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Back to Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

Learner Reviews & Feedback for Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud by University of Illinois Urbana-Champaign

4.3
stars
342 ratings

About the 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....

Top reviews

DT

Oct 10, 2016

The course could use a programming assignment to go along with the lectures.

SB

Mar 18, 2018

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.

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51 - 53 of 53 Reviews for Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

By Sushil S

•

Dec 27, 2019

This was an exasperating course - it is at times incoherent, at times just plain reading out of a teleprompter, and at times referring to assignments or slides which do not exist.

The quizzes can be safely tackled by going through 5% of the coursework and that is being generous. A deficit that a programming section could easily overcome.

I do feel bad for the instructors, i am sure it is not what they had in mind when they set out to design the course. Unfortunately it is hardly what one expects from a course part of a paid specialisation.

By David M

•

Dec 2, 2021

I've never had an instructor that was so clearly phoning it in. What's more, lots of the information presented about how the Cloud works is factually inaccurate, and no one has bothered to correct it. I strongly suggest that working professionals with even a basic level of experience with the Cloud (read: clearly more than the instructor) simply save themselves the aggravation.

By Michał M

•

May 2, 2017

I've already written a review for part 1 and I have the same opinion about this one. The course is rather poor and not challenging. Only general information about relevant topics that as well read on wikipedia. No exercises, no code assignments. A lot of this content was repeated from first two parts of this specialization.