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

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud, 일리노이대학교 어버너-섐페인캠퍼스

4.2
189개의 평가
32개의 리뷰

About this Course

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

대학: UN

Apr 10, 2018

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

대학: MS

Nov 27, 2017

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

필터링 기준:

30개의 리뷰

대학: Manasvi Nallamothu

May 02, 2019

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대학: Austin Zimmer

Apr 26, 2019

Much better than Part 1. This course mostly shows the applications of the topics covered in the Cloud Computing Concepts course using the popular tools from when this course was recorded. There is a decent amount of redundant material from course overlap and this course could be made more concise, but there is still a decent amount of new material. You can probably pass most of the quizzes from knowledge gained in the other course though.

대학: Joseph Kilonzo

Mar 30, 2019

This is amazing

대학: shashank

Nov 14, 2018

Great for learning

대학: KimManSoo

Oct 05, 2018

good

대학: Aditya Kulkarni

Sep 05, 2018

Again, too much theory. More exercises needed.

대학: Michael Maximov

Jun 19, 2018

There are very small quizzes in this course. First two parts were much more better and more interesting

대학: Eduardo Barreto Lourenço

Jun 12, 2018

The content is quite complete and challenging.

대학: Ricardo Oneda Pereira de Toledo

Apr 16, 2018

The course is good, gives you an overview of many important technologies, although the last module is too superficial.

대학: Uche Ngadi

Apr 10, 2018

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