課程信息
18,372 次近期查看

第 4 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為15 小時

建議:There is about 3-4 hours of video lectures per week. Each week's quiz takes about 30 minutes. ...

英語(English)

字幕:英語(English), 韓語

您將獲得的技能

GraphsDistributed ComputingBig DataMachine Learning

第 4 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為15 小時

建議:There is about 3-4 hours of video lectures per week. Each week's quiz takes about 30 minutes. ...

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

...
1 個視頻 (總計 26 分鐘), 4 個閱讀材料, 1 個測驗
4 個閱讀材料
Syllabus10分鐘
About the Discussion Forums10分鐘
Updating Your Profile10分鐘
Social Media10分鐘
1 個練習
Orientation Quiz10分鐘
完成時間為 2 小時

Module 1: Spark, Hortonworks, HDFS, CAP

In Module 1, we introduce you to the world of Big Data applications. We start by introducing you to Apache Spark, a common framework used for many different tasks throughout the course. We then introduce some Big Data distro packages, the HDFS file system, and finally the idea of batch-based Big Data processing using the MapReduce programming paradigm.

...
13 個視頻 (總計 108 分鐘), 1 個閱讀材料, 1 個測驗
13 個視頻
1.1.2 Apache Spark11分鐘
1.1.3 Spark Example: Log Mining9分鐘
1.1.4 Spark Example: Logistic Regression7分鐘
1.1.5 RDD Fault Tolerance4分鐘
1.1.6 Interactive Spark4分鐘
1.1.7 Spark Implementation4分鐘
1.2.1 Introduction to Distros3分鐘
1.2.2 Hortonworks23分鐘
1.2.3 Cloudera CDH2分鐘
1.2.4 MapR Distro2分鐘
1.3.1 HDFS Introduction15分鐘
1.3.2 YARN and MESOS9分鐘
1 個閱讀材料
Module 1 Overview10分鐘
1 個練習
Module 1 Quiz30分鐘
2
完成時間為 6 小時

Module 2: Large Scale Data Storage

In this module, you will learn about large scale data storage technologies and frameworks. We start by exploring the challenges of storing large data in distributed systems. We then discuss in-memory key/value storage systems, NoSQL distributed databases, and distributed publish/subscribe queues.

...
24 個視頻 (總計 303 分鐘), 1 個閱讀材料, 1 個測驗
24 個視頻
2.1.1 Introduction to MapReduce with Spark3分鐘
2.1.2 MapReduce: Motivation15分鐘
2.1.3 MapReduce Programming Model with Spark9分鐘
2.1.4 MapReduce Example: Word Count9分鐘
2.1.5 MapReduce Example: Pi Estimation & Image Smoothing15分鐘
2.1.6 MapReduce Example: Page Rank13分鐘
2.1.7 MapReduce Summary4分鐘
2.2.1 Eventual Consistency – Part 110分鐘
2.2.2 Eventual Consistency – Part 220分鐘
2.2.3 Consistency Trade-Offs4分鐘
2.2.4 ACID and BASE19分鐘
2.2.5 Zookeeper and Paxos: Introduction10分鐘
2.2.6 Paxos17分鐘
2.2.7 Zookeeper16分鐘
2.3.1 Cassandra Introduction27分鐘
2.3.2 Redis7分鐘
2.3.3 Redis Demonstration14分鐘
2.4.1 HBase Usage API15分鐘
2.4.2 HBase Internals - Part 117分鐘
2.4.3 HBase Internals - Part 29分鐘
2.4.4 Spark SQL8分鐘
2.5.5 Spark SQL Demo8分鐘
2.5.1 Kafka17分鐘
1 個閱讀材料
Module 2 Overview10分鐘
1 個練習
Module 2 Quiz30分鐘
3
完成時間為 4 小時

Module 3: Streaming Systems

This module introduces you to real-time streaming systems, also known as Fast Data. We talk about Apache Storm in length, Apache Spark Streaming, and Lambda and Kappa architectures. Finally, we contrast all these technologies as a streaming ecosystem.

...
18 個視頻 (總計 216 分鐘), 1 個閱讀材料, 1 個測驗
18 個視頻
3.1.1 Streaming Introduction9分鐘
3.1.2 "Big Data Pipelines: The Rise of Real-Time"7分鐘
3.1.3 Storm Introduction: Protocol Buffers & Thrift15分鐘
3.1.4 A Storm Word Count Example3分鐘
3.1.5 Writing the Storm Word Count Example10分鐘
3.1.6 Storm Usage at Yahoo3分鐘
3.2.1 Anchoring and Spout Replay17分鐘
3.2.2 Trident: Exactly Once Processing10分鐘
3.3.1 Inside Apache Storm9分鐘
3.3.2 The Structure of a Storm Cluster4分鐘
3.3.3 Using Thrift in Storm10分鐘
3.3.4 How Storm Schedulers Work12分鐘
3.3.5 Scaling Storm to 4000 Nodes14分鐘
3.3.6 Q&A with Bobby Evans (Yahoo) on Storm32分鐘
3.4.1 Spark Streaming18分鐘
3.4.2 Lambda and Kappa Architecture4分鐘
3.4.3 Streaming Ecosystem24分鐘
1 個閱讀材料
Module 3 Overview10分鐘
1 個練習
Module 3 Quiz30分鐘
4
完成時間為 4 小時

Module 4: Graph Processing and Machine Learning

In this module, we discuss the applications of Big Data. In particular, we focus on two topics: graph processing, where massive graphs (such as the web graph) are processed for information, and machine learning, where massive amounts of data are used to train models such as clustering algorithms and frequent pattern mining. We also introduce you to deep learning, where large data sets are used to train neural networks with effective results.

...
18 個視頻 (總計 173 分鐘), 1 個閱讀材料, 1 個測驗
18 個視頻
4.1.2 Pregel - Part 17分鐘
4.1.3 Pregel - Part 211分鐘
4.1.4 Pregel - Part 36分鐘
4.1.5 Giraph Introduction6分鐘
4.1.6 Giraph Example4分鐘
4.1.7 Spark GraphX15分鐘
4.2.1 Big Data Machine Learning Introduction13分鐘
4.2.2 Mahout: Introduction8分鐘
4.2.3 Mahout kmeans5分鐘
4.2.4 Mahout: Naïve Bayes9分鐘
4.2.5 Mahout: fpm6分鐘
4.2.6 Spark Naïve Bayes2分鐘
4.2.7 Spark fpm2分鐘
4.2.8 Spark ML/MLlib11分鐘
4.2.9 Introduction to Deep Learning20分鐘
4.2.10 Deep Neural Network Systems17分鐘
4.3.1 Closing Remarks1分鐘
1 個閱讀材料
Module 4 Overview10分鐘
1 個練習
Module 4 Quiz30分鐘
4.2
32 個審閱Chevron Right

來自Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud的熱門評論

創建者 UNApr 10th 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

創建者 MSNov 27th 2017

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

講師

Avatar

Reza Farivar

Data Engineering Manager at Capital One, Adjunct Research Assistant Professor of Computer Science
Department of Computer Science
Avatar

Roy H. Campbell

Professor of Computer Science
Department of Computer Science

立即開始攻讀碩士學位

此 課程 隸屬於 伊利诺伊大学香槟分校 提供的 100% 在線 Master in Computer Science。如果您被錄取參加全部課程,您的課程將計入您的學位學習進程。

關於 伊利诺伊大学香槟分校

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. ...

關於 云计算 專項課程

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....
云计算

常見問題

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

還有其他問題嗎?請訪問 學生幫助中心