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Opiniones y comentarios de aprendices correspondientes a Visualización de datos por parte de Universidad de Illinois en Urbana-Champaign

4.5
estrellas
1,246 calificaciones
281 reseña

Acerca del Curso

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns....

Principales reseñas

MK
5 de abr. de 2018

Good course, very well structured and with interesting assignments. Some (especially first) lessons are more of a general culture but most are very helpful and allow to learn a lot of things.

GC
16 de nov. de 2020

Very useful course. It enlightens my ways to data visualization. I knew some concepts, but in a disorganized way and not knowing how. This course fills these gaps. It is tremendously helpful.

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226 - 250 de 278 revisiones para Visualización de datos

por Jason M H

5 de nov. de 2016

the third week requires learning a software package.

por AJETUNMOBI O

1 de may. de 2017

Breaks down all complexity in Data Visualisation

por To P H

2 de may. de 2019

Some interesting visualization concepts

por Yongyi Z

13 de jun. de 2018

Learning curve is too steep in week 3.

por Zheyan S

17 de jun. de 2016

Quite clear, good for introduction

por Suketu B

27 de ene. de 2018

Good intro to data visualization.

por Hyun J L

30 de may. de 2017

Was fun, and informative indeed!

por Augusto R G

7 de jul. de 2019

Great course, very good format!

por Alec M

10 de mar. de 2017

I wish for more hands on work.

por Liu S

16 de ago. de 2018

Maybe more practical skills.

por Walter F G

6 de jul. de 2020

Good introductory course.

por Mark T

23 de sep. de 2017

Deep and rich content.

por Jason M

5 de jul. de 2017

Great overview!

por Narasimharao M

4 de may. de 2020

good knowledge

por Yuexin ( C

28 de may. de 2020

great course!

por Klent A

28 de ago. de 2016

Great class

por TerryTang

7 de jun. de 2016

good!

por PALAKONDA A

23 de abr. de 2021

good

por DORRIN U D G

14 de sep. de 2020

Good

por SURAJ P

30 de jul. de 2020

good

por Sudhanshu R

14 de jun. de 2020

good

por Deepak S

2 de ago. de 2016

E

por Amit S

14 de oct. de 2017

The Data Visualization course gives insight of the various methods that can be used for visualizing different forms of data and also explains how data is perceived differently by human and computers. This course lacks the utilization of different data visualization tools and techniques which can be used.

In my view, different visualization techniques based on few tools and the way to use those tools should be added in this course which will make it more practical way of understanding Data Visualization.

por PhilTheShill

25 de ago. de 2016

I thought at times the explanations were a bit concise. If I look at the process mining course for example, a lot more video material is included (and its price is lower) with more concrete examples and practice. For non programmers it is not evident to find a solution to some of the assignments and there isn't much guidance on how to use certain tools. therefore, the time to be invested for non programmers - especially in week 3 - is far more than the hou

por Vivek V

29 de oct. de 2016

The course is awsome to get motivation and quite informative. However it teaches lot of practical concepts using Tableau which is a commercial software.

Since these concepts entirely new to me. It take me a lot of time to understand videos and still I'm afraid I'll forget the things as soon as I leave it. I think some more practical activities should be introduce (on free platforms), to make knowledge more sustainable.