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캘리포니아 샌디에고 대학교의 Introduction to Big Data 학습자 리뷰 및 피드백

8,564개의 평가
2,037개의 리뷰

강좌 소개

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. * Get value out of Big Data by using a 5-step process to structure your analysis. * Identify what are and what are not big data problems and be able to recast big data problems as data science questions. * Provide an explanation of the architectural components and programming models used for scalable big data analysis. * Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. * Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+....

최상위 리뷰


Sep 09, 2019

I love the course. It goes deep into the foundations, and then finishes up with an actual lab where you learn by practice. I greatly benefited from it and feel I have achieved a milestone in big data.


Jul 14, 2017

First of all i would like to take this opportunity to thanks the instructors the course is well structured and explained the foundations with real world problems with easy to understand the concepts.

필터링 기준:

Introduction to Big Data의 1,973개 리뷰 중 451~475

교육 기관: Abhijeet K

Jan 28, 2018

Great way of teaching ...personalised learning....looking for more courses with them...

교육 기관: Ashish J

Aug 17, 2017

It was nice to get some basic understanding and run some hadoop commands. I enjoyed it.

교육 기관: Lokesh J

Jun 22, 2017

Value to money and providing good exposure as i was just beginner so learn a lot.Thanks

교육 기관: Andrew W T

Apr 19, 2017

This was a very good course to get a foundation in Big Data terms, concepts, and tools.

교육 기관: Renjith

Jul 03, 2019

Very beneficial course for big data beginners. It gave a great interest to learn more.

교육 기관: Chin C L

Jan 31, 2019

The course is pretty good. It help me to understand some basic of Big Data and Hadoop.

교육 기관: Nagarjuna

Oct 01, 2018

wonderfully scripted for beginners to understand and learn the basics of the big data.

교육 기관: martin k

Aug 03, 2018

Very good course, very good topics, got a very good overview about how to use big data

교육 기관: Arturo R

Jun 02, 2018

I liked the introductory course, the concepts and the explanation was clear. Thank you

교육 기관: Nithin P

Jul 21, 2017

This course is really good for beginners. Helps understand all the aspects of Big Data

교육 기관: Nicolas L M

Oct 29, 2016

Excellent course to learn about big data and how to apply this knowledge in real cases

교육 기관: jorge a r o

Sep 08, 2020

Excellent course! really well structured! content easy to process. super recommended!

교육 기관: Low Z Y J

Jun 20, 2020

the second act was quite a steep curve. a great introduction overall however. thanks.

교육 기관: Juan E A

Jun 17, 2020

Un excelente curso practico para iniciar y conocer los conceptos basicos de Big Data!

교육 기관: Nikil R

Jun 05, 2018

this course gives very good understanding of foundations and technologies in big data

교육 기관: Anne M

Mar 12, 2018

Thanks so much. I learned a lot about Big Data. The hands-on are very easy to follow.

교육 기관: Ana M

Mar 03, 2018

I've learned a lot about how the data could be structure and the tools to exploid it.

교육 기관: Ashish C

Apr 12, 2017

Very well formulated with all the necessary details required to understand the basics

교육 기관: Shantanu P

Dec 19, 2016

I learnt many things about Big Data. Now at least I have some basic foundation in it.

교육 기관: Louisa C H

Jul 22, 2020

This course easy to follow and give me new knowledge and new basic skill in big data

교육 기관: Sirak K

Jun 09, 2020

I like the Hadoop part especially MapReduce the most. It is very easy to understand.

교육 기관: Anupam k

May 13, 2020

it was really a good cousre thank you coursera for giving such a wonderful sesssion

교육 기관: Haris G

Mar 24, 2020

A wonderful course for beginners you can learn a lot. Instructors are super awesome.

교육 기관: vincent

Mar 03, 2019

The best introduction course I had so far. Now I know the big picture about big data

교육 기관: luân n

Aug 26, 2018

It is a great course for beginner to understand about Big Data and Hadoop ecosystem.