Acerca de este curso: 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).
Para quién es esta clase: Learners with at least a little bit of programming experience who want to learn the essentials of algorithms. In a University computer science curriculum, this course is typically taken in the third year.
Creada por: Stanford University
Enseñado por: Tim Roughgarden, Professor
Computer Science
| Información básica | Curso 4 de 4 en Algorithms Specialization |
| Nivel | Intermedio |
| Compromiso | 4 weeks of study, 4-8 hours/week |
| Idioma | English |
| Cómo aprobar | Aprueba todas las tareas calificadas para completar el curso. |
| Calificaciones del usuario |
Programa
SEMANA 1
Week 1
The Bellman-Ford algorithm; all-pairs shortest paths.
14 videos, 4 lecturas
- Материал для самостоятельного изучения: Week 1 Overview
- Материал для самостоятельного изучения: Overview, Resources, and Policies
- Материал для самостоятельного изучения: Lecture Slides
- Vídeo: Optimal Substructure
- Vídeo: The Basic Algorithm I
- Vídeo: The Basic Algorithm II
- Vídeo: Detecting Negative Cycles
- Vídeo: A Space Optimization
- Vídeo: Internet Routing I [Optional]
- Vídeo: Internet Routing II [Optional]
- Vídeo: Problem Definition
- Vídeo: Optimal Substructure
- Vídeo: The Floyd-Warshall Algorithm
- Vídeo: A Reweighting Technique
- Vídeo: Johnson's Algorithm I
- Vídeo: Johnson's Algorithm II
- Материал для самостоятельного изучения: Optional Theory Problems (Week 1)
Calificado: Problem Set #1
Calificado: Programming Assignment #1
SEMANA 2
Week 2
NP-complete problems and exact algorithms for them.
11 videos, 2 lecturas
- Материал для самостоятельного изучения: Week 2 Overview
- Vídeo: Reductions and Completeness
- Vídeo: Definition and Interpretation of NP-Completeness I
- Vídeo: Definition and Interpretation of NP-Completeness II
- Vídeo: The P vs. NP Question
- Vídeo: Algorithmic Approaches to NP-Complete Problems
- Vídeo: The Vertex Cover Problem
- Vídeo: Smarter Search for Vertex Cover I
- Vídeo: Smarter Search for Vertex Cover II
- Vídeo: The Traveling Salesman Problem
- Vídeo: A Dynamic Programming Algorithm for TSP
- Материал для самостоятельного изучения: Optional Theory Problems (Week 2)
Calificado: Problem Set #2
Calificado: Programming Assignment #2
SEMANA 3
Week 3
Approximation algorithms for NP-complete problems.
6 videos, 1 lectura
- Материал для самостоятельного изучения: Week 3 Overview
- Vídeo: Analysis of a Greedy Knapsack Heuristic I
- Vídeo: Analysis of a Greedy Knapsack Heuristic II
- Vídeo: A Dynamic Programming Heuristic for Knapsack
- Vídeo: Knapsack via Dynamic Programming, Revisited
- Vídeo: Ananysis of Dynamic Programming Heuristic
Calificado: Problem Set #3
Calificado: Programming Assignment #3
SEMANA 4
Week 4
Local search algorithms for NP-complete problems; the wider world of algorithms.
11 videos, 3 lecturas
- Материал для самостоятельного изучения: Week 4 Overview
- Vídeo: The Maximum Cut Problem II
- Vídeo: Principles of Local Search I
- Vídeo: Principles of Local Search II
- Vídeo: The 2-SAT Problem
- Vídeo: Random Walks on a Line
- Vídeo: Analysis of Papadimitriou's Algorithm
- Vídeo: Stable Matching [Optional]
- Vídeo: Matchings, Flows, and Braess's Paradox [Optional]
- Vídeo: Linear Programming and Beyond [Optional]
- Vídeo: Epilogue
- Материал для самостоятельного изучения: Optional Theory Problems (Week 4)
- Материал для самостоятельного изучения: Info and FAQ for final exam
Calificado: Problem Set #4
Calificado: Programming Assignment #4
Calificado: Final Exam
Preguntas Frecuentes
Cómo funciona
Задания курса
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Creadores
Stanford University
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.
Tarifa
| Comprar curso | |
|---|---|
| Accede a los materiales del curso | Disponible |
| Accede a los materiales con calificación | Disponible |
| Recibe una calificación final | Disponible |
| Obtén un Certificado de curso para compartir | Disponible |
Calificaciones y revisiones
A very nice introduction to algorithms from a high-level mathematical perspective. This course is great for building intuition about key concepts. Highly recommended. I did the Princeton algorithms course first. Both are great. The first tests one more on the implementation side and requires Java. This course is more focused on theory and a great complement. Too bad there is not a Part 5, 6, ….
Great one for people with advanced understanding! Others will find it slightly hard to follow!
This was the hardest course in this specialization. But the quality of the course material and the instructor's way of explaining kept me engaged and motivated. The problems and the programming assignments were significantly harder than the earlier courses in this specialization - but it felt that much more satisfying after completing the course. Special thanks to Prof. Roughgarden for creating such an amazing course. :-)
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BG
Excellent course! Bravo to the teacher for the commitment provided in this course. Kind regards.