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Отзывы учащихся о курсе Введение в большие данные от партнера Калифорнийский университет в Сан-Диего

4.6
звезд
Оценки: 9,574
Рецензии: 2,259

О курсе

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+....

Лучшие рецензии

HM
8 сент. 2019 г.

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
24 мая 2018 г.

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.

Фильтр по:

2076–2100 из 2,191 отзывов о курсе Введение в большие данные

автор: Fernando A S G

14 июня 2017 г.

A good summary about big data basics. Well structured. Very good course!

автор: Nadeem

4 янв. 2017 г.

It would be good if more explanation and more examples are demonstrated.

автор: Patil S S S

18 окт. 2020 г.

mostly everything was theoretical , much practical knowledge was needed

автор: Ankit R

30 июня 2020 г.

only theoretical knowledge, no practical use is shown in implementation

автор: Panumate C

15 дек. 2020 г.

not enough technical contents and too easy

Anyway, thank you very much

автор: Deleted A

5 мар. 2019 г.

The audio quality is so bad in the videos - it's really distracting.

автор: Amir K

4 авг. 2016 г.

Only skims the surface of Big Data, even for an introduction course.

автор: Manik S

11 авг. 2019 г.

Very easy. Videos are too slow, almost felt like a waste of time

автор: SUJANA C

27 дек. 2016 г.

The classes could have been delivered by creating more interest.

автор: Swati T

20 сент. 2017 г.

Was good foundational course. week 3 was most important for me

автор: Muhammad S V

20 янв. 2017 г.

this course need some odifications because of cloudera version

автор: eyal

28 февр. 2018 г.

To my opinion, the intro course should be shorter and faster.

автор: Punukolu B C

16 авг. 2016 г.

Introductory Level Course.Nothing much on analytical methods.

автор: Fazila P P

3 окт. 2020 г.

unable to understand some concept and it is not very clear

автор: Miguel G

10 янв. 2018 г.

Very good material but, in my opinion, too many seminars :)

автор: Rahul P

30 июня 2019 г.

The assignments and the quizes seemed pretty shallow...

автор: Haochuan W

23 окт. 2018 г.

Watch out for trolls in the peer grading assignments..

автор: WEIXUAN H

28 нояб. 2018 г.

to many high level concepts but lack of real examples

автор: Manuel

17 дек. 2017 г.

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

автор: Yajuvendra P

9 мар. 2017 г.

No technical support is provided for VM issues.

автор: Congcong Z

26 окт. 2017 г.

well explained landscape of data science

автор: Maria G

16 февр. 2017 г.

Solo videos con conceptos. Poco Hands-on

автор: Daniel A D

8 апр. 2018 г.

Good information but not very hands-on.

автор: Camilo P T

28 нояб. 2018 г.

basico y sencillo. Ideal para iniciar

автор: Gagan D S

8 апр. 2020 г.

Good to start from Basic. Love it