Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing.
Este curso faz parte do Programa de cursos integrados Computação em nuvemComputação em Nuvem
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oferecido por
Programa de cursos integrados Computação em nuvemComputação em NuvemUniversidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-ChampaignInformações sobre o curso
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Prazos flexíveis
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Aprox. 20 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
- Distributed Computing
- C++
- Cloud Computing
- NoSQL
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Aprox. 20 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Programa - O que você aprenderá com este curso
5 horas para concluir
Week 1: Course Orientation and Classical Distributed Algorithms Continued
Lesson 1: To coordinate machines in a distributed system, this module first looks at classical algorithms for electing a leader, including the Ring algorithm and Bully algorithm. We also cover how Google’s Chubby and Apache Zookeeper solve leader election. Lesson 2: This module covers solutions to the problem of mutual exclusion, which is important for correctness in distributed systems with shared resources. We cover classical algorithms, including Ricart-Agrawala’s algorithm and Maekawa’s algorithm. We also cover Google’s Chubby support for mutual exclusion.
5 horas para concluir
11 vídeos (Total 122 mín.), 7 leituras, 2 testes
3 horas para concluir
Week 2: Concurrency and Replication Control
Lesson 1: Transactions are an important component of many cloud systems today. This module presents building blocks to ensure transactions work as intended, from Remote Procedure Calls (RPCs), to serial equivalence for transactions, to optimistic and pessimistic approaches to concurrency control, to deadlock avoidance/prevention. Lesson 2: This module covers how replication – maintaining copies of the same data at different locations – is used to provide many nines of availability in distributed systems, as well as different techniques for replication and for ensuring transactions commit correctly in spite of replication.
3 horas para concluir
8 vídeos (Total 95 mín.), 2 leituras, 1 teste
3 horas para concluir
Week 3: Emerging Paradigms
Lesson 1: We study the emerging area of stream processing, touching on key design aspects of Apache Storm. Lesson 2: We study how enormous graphs can be processed in clouds. Lesson 3: We study various types of networks/graphs that are both natural and artificial, and their surprising commonalities. Lesson 4: This module presents classical scheduling algorithms that have been used in operating systems since the inception of computers. We then cover two popular scheduling algorithms for Hadoop.
3 horas para concluir
9 vídeos (Total 110 mín.), 2 leituras, 1 teste
3 horas para concluir
Week 4: Classical Systems
Lesson 1: When files and directories are stored/accessed over the network, it is called a distributed file system. This module covers the working of distributed file systems like NFS and AFS. Lesson 2: This module covers Distributed Shared Memory systems, their techniques, and pros/cons. Lesson 3: This module looks at the area of sensor networks, starting from what’s inside a sensor mote and how networks of them work.
3 horas para concluir
6 vídeos (Total 109 mín.), 2 leituras, 1 teste
Avaliações
- 5 stars68,28%
- 4 stars24,59%
- 3 stars4,20%
- 2 stars0,97%
- 1 star1,94%
Principais avaliações do CONCEITOS DA COMPUTAÇÃO EM NUVEM: PARTE 2
por MR15 de jul de 2017
Great course, I would recommend to everyone who wants to understand the basics of cloud computing. The course material is excellent, the instructor Indy is phenomenal and the exams are marvelous.
por SR26 de jun de 2017
In continuation with Pt. I, this course delves into many more interesting topics. There's a significant scope of self-discovery and learning.
por AK12 de jul de 2018
I couldn't quite appreciate the utility of topics like sensor networks or structure of networks. Other than that, the course was fine and the programming assignment was interesting.
por ML8 de fev de 2017
Very challenging and very well presented material. I wish all coursera courses could be this way.
Sobre Programa de cursos integrados Computação em nuvemComputação em Nuvem
The Cloud Computing Specialization takes you on a tour through cloud computing systems. We start in in the middle layer with Cloud Computing Concepts covering core distributed systems concepts used inside clouds, move to the upper layer of Cloud Applications and finally to the lower layer of Cloud Networking. We conclude with a project that allows you to apply the skills you've learned throughout the courses.
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