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Отзывы учащихся о курсе Graph Analytics for Big Data от партнера Калифорнийский университет в Сан-Диего

4.3
звезд
Оценки: 1,094
Рецензии: 209

О курсе

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....

Лучшие рецензии

KM

Dec 17, 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 26, 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.

Фильтр по:

126–150 из 208 отзывов о курсе Graph Analytics for Big Data

автор: Petch C

Apr 21, 2020

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

автор: Kun Z

May 10, 2017

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

автор: Efendi

May 22, 2017

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

автор: Anant K

Feb 07, 2019

Can be improved further by including rigorous Hands-on exercises

автор: Adam G

Dec 21, 2018

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

автор: Prospero-Martin R

Sep 01, 2018

I really enjoyed learning graph analytics, great course!

автор: Juan J R M

Aug 26, 2017

It's really long and we need more practical examples

автор: Mihai-Bogdan Z

Sep 02, 2020

Things made a bit too complicated sometimes.

автор: Marwa K E

Oct 06, 2020

Week 5 materials are not well prepared.

автор: Miguel A R S

Dec 05, 2017

This is a great introductory course.

автор: Amir A

Feb 09, 2017

Thanks so much

you are great people

автор: Fernando M

Jun 30, 2016

interesting practices with neo4j

автор: Mehul P

Dec 31, 2017

Nice overview to get into it.

автор: Seth D

Sep 09, 2016

best course of the series

автор: Congcong Z

Dec 05, 2017

well explained

автор: Liliana d C C M

Nov 11, 2019

buen curso

автор: Qian H

Jul 31, 2017

Not bad

автор: Bahaa E A E

Jun 27, 2018

Thanks

автор: Rohit K S

Oct 13, 2020

Good!

автор: AGARAOLI A

Feb 10, 2017

-

автор: Brittany

Jul 09, 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.

автор: Stephane T

Mar 07, 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.

автор: Dag S

Oct 12, 2016

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.

автор: Carlos M

Oct 08, 2019

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.

автор: Marcel V N

Jan 16, 2017

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.