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Opiniones y comentarios de aprendices correspondientes a Introduction to Big Data por parte de Universidad de California en San Diego

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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+....

Principales reseñas

DK

11 de ago. de 2021

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.

HM

8 de sep. de 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.

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2301 - 2325 de 2,406 revisiones para Introduction to Big Data

por WEIXUAN H

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28 de nov. de 2018

to many high level concepts but lack of real examples

por Manuel

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17 de dic. de 2017

Too generic and high-level, not a lot of learning

por Yajuvendra P

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9 de mar. de 2017

No technical support is provided for VM issues.

por Karen H

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28 de may. de 2021

I spent tons of time to solve centos issues

por Congcong Z

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26 de oct. de 2017

well explained landscape of data science

por Maria G

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16 de feb. de 2017

Solo videos con conceptos. Poco Hands-on

por Daniel A D

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8 de abr. de 2018

Good information but not very hands-on.

por Camilo P T

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28 de nov. de 2018

basico y sencillo. Ideal para iniciar

por Gagan D S

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8 de abr. de 2020

Good to start from Basic. Love it

por SERGEI S

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12 de jul. de 2017

it is so simple, but informative

por YUVARANI P 2 C A

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4 de ago. de 2020

It is very easy to understand

por Franciszek G

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22 de oct. de 2018

Too little technical aspects.

por Bhawna B

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23 de ago. de 2017

need to give more assignments

por Alexander H

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10 de nov. de 2018

More hands on would be good

por YongDeuk C

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20 de nov. de 2016

it's too much basic stuffs.

por Aditya A

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26 de feb. de 2021

Add more hands on sessions

por Alvaro M

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18 de sep. de 2017

Booooooooorinnnnggggg

por Irfan S

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11 de sep. de 2017

Its very basic course

por Shivraj J

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19 de dic. de 2016

Basic info covered.

por Roman N

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4 de nov. de 2016

too philosophical

por Toti S

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8 de ene. de 2019

Very theoretical

por Alex B

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18 de feb. de 2017

Quite shallow...

por Ravi

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14 de nov. de 2017

Lot of talking.

por Deleted A

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17 de mar. de 2017

Not good enough

por Marcelo G D L

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12 de may. de 2020

A bit outdated

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