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

8,924 ratings
2,131 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


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.


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.

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451 - 475 of 2,064 Reviews for Introduction to Big Data

By Miguel M P

Aug 22, 2020

The only thing i don't like is the autocalification of the students the are many trolls...

By Aravind R L

Jun 01, 2020

Excellent to course to understand Big Data and relevance with IIOT, Data Science and Cloud

By Shabanova O

Apr 12, 2020

Great course. He gives excellent theoretical and practical skills. I recommend for passing

By Mohamed S

Apr 04, 2019

I have benefited greatly from this course, which is a powerful start to the big data field

By Maria F O D

Feb 06, 2017

Excelente!! Muy buen curso, como está enfocado y los temas que cubre. Ejemplos muy claros.

By Jyothi k

Dec 29, 2016

thanks for instructors this course helped me to understand what exactly bib data modules

By Laura R

Jul 24, 2020

All information is useful. The material is presented in a clear and comprehensible manner

By Shrajna S

May 10, 2020

This course gave me a thorough insight into Big Data with a few hands-on implementations.


Apr 10, 2020

Got to known about Big Data and it's applications in our daily life. Wonderful trainers.

By Ashok K

May 17, 2019

Awesome learning experience and added great value to my knowledge, thank you so very much

By Yash V

Jun 19, 2017

Awesome teachers and a well rounded course curriculum to step in to the world of Big data

By Vihang P

Nov 22, 2016

Kindler Gentler introduction to Big Data Concepts and Hadoop hands on exercise was great!

By Zubair s

Aug 13, 2016

I love this course its worth for a basic and freshers learning

Thanks Coursera for this...

By kaan g

May 07, 2020

Really good that is prepared. I suggest for person who would like to introduce big data.

By Majji H

Jul 29, 2019

This would be purely useful to beginners who would like to start the course from scratch

By Elisabeth G

Sep 01, 2020

It is a simple course for beginner like me to understand Big Data and it's application.

By Okan E

Jul 19, 2020

This course is very informative. The Lecturer explains everything clearly and detailed.

By Modali G K

Jun 06, 2020

really this course was very useful to build my basics of big data and its methodologies


Nov 21, 2019

Perfect for people like me that is not familiar yet with those new technologies.


By Edgar G H

Dec 02, 2018

Great to get a general Idea on what Big Data means and what are the general uses of it.

By Marcos H M C R

Sep 23, 2018

Good course, however, a bit difficult for the ones who are not used to this framewoork.

By Abhijeet K

Jan 28, 2018

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

By Ashish J

Aug 17, 2017

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

By Lokesh J

Jun 22, 2017

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

By Andrew W T

Apr 19, 2017

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