The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).
Este curso faz parte do Programa de cursos integrados Algoritmos
oferecido por
Informações sobre o curso
Habilidades que você terá
- Data Structure
- Algorithms
- Np-Completeness
- Dynamic Programming
oferecido por

Universidade de Stanford
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Programa - O que você aprenderá com este curso
Week 1
The Bellman-Ford algorithm; all-pairs shortest paths.
Week 2
NP-complete problems and exact algorithms for them.
Week 3
Approximation algorithms for NP-complete problems.
Week 4
Local search algorithms for NP-complete problems; the wider world of algorithms.
Avaliações
- 5 stars85,21%
- 4 stars12,97%
- 3 stars1,16%
- 2 stars0,51%
- 1 star0,12%
Principais avaliações do SHORTEST PATHS REVISITED, NP-COMPLETE PROBLEMS AND WHAT TO DO ABOUT THEM
Really happy to finish this specialization and I will still study algorithms in the future.
Great course in general, got the chance to dive a little deeper into the world of computer science.
This is the most challenging course in this specialization. Assignments as well as test questions require good amount of thinking. One of the best courses I did on Coursera.
Thoroughly enjoyed this course! Problems and assignments are quite challenging but doable
Sobre Programa de cursos integrados Algoritmos
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.

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