Informações sobre o curso: The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Para quem é direcionado este curso: 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.
Desenvolvido por: Stanford University
Ministrado por: Tim Roughgarden, Professor
Computer Science
| Informações básicas | Curso 3 de 4 no Algorithms Specialization |
| Nível | Intermediate |
| Compromisso | 4 weeks of study, 4-8 hours/week |
| Idioma | English |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Programa
SEMANA 1
Week 1
Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
16 vídeos, 4 leituras
- Reading: Week 1 Overview
- Reading: Overview, Resources, and Policies
- Reading: Lecture slides
- Vídeo: Application: Internet Routing
- Vídeo: Application: Sequence Alignment
- Vídeo: Introduction to Greedy Algorithms
- Vídeo: Application: Optimal Caching
- Vídeo: Problem Definition
- Vídeo: A Greedy Algorithm
- Vídeo: Correctness Proof - Part I
- Vídeo: Correctness Proof - Part II
- Vídeo: Handling Ties [Advanced - Optional]
- Vídeo: MST Problem Definition
- Vídeo: Prim's MST Algorithm
- Vídeo: Correctness Proof I
- Vídeo: Correctness Proof II
- Vídeo: Proof of Cut Property [Advanced - Optional]
- Vídeo: Fast Implementation I
- Vídeo: Fast Implementation II
- Reading: Optional Theory Problems (Week 1)
Nota atribuída: Problem Set #1
Nota atribuída: Programming Assignment #1
SEMANA 2
Week 2
Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
16 vídeos, 2 leituras
- Reading: Week 2 Overview
- Vídeo: Kruskal's MST Algorithm
- Vídeo: Correctness of Kruskal's Algorithm
- Vídeo: Implementing Kruskal's Algorithm via Union-Find I
- Vídeo: Implementing Kruskal's Algorithm via Union-Find II
- Vídeo: MSTs: State-of-the-Art and Open Questions [Advanced - Optional]
- Vídeo: Application to Clustering
- Vídeo: Correctness of Clustering Algorithm
- Vídeo: Lazy Unions [Advanced - Optional]
- Vídeo: Union-by-Rank [Advanced - Optional]
- Vídeo: Analysis of Union-by-Rank [Advanced - Optional]
- Vídeo: Path Compression [Advanced - Optional]
- Vídeo: Path Compression: The Hopcroft-Ullman Analysis I [Advanced - Optional]
- Vídeo: Path Compression: The Hopcroft-Ullman Analysis II [Advanced - Optional]
- Vídeo: The Ackermann Function [Advanced - Optional]
- Vídeo: Path Compression: Tarjan's Analysis I [Advanced - Optional]
- Vídeo: Path Compression: Tarjan's Analysis II [Advanced - Optional]
- Reading: Optional Theory Problems (Week 2)
Nota atribuída: Problem Set #2
Nota atribuída: Programming Assignment #2
SEMANA 3
Week 3
Huffman codes; introduction to dynamic programming.
11 vídeos, 1 leitura
- Reading: Week 3 Overview
- Vídeo: Introduction and Motivation
- Vídeo: Problem Definition
- Vídeo: A Greedy Algorithm
- Vídeo: A More Complex Example
- Vídeo: Correctness Proof I
- Vídeo: Correctness Proof II
- Vídeo: Introduction: Weighted Independent Sets in Path Graphs
- Vídeo: WIS in Path Graphs: Optimal Substructure
- Vídeo: WIS in Path Graphs: A Linear-Time Algorithm
- Vídeo: WIS in Path Graphs: A Reconstruction Algorithm
- Vídeo: Principles of Dynamic Programming
Nota atribuída: Problem Set #3
Nota atribuída: Programming Assignment #3
SEMANA 4
Week 4
Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
10 vídeos, 3 leituras
- Reading: Week 4 Overview
- Vídeo: The Knapsack Problem
- Vídeo: A Dynamic Programming Algorithm
- Vídeo: Example [Review - Optional]
- Vídeo: Optimal Substructure
- Vídeo: A Dynamic Programming Algorithm
- Vídeo: Problem Definition
- Vídeo: Optimal Substructure
- Vídeo: Proof of Optimal Substructure
- Vídeo: A Dynamic Programming Algorithm I
- Vídeo: A Dynamic Programming Algorithm II
- Reading: Optional Theory Problems (Week 4)
- Reading: Info and FAQ for final exam
Nota atribuída: Problem Set #4
Nota atribuída: Programming Assignment #4
Nota atribuída: Final Exam
Perguntas frequentes
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Desenvolvedores
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.
Custo
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
Classificações e avaliações
Very difficult! That's what heroes do.
Excellent Course. I really enjoyed it. Stretched my imagination and analytical capacity to new frontiers. The problems studied during the course stimulate you to learn more about new algorithms and coding, There's so much more to learn now. Many thanks to Professor Roughgarden and his team for making this available. Keep the great work!
I thought this course was kind of harder than the 2 previous one in the specialization (mainly the problems sets which require way more thinking)
It's a very good quality course to strenghten the basics, but in depth.
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Tim Roughgarden manages to turn a dry topic like "Algos" into a sexy hot one!!