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.
oferecido por
Otimização discreta
Universidade de MelbourneInformações sobre o curso
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Resultados de carreira do aprendiz
29%
comecei uma nova carreira após concluir estes cursos
17%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 65 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
Constraint ProgrammingBranch And BoundDiscrete OptimizationLinear Programming (LP)
Resultados de carreira do aprendiz
29%
comecei uma nova carreira após concluir estes cursos
17%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 65 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade de Melbourne
The University of Melbourne is an internationally recognised research intensive University with a strong tradition of excellence in teaching, research, and community engagement. Established in 1853, it is Australia's second oldest University.
Programa - O que você aprenderá com este curso
2 horas para concluir
Welcome
These lectures and readings give you an introduction to this course: its philosophy, organization, and load. They also tell you how the assignments are a significant part of the class. This week covers the common input/output organization of the assignments, how they are graded, and how to succeed in this class.
2 horas para concluir
4 vídeos (Total 43 mín.), 2 leituras, 1 teste
7 horas para concluir
Knapsack
These lectures introduce optimization problems and some optimization techniques through the knapsack problem, one of the most well-known problem in the field. It discusses how to formalize and model optimization problems using knapsack as an example. It then reviews how to apply dynamic programming and branch and bound to the knapsack problem, providing intuition behind these two fundamental optimization techniques. The concept of relaxation and search are also discussed.
7 horas para concluir
9 vídeos (Total 101 mín.)
17 horas para concluir
Constraint Programming
Constraint programming is an optimization technique that emerged from the field of artificial intelligence. It is characterized by two key ideas: To express the optimization problem at a high level to reveal its structure and to use constraints to reduce the search space by removing, from the variable domains, values that cannot appear in solutions. These lectures cover constraint programming in detail, describing the language of constraint programming, its underlying computational paradigm and how it can be applied in practice.
17 horas para concluir
13 vídeos (Total 248 mín.), 1 leitura, 2 testes
13 horas para concluir
Local Search
Local search is probably the oldest and most intuitive optimization technique. It consists in starting from a solution and improving it by performing (typically) local perturbations (often called moves). Local search has evolved substantially in the last decades with a lot of attention being devoted on which moves to explore. These lectures explore the theory and practice of local search, from the concept of neighborhood and connectivity to meta-heuristics such as tabu search and simulated annealing.
13 horas para concluir
10 vídeos (Total 191 mín.)
Avaliações
Principais avaliações do OTIMIZAÇÃO DISCRETA
por SK29 de Mai 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.
por JB21 de Jul de 2017
Great course, the teacher is very clear and often goes into sufficient depth for the student to understand concepts. Assignments are challenging and help understanding course content.
por M2 de Jun de 2020
This is, without a doubt, one of the most interesting courses I have ever taken. You will be challenged to create your own ideas and you will get to know what NP hard means in practice.
por GD1 de Mai de 2019
I just completed the course. This an amazing course with an Outstanding professor and highly interesting, although difficult, assignments. Thanks for this! I am proud to have finished
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