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Learner Reviews & Feedback for Introduction to Big Data by University of California San Diego

4.6
stars
10,480 ratings
2,451 reviews

About the Course

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+....

Top reviews

DK

Aug 11, 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

Sep 8, 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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1926 - 1950 of 2,400 Reviews for Introduction to Big Data

By Aravind M

Aug 3, 2018

A good course for understanding the fundamentals of Big Data, HDFS and concepts like MapReduce.

By Daniel A M

Sep 5, 2021

Great amount of information and real life examples. Clear and precise explanations. Good job!

By ashutosh k

Dec 16, 2017

So far it is good to go... still i m perusing 2 more weeks of this course. So left one star.

By Mohamed E T

Jun 7, 2017

More hand on exercises similar to the one at the end of the course would be very valuable.

By Visas V T

Feb 24, 2018

Great course. Explanation is good. Also gives good practical applications of each section

By Adnan B

Jan 27, 2017

Course is good to get initial background of Big Data and to understand What/Why Big Data.

By Kaddoum R

Sep 24, 2016

Content is very interesting, nice introduction to Big Data.

Slides can be improved though.

By Robert C

Jul 24, 2017

useful, but the english is a bit sketchy at times and the explanations could be clearer

By Ian M

Dec 28, 2016

Excellent introduction to Big Data and Hadoop. Practical exercise reinforces materials.

By Javier E T

May 8, 2021

cool course, sad thing is that doesn't have instructions to work with hadoop on linux.

By Jorge d l V G

Aug 28, 2016

The material OK, but some of the exercises and their interfaces are not well designed.

By Prashanth K

Oct 26, 2018

Good introductory course, although more advanced concepts could have been intrdoduced

By David L M

Jun 12, 2020

It is useful for beginners. However, I think the provided material could be updated.

By Cristhian M P V

Jun 7, 2020

Good explanation, I would like you to continue improving with the audiovisual media.

By Cristian A

May 10, 2020

The MapReduce exercise is a little confusing, specially after the vegetable example.

By Piyush P

Nov 5, 2018

Nice course but if programming part for map reduce was there it would be much better

By mike d

Apr 26, 2018

Dr. Altıntaş' presentation is rather choppy at first, but gets better after week 1.

By Victor O d S

Jun 17, 2020

It's a great introduction to the big data. That's improve my vision about the area

By Madhu M

May 31, 2020

A good introduction given for all basics of big data. clearly explained all topics

By SAYANTAN B

May 15, 2020

The explanation and elaboration of the coding part is very good and very helpfull.

By Gopesh T

Jan 21, 2017

I learnt basic of Big Data, exicited to dive deeper.Very informative and engaging

By Md. M Z

Dec 9, 2017

I really enjoyed the course and learned a lot but contents could be much better.

By Amit T

Feb 27, 2017

Would love to have more practical hands on exersizes and examples of map reduce.

By Tatiana M

Sep 18, 2016

Engaging and challenging, this course was an excellent introduction to Big Data!

By Pawinee

Nov 29, 2017

It is good introduction to Big data.

And would be great if having more hands-on.