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Graph Analytics for Big Data に戻る

カリフォルニア大学サンディエゴ校 による Graph Analytics for Big Data の受講者のレビューおよびフィードバック



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....




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.



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.


Graph Analytics for Big Data: 151 - 175 / 232 レビュー

by Mihai-Bogdan Z


Things made a bit too complicated sometimes.

by Marwa K E


Week 5 materials are not well prepared.

by Miguel A R S


This is a great introductory course.

by Rüdiger S


Liked the hands-on neo4j part most.

by Amir A


Thanks so much

you are great people

by Fernando M


interesting practices with neo4j

by Rudransh P


H​ands-on exercises help a lot!

by Mehul P


Nice overview to get into it.

by Seth D


best course of the series

by Nicolas G


more practicing

by Congcong Z


well explained

by Liliana d C C M


buen curso

by Qian H


Not bad

by Bahaa E A E



by Rohit K S



by Agaraoli A



by Ben


It's not fantastic. It's a concise introduction to computational graph concepts, with a lot of time spent discussing the implementation of specific algorithms for implementing graph search considering hardware. There is little in the way of applying the algorithms using modern popular graph software.

The final week has some simple walk throughs using some data, but this seems quite old and there is no provision available to be able to attempt it yourself. I did not get much of an impression of a coherent plan for the course either besides introduce some concepts, but it is a relatively small time commitment for an initial introduction. All of the time spent looking at scala code or how to write a graph search algorithm from scratch and designing a data structure might be your bag, but it is not what I would look for in a modern graph data science course. Better graph network courses exist - neo4j is quite mature now and has extensive resources. Saying that, they do introduce the key concepts and some graph analytical ideas to help the user begin to think more graphically.

by Brittany


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


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.

by Dag S


The professor is well spoken and the class started out very well. But by the final section the hands on example were simply cut-paste with no explanation of what we were doing or how it worked. It's not the fault of the professor but this course and the Big Data specialization attempts to cover too much information. Graph Analytics should be its own 6 course specialization. But really, to understand graph analytics one should be spending a great deal of time with the subject. Perhaps online courses are not the way to understand such a complex subject.

by Cecilie L


Fine content overall, but there were a lot of problems with links and hands-on exercises. Often, the links in quizzes did not work. Week 5 was centered around being able to use Cloudera Quick Start VM. This is no longer available, so I was not able to do the exercises, making week 5 of the course terrible. In week 4, a lot of the example code was not up-to-date, so the code required modifications to work - some parts more than others.

Otherwise, I liked the structure and the topics, but you should update the technical contents more often.

by Carlos M


Unfortunately the videos and lectures about Neo4j installation is not up to date making it difficult to install by the learner. Mostly if you take into account that not all the students have the technical background to do it. On the other hand, after installation Neo4j was returning an error that don't let complete the labs. Regardless these issues, all the other course content is really helpful to get a high level understanding of how Graph Analytics can be used in a Big Data ecosystem.

by Nguemaha M


Probably because I'm new to all the big data and graph analytics terminologies but the lectures in this chapter were quite difficult to follow in my opinion. The instructor was just talking, not teaching nor explaining, just like someone who prepares notes and is reading to students. The hand-ons were a bit helpful, but overall this class is more for those who already know about the subject.

by Priyadarshi V


A lot of online resources have changed over the years like the way to download and work on Neo4j. But the video lesson is not reflecting the change. If not for the learner's community support I would not have been able to complete this course. I would urge the mentors to keep updating the course materials from time to time and post the changes in forums.

by Jyothi-Raghav J


Except for the Neo4j week 4 and week 2, the other weeks were really confusing as it was hard to follow where the instructor is on a slide. Week 5 hands-on videos really were too fast and the instructor in video hands-on seems to be in a hurry. I also had hard time copy pasting the code snippets from the hands-on material.