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.
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Cloud Computing SpecializationUniversity of Illinois at Urbana-ChampaignAbout this Course
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Course 2 of 6 in the
Flexible deadlines
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Approx. 19 hours to complete
English
Subtitles: English, Korean
Skills you will gain
Distributed ComputingC++Cloud ComputingNoSQL
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 19 hours to complete
English
Subtitles: English, Korean
Offered by
University of Illinois at 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.
Start working towards your Master's degree
This course is part of the 100% online Master in Computer Science from University of Illinois at Urbana-Champaign.
If you are admitted to the full program, your courses count towards your degree learning.
Syllabus - What you will learn from this course
4 hours to complete
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.
4 hours to complete
11 videos (Total 122 min), 7 readings, 2 quizzes
11 videos
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23m
Week 1 Introduction1m
1.1. The Election Problem8m
1.2. Ring Leader Election14m
1.3. Election in Chubby and ZooKeeper9m
1.4. Bully Algorithm9m
2.1. Introduction and Basics12m
2.2. Distributed Mutual Exclusion10m
2.3. Ricart-Agrawala's Algorithm11m
2.4. Maekawa's Algorithm and Wrap-Up16m
7 readings
Orientation Overview10m
Syllabus10m
About the Discussion Forums10m
Course Learning Community and Social Media10m
Week 1 Overview10m
Homework 1 Instructions10m
Programming Assignment Instructions10m
2 practice exercises
Orientation Quiz10m
Homework 120m
2 hours to complete
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.
2 hours to complete
8 videos (Total 95 min), 2 readings, 1 quiz
8 videos
1.1. RPCs17m
1.2. Transactions13m
1.3. Serial Equivalence12m
1.4. Pessimistic Concurrency13m
1.5. Optimistic Concurrency Control9m
2.1. Replication14m
2.2. Two-Phase Commit11m
2 readings
Week 2 Overview10m
Homework 2 Instructions10m
1 practice exercise
Homework 230m
3 hours to complete
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 hours to complete
9 videos (Total 110 min), 2 readings, 1 quiz
9 videos
Stream Processing in Storm15m
Distributed Graph Processing16m
Structure of Networks21m
4.1. Single-processor Scheduling11m
4.2. Hadoop Scheduling11m
4.3. Dominant-Resource Fair Scheduling8m
Storm Demo 9m
Apache Spark by Faria Kalim12m
2 readings
Week 3 Overview10m
Homework 3 Instructions10m
1 practice exercise
Homework 330m
3 hours to complete
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 hours to complete
6 videos (Total 109 min), 2 readings, 1 quiz
6 videos
1.1. File System Abstraction23m
1.2. NFS and AFS14m
Distributed Shared Memory17m
Sensor and Their Networks30m
Interview with Brighten Godfrey23m
2 readings
Week 4 Overview10m
Homework 4 Instructions10m
1 practice exercise
Homework 420m
Reviews
TOP REVIEWS FROM CLOUD COMPUTING CONCEPTS: PART 2
by MRJul 15, 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.
by TCJul 2, 2017
Good, but not a fan of using C++ and that made the programming assignment tricky, especially since can only chnage a few things and the provided code is not always very well explained.
by AKJul 12, 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.
by HGApr 14, 2017
Just the same as the first course. Medium-hard quizzes and a hard programming assigment that is actually harder to understand than to develop. Overall a five star course.
About the Cloud Computing Specialization
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.
The first four courses in this Specialization form the lecture component of courses in our online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.
Frequently Asked Questions
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What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
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Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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