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

4.6
stars
10,975 ratings

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

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.

JT

Aug 30, 2016

This is a great introduction for Big Data. It helps me to revisit what I learned from the meetups and webinars, then put the fundamental knowledge and information in a solid foundation. Thank you.

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2276 - 2300 of 2,499 Reviews for Introduction to Big Data

By Deleted A

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Jan 18, 2023

Helpful

By NEELJI P

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Aug 22, 2018

nothing

By Sheraz I

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Jul 4, 2020

v.good

By Albouchi A

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Aug 5, 2021

merci

By Rishabh T

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Jul 3, 2020

great

By PARVADHARSHINI K

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May 18, 2020

Great

By SATYAPRAKASH R

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Jan 7, 2025

good

By Jatin t

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Nov 14, 2024

good

By Ilboudo W E

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Sep 6, 2024

Good

By Garvit T

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Sep 15, 2021

good

By VEDIKOLA R R

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Oct 12, 2020

Good

By SATHYASRI V

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Aug 5, 2020

Good

By Arihant S J

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Jun 18, 2020

Good

By Sumit K

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Jun 18, 2020

good

By Tejal C

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Jun 9, 2020

Good

By Chirag P

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May 15, 2020

Good

By SUTHAHAR P

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May 13, 2020

Good

By Hyungje W

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Oct 31, 2018

Good

By Mahmoud T

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Jul 6, 2017

good

By Sweta c

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Aug 27, 2020

ok

By Rosaline P

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Mar 3, 2025

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By Kirk S

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May 5, 2018

Quizzes appear to have been written by someone who simply went through the videos and slides and looked for things for the student could parrot back rather than by someone who was asking questions based on understanding of the material.

Videos is not a great medium for this kind of thing. It is slow and hard to review. I understand the desire to replicate a classroom experience, but without the ability to interrupt and ask a question, that isn't what you are creating. The transcript system is quite helpful in this regard, but really, if you just gave me a short text to read that clearly stated the things discussed in the video it would be more efficient.

By Michael L

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Feb 28, 2020

The course is gives a good overview on big data as a topic. I personnally found the questions in the reviews sometimes arbitrary. I would have liked more implementation and a bit more technical flavour. At the same time the technical infrastructure (Cloudera virtual Machine) needs to be updated. It is bit messy working on a machine with such a bad screen resolution. E.g.: Unfortunately, installing the guest additions affects the functionality of haddop on the virtual machine. Thus, in the practical part one bothers more with technical issues than the actual implementation.

By Zsolt B

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Sep 5, 2016

The content of the course is alright and up to date. The instructors are also good, passionate and has a great knowledge.

What brings everything down is the video editing and the slide design/quality. They are terrible and clearly not in the field of profession of the creators.

All in all, it is an average course, but I can recommend it to anyone interesting in the topic, because it does its job. If someone could improve the slides and the video editing could reach the youtube video reviewer/critic level, it could easily do a 4 out of 5.

By Juan P

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Jul 16, 2016

This is an introduction course, and no advanced concepts are seen. I think it provides a good background, that is all. If you have a solid technical (programming, databases, etc.) knowledge maybe you will miss more hand-ons. For me, for an introductory and theoretical course I expected more resources, for example additional suggested readings, optional exercises...

Lectures are well structured (intro and summary at the end), but I have missed presentations from some of the most interesting videos (week 6).