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Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud(으)로 돌아가기

일리노이대학교 어버너-섐페인캠퍼스의 Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud 학습자 리뷰 및 피드백

322개의 평가

강좌 소개

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information. We start the first week by introducing some major systems for data analysis including Spark and the major frameworks and distributions of analytics applications including Hortonworks, Cloudera, and MapR. By the middle of week one we introduce the HDFS distributed and robust file system that is used in many applications like Hadoop and finish week one by exploring the powerful MapReduce programming model and how distributed operating systems like YARN and Mesos support a flexible and scalable environment for Big Data analytics. In week two, our course introduces large scale data storage and the difficulties and problems of consensus in enormous stores that use quantities of processors, memories and disks. We discuss eventual consistency, ACID, and BASE and the consensus algorithms used in data centers including Paxos and Zookeeper. Our course presents Distributed Key-Value Stores and in memory databases like Redis used in data centers for performance. Next we present NOSQL Databases. We visit HBase, the scalable, low latency database that supports database operations in applications that use Hadoop. Then again we show how Spark SQL can program SQL queries on huge data. We finish up week two with a presentation on Distributed Publish/Subscribe systems using Kafka, a distributed log messaging system that is finding wide use in connecting Big Data and streaming applications together to form complex systems. Week three moves to fast data real-time streaming and introduces Storm technology that is used widely in industries such as Yahoo. We continue with Spark Streaming, Lambda and Kappa architectures, and a presentation of the Streaming Ecosystem. Week four focuses on Graph Processing, Machine Learning, and Deep Learning. We introduce the ideas of graph processing and present Pregel, Giraph, and Spark GraphX. Then we move to machine learning with examples from Mahout and Spark. Kmeans, Naive Bayes, and fpm are given as examples. Spark ML and Mllib continue the theme of programmability and application construction. The last topic we cover in week four introduces Deep Learning technologies including Theano, Tensor Flow, CNTK, MXnet, and Caffe on Spark....

최상위 리뷰


2018년 4월 9일

My understanding of Big Data technologies was really enhanced by this course. I have decided to pursue more of these underlying technologies after this course. Good job


2019년 9월 29일

Very Useful Course. Course material is massive and well prepared for the modern industry demands.

필터링 기준:

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud의 51개 리뷰 중 1~25

교육 기관: Ak D

2017년 9월 2일

This course is only informative. It provides good information of current big data technology and tool. It would be good if course also provide some assignment to complete so that course gives some hands on on technology.

교육 기관: Patrick S

2017년 6월 19일

This course is really useful to get an overview of the cloud technologies if you are ether curious know what's out there, or if you are trying to determine which technologies you should focus on for the problem you are trying to solve. I believe the course is a lot more relevant if you tried out some cloud framework (i.e. play with one of the Docker or Vagrant VM demos)

The lecturers are clear, and the audio and slides are of good quality. One of the most valuable pieces of information from this course (that you cannot easily discern from reading documentation on each framework) is how the lectures link strengths or weaknesses in a technology or algorithm to its inner-workings.

One small nitpick is that the quiz questions could be improved. A lot of them is regurgitation of definitions (or regurgitation of the order of bullet points in a slide somewhere), rather than analytical style questions that require the user to think of the concepts. The end result is that the quizzes are very easy but not valuable. I assume this course had assignments before, but they appear to have been removed.

교육 기관: Ning Z

2020년 10월 28일

Provides a very good overview of the essential components of distributed data processing. Popular frameworks and other tools such as Hadoop, Spark, Kafka, etc. are introduced. Several important algorithms are introduced in an animated and very accessible way, APIs and source code is also shown. Particular practical is, the course discusses which tool is best for what kind of job. The instructors are amiable and they talk in a very accessible way. Thank you very much for putting this course together!!! I enjoyed learning it.

교육 기관: Yaron K

2017년 8월 27일

Introduces major Big data technologies and products and their use-cases. There are some "rough edges" as this course has clearly been built from videos from former courses, and as usual with Coursera - there are numerous errors in the subtitles/transcripts, Problematic if you're deaf or find following spoken English difficult. Still - the lecturers are very enthusiastic and you can see that they really tried hard to explain the Big data technologies - so 4 stars rounded to 5.

교육 기관: Uche N

2018년 4월 10일

My understanding of Big Data technologies was really enhanced by this course. I have decided to pursue more of these underlying technologies after this course. Good job

교육 기관: Fillipe d S S

2016년 11월 13일

A very good course, with interesting topics about Big Data, Cloud Computing and MapReduce paradigm with real application examples.

교육 기관: André L D d S J

2020년 8월 5일

Great course, that second part gave me a broad view of how can i build distributed systems based on each use case.

교육 기관: Javed A

2019년 9월 30일

Very Useful Course. Course material is massive and well prepared for the modern industry demands.

교육 기관: Mahendra P S

2017년 11월 27일

Very good introduction of application concepts of cloud data computing. Thank You!

교육 기관: Kedar G

2020년 7월 15일

Really helpful to get insights into Big Data applications

교육 기관: uzair n

2016년 10월 31일

good things to learn about real world big problems

교육 기관: Eduardo B L

2018년 6월 12일

The content is quite complete and challenging.

교육 기관: Sudhanshu S

2016년 12월 18일

Better understanding of latest technology

교육 기관: Turdaliev N K

2016년 10월 29일

Love this course!!!

교육 기관: Ruiwen W

2020년 8월 14일

interesting course

교육 기관: Sreedevi R N

2020년 8월 6일

A very good course

교육 기관: shashank

2018년 11월 13일

Great for learning

교육 기관: Dario F B

2020년 11월 10일

Excelent as usual

교육 기관: Joseph K

2019년 3월 30일

This is amazing

교육 기관: Murat K

2017년 7월 5일

Great course!

교육 기관: Sarvesh G

2021년 1월 21일


교육 기관: KimManSoo

2018년 10월 5일


교육 기관: Raptis D

2016년 10월 15일

This course contained a great amount of information about several systems widely used nowadays for large-scale problems. There were analyses of the inner workings of these systems and their algorithms, as well as simple examples of how they can be used to solve common problems. The only drawback of the course is that the coursework was not significantly challenging and there were no programming assignments, which could give learners an opportunity to experiment with some of these technologies and acquire hands-on experience.

교육 기관: Shiva B

2018년 3월 19일

Good overview and jumping off points to go explore more. Great that a lot of tool sets were exposed to us. A list of all these tool sets in a document would be handy.

교육 기관: Birhanu D

2020년 2월 23일

There are a lot of technologies to cover and it is a dynamically changing subject. However, it will be great adding some hands-on exercises.