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GraphsDistributed ComputingBig DataMachine Learning
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 6개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 19시간 필요
영어
자막: 영어, 한국어

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일리노이대학교 어버너-섐페인캠퍼스 로고

일리노이대학교 어버너-섐페인캠퍼스

석사 학위 취득 시작

This 강좌 is part of the 100% online Master in Computer Science from 일리노이대학교 어버너-섐페인캠퍼스. If you are admitted to the full program, your courses count towards your degree learning.

강의 계획 - 이 강좌에서 배울 내용

1

1

완료하는 데 3시간 필요

Course Orientation

완료하는 데 3시간 필요
1개 동영상 (총 26분), 4 개의 읽기 자료, 1 개의 테스트
4개의 읽기 자료
Syllabus10m
About the Discussion Forums10m
Updating Your Profile10m
Social Media10m
1개 연습문제
Orientation Quiz10m
완료하는 데 2시간 필요

Module 1: Spark, Hortonworks, HDFS, CAP

완료하는 데 2시간 필요
13개 동영상 (총 108분), 1 개의 읽기 자료, 1 개의 테스트
13개의 동영상
1.1.2 Apache Spark11m
1.1.3 Spark Example: Log Mining9m
1.1.4 Spark Example: Logistic Regression7m
1.1.5 RDD Fault Tolerance4m
1.1.6 Interactive Spark4m
1.1.7 Spark Implementation4m
1.2.1 Introduction to Distros3m
1.2.2 Hortonworks23m
1.2.3 Cloudera CDH2m
1.2.4 MapR Distro2m
1.3.1 HDFS Introduction15m
1.3.2 YARN and MESOS9m
1개의 읽기 자료
Module 1 Overview10m
1개 연습문제
Module 1 Quiz30m
2

2

완료하는 데 6시간 필요

Module 2: Large Scale Data Storage

완료하는 데 6시간 필요
24개 동영상 (총 303분), 1 개의 읽기 자료, 1 개의 테스트
24개의 동영상
2.1.1 Introduction to MapReduce with Spark3m
2.1.2 MapReduce: Motivation15m
2.1.3 MapReduce Programming Model with Spark9m
2.1.4 MapReduce Example: Word Count9m
2.1.5 MapReduce Example: Pi Estimation & Image Smoothing15m
2.1.6 MapReduce Example: Page Rank13m
2.1.7 MapReduce Summary4m
2.2.1 Eventual Consistency – Part 110m
2.2.2 Eventual Consistency – Part 220m
2.2.3 Consistency Trade-Offs4m
2.2.4 ACID and BASE19m
2.2.5 Zookeeper and Paxos: Introduction10m
2.2.6 Paxos17m
2.2.7 Zookeeper16m
2.3.1 Cassandra Introduction27m
2.3.2 Redis7m
2.3.3 Redis Demonstration14m
2.4.1 HBase Usage API15m
2.4.2 HBase Internals - Part 117m
2.4.3 HBase Internals - Part 29m
2.4.4 Spark SQL8m
2.5.5 Spark SQL Demo8m
2.5.1 Kafka17m
1개의 읽기 자료
Module 2 Overview10m
1개 연습문제
Module 2 Quiz30m
3

3

완료하는 데 4시간 필요

Module 3: Streaming Systems

완료하는 데 4시간 필요
18개 동영상 (총 216분), 1 개의 읽기 자료, 1 개의 테스트
18개의 동영상
3.1.1 Streaming Introduction9m
3.1.2 "Big Data Pipelines: The Rise of Real-Time"7m
3.1.3 Storm Introduction: Protocol Buffers & Thrift15m
3.1.4 A Storm Word Count Example3m
3.1.5 Writing the Storm Word Count Example10m
3.1.6 Storm Usage at Yahoo3m
3.2.1 Anchoring and Spout Replay17m
3.2.2 Trident: Exactly Once Processing10m
3.3.1 Inside Apache Storm9m
3.3.2 The Structure of a Storm Cluster4m
3.3.3 Using Thrift in Storm10m
3.3.4 How Storm Schedulers Work12m
3.3.5 Scaling Storm to 4000 Nodes14m
3.3.6 Q&A with Bobby Evans (Yahoo) on Storm32m
3.4.1 Spark Streaming18m
3.4.2 Lambda and Kappa Architecture4m
3.4.3 Streaming Ecosystem24m
1개의 읽기 자료
Module 3 Overview10m
1개 연습문제
Module 3 Quiz30m
4

4

완료하는 데 4시간 필요

Module 4: Graph Processing and Machine Learning

완료하는 데 4시간 필요
18개 동영상 (총 173분), 1 개의 읽기 자료, 1 개의 테스트
18개의 동영상
4.1.2 Pregel - Part 17m
4.1.3 Pregel - Part 211m
4.1.4 Pregel - Part 36m
4.1.5 Giraph Introduction6m
4.1.6 Giraph Example4m
4.1.7 Spark GraphX15m
4.2.1 Big Data Machine Learning Introduction13m
4.2.2 Mahout: Introduction8m
4.2.3 Mahout kmeans5m
4.2.4 Mahout: Naïve Bayes9m
4.2.5 Mahout: fpm6m
4.2.6 Spark Naïve Bayes2m
4.2.7 Spark fpm2m
4.2.8 Spark ML/MLlib11m
4.2.9 Introduction to Deep Learning20m
4.2.10 Deep Neural Network Systems17m
4.3.1 Closing Remarks1m
1개의 읽기 자료
Module 4 Overview10m
1개 연습문제
Module 4 Quiz30m

검토

CLOUD COMPUTING APPLICATIONS, PART 2: BIG DATA AND APPLICATIONS IN THE CLOUD의 최상위 리뷰

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클라우드 컴퓨팅 특화 과정 정보

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....
클라우드 컴퓨팅

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