared to other courses I took, I feel that here the guidance is sometimes excessively little, and it is quite easy to get stuck on a given exercise. I honestly felt a bit lost at the beginning, and doubted whether it made sense to continue the course. Also, having access or not to licences of professional tools can make a significant difference in the level of difficulty of the assignments (implementing from scratch some solvers is, in some cases, a rather difficult task, which also requires quite advanced programming skills). I really think that providing more guidance/instructions on this would be of very high benefit here. There is actually a video which partly addresses this point, but it is only at the end of Week 3 (I guess many people abandon before having seen it - I recommend students to watch it at the very beginning).

Also, possibly related to this, my feeling is that currently the course is far less active than in the last years; the forums are not very active, and very seldom instructors/tutors intervene in the discussion.

por Jabez T W

31 de ago. de 2020

The content was very useful and very well presented, but I thought I needed more help with the assignments. An indication of how long each program should run should also be made clear. My MIP programs took a few hours for each problem to solve.

por Yury K

12 de nov. de 2019

Pascal is highly engaging lecturer. The course is superb, but is indeed advanced. Not very suitable as an intro to a topic (the way I tried to use it). Scraped through though, and rather proud of it :-)

por Baltasar B R

25 de ene. de 2017

I've enjoyed a lot this challenging course. To get a 10 in all the assignments is very hard. But 7 is achievable.

por Jyh1003040

23 de jun. de 2020

The content is exciting and the homework is equally challenging! Don't start if you are not ready.

por Juan L R A

21 de ago. de 2017

Challenging. I have missed some more explanation about algorithms....

por athanasio v

23 de may. de 2020

great lesson should be a little bit more programming friendly

por Ian B

11 de mar. de 2020

Great course, but a heavy workload.