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캘리포니아 샌디에고 대학교의 Introduction to Big Data 학습자 리뷰 및 피드백

4.6
5,549개의 평가
1,332개의 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

HM

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.

PB

May 25, 2018

A step by step approach stating from basic big data concept extending to Hadoop framework and hands on mapping and simple MapReduce application development effort.\n\nVery smooth learning experience.

필터링 기준:

Introduction to Big Data의 1,272개 리뷰 중 226~250

교육 기관: Jorge M

May 09, 2017

Great Introduction to Big Data!!

교육 기관: Paulo R V P

May 02, 2017

Excellent introduction to big data.

교육 기관: Charles, Q L

May 27, 2017

I highly recommend this course if you want to enter the world of Big Data. So far I have learned what big data is, the process of big data, distributed file systems, MapReduce programme model, Hadoop ecosystems, and more. It is simply a good course!

교육 기관: Husnain A

Oct 26, 2017

Very well structured

교육 기관: Luis A R G

Mar 02, 2017

Excelent course about basic knowlegment of Big Data, Exceleent materials and examples. Recomended

교육 기관: Steven V

Aug 01, 2017

Great intro course. The first 2 weeks move a bit slowly, but the final week of courses were very insightful.

교육 기관: Amol G

Oct 09, 2017

Lots of new information for beginners -> structured, delivered in clear speech, appropriate graphics

교육 기관: Robert R

Jan 04, 2018

Excellent introduction to the Big Data landscape!

교육 기관: Leonardo R d A

Jul 10, 2017

An excellent introductory course on Big Data addressing its application in current and practical subjects, with a good method of evaluation besides providing the necessary tools to apply all the theoretical content in practice.

교육 기관: Matheus G L

Jul 20, 2016

Good content, good teacher. Maybe should have a little more hands on assignments, but it is an excellent introduction to the topic!

교육 기관: Anand G

Apr 06, 2017

Great introduction to Big Data. so far best i have seen.

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: Eduardo A

May 25, 2017

The first course in Big Data Specialization, You must need to know the basics but it's very practical and simple to get inside Big Data

교육 기관: Hongyang Y

Feb 07, 2018

神课!

교육 기관: Luis E R

Sep 16, 2016

Great introduction

Clear and consice.

교육 기관: Govardhan H

Sep 26, 2016

I would like to enroll many such courses . Excellent Teaching . Thanks to teachers who spent their precious time in preparing slides and delivering quality teaching.. Hats off to Coursera. I recommend my friends too , to enroll such a wonderful course.

교육 기관: Thuong D H

Sep 23, 2016

Good course

교육 기관: Anup K M

Apr 22, 2018

very good

교육 기관: Venkata S P

Dec 11, 2016

Excellent course. Very good foundation.

교육 기관: Ismael F M

Oct 04, 2016

It is a great introduction to big data world

교육 기관: anupam b

Jun 11, 2017

Gives a great start to delving into the area of data science.

교육 기관: Davide M

Mar 19, 2018

good introduction to big data ideas and MapReduce concepts

교육 기관: Prabir B

May 25, 2018

A step by step approach stating from basic big data concept extending to Hadoop framework and hands on mapping and simple MapReduce application development effort.

Very smooth learning experience.

교육 기관: Edgar R E B

Jun 20, 2017

Excelent.

교육 기관: Federico S

Jan 27, 2018

I'd say it's an excellent first serious approach to Big Data. It has been great to do some hands-on MapReduce exercises