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Learner Reviews & Feedback for Graph Analytics for Big Data by University of California San Diego

4.3
stars
1,118 ratings
214 reviews

About the Course

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects....

Top reviews

KM
Dec 16, 2017

Got an amazing introduction to Graph Analytics in Big Data. Technical issues with Neo4J made this course a little more challenging than necessary. But the introduction to Spark GraphX was invaluable.

JT
Oct 25, 2016

This course was excellent as an introduction to Graph Analytics and using Neo4j. Not only did I learn a lot, I've been given tasks related to what I've learned in this course after finishing it.

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126 - 150 of 213 Reviews for Graph Analytics for Big Data

By Anthony W U

Mar 22, 2017

Displaying handson queries graphically would make it more appealing as it was in Neo4j

By Gabriel T

Feb 9, 2018

Very sound course with lots of information to digest. Just enough for "lift-off".

By Petch C

Apr 21, 2020

hand on is quite hard and need a lot of installation such as cloudera.

By Kun Z

May 10, 2017

Very good project! Hopefully it will be helpful in my future career!

By Efendi

May 22, 2017

Suggest to remove the peer-grade assessment as it could be bias :)

By Anant K

Feb 7, 2019

Can be improved further by including rigorous Hands-on exercises

By Adam G

Dec 21, 2018

Within the usual pedagogical standards, it is a very good course

By Prospero-Martin R

Aug 31, 2018

I really enjoyed learning graph analytics, great course!

By Juan J R M

Aug 26, 2017

It's really long and we need more practical examples

By Mihai-Bogdan Z

Sep 2, 2020

Things made a bit too complicated sometimes.

By Marwa K E

Oct 6, 2020

Week 5 materials are not well prepared.

By Miguel A R S

Dec 5, 2017

This is a great introductory course.

By Rüdiger S

Nov 1, 2020

Liked the hands-on neo4j part most.

By Amir A

Feb 9, 2017

Thanks so much

you are great people

By Fernando M

Jun 30, 2016

interesting practices with neo4j

By Mehul P

Dec 30, 2017

Nice overview to get into it.

By Seth D

Sep 9, 2016

best course of the series

By Congcong Z

Dec 5, 2017

well explained

By Liliana d C C M

Nov 11, 2019

buen curso

By Qian H

Jul 31, 2017

Not bad

By Bahaa E A E

Jun 27, 2018

Thanks

By Rohit K S

Oct 13, 2020

Good!

By AGARAOLI A

Feb 10, 2017

-

By Brittany

Jul 9, 2018

The course theory was illustrated and demonstrated very well. Examples were shown and the lectures were short but concise. I appreciated this greatly. The professor also spoke very slowly and deliberately, so the viewers could understand and have time to let the information sink in. In contrast, although the guest lecturer for Neo4j was great, the material was not up-to-date and caused several issues in completing the assignment. Other students were able to lead the class in the right direction in order to even start the assignment. The GraphX on Cloudera virtual machine was almost impossible to replicate as well due to the material being so outdated. Week 5 of the course peaked my interest but lacked the resources to completely follow the instructions and understand the material that was being presented.

By Stephane T

Mar 7, 2017

I would have liked to put 5 stars. This topic is so important and relevant to big data. After week 4 hands on part, it became obvious we will not see how to implement or interpret the more abstract graph concepts presented in week 3. That was very disappointing.

Moreover, the structure of the course is not as good as the other module. I don't understand the lack of balance between theory and hands on (Not enough hands on to reflect the theory) part.

On a constructive note, I would replace some of the theoretical concepts of week 3 with additional information on how to link a graph database to machine learning OR I would add more hands on exercise to help using those more complex concepts and learn how to interpret them.