good

E

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.

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

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.

Durante os dois trabalhos a serem entregues o auxilio a pessoas que não possuem conhecimentos prévios não é conduzido de modo razoável. É necessário que essa pessoa procure programas sozinhos, uma vez que os fornecidos são muito antigos e não possuem tutoriais nem dentro ou fora do coursera.

Entretanto o curso atendeu razoavelmente as minhas expectativas, ele é um pouco mais abrangente e superficial do que eu esperava.

I consider the assignment is not very useful. Network plot usually does not help much if you are researching dataset. Scatterplot, histogram can be much useful. Tableau? Sorry, can't afford it, why not excel? At least, almost anyone uses it. Not very practical one, but it does contains a lot of information in the course.

I expected a more advanced course. Although there were interesting points, they were treated very superficially. The last week gave principles regarding dashboards, but there is an important difference between treating dashboard principles and actually doing a dashboard.

There was too little or almost no help (tutorials, etc) on tools for graph visualization prior to assignment 2. I had already done a course on graph analytics and it was too better on this.

Could have a more practical activity to create a dashboard and assignment 2 did not provide appropriate tools and data sets to easily to do the assignment

Very useful course for beginners.

Pdf of the slides not available

Low interaction with other students, mentor answering the forum a bit bizarre

Need to add more materials about software to be used. I used Python libraries, otherwise, I would not able to complete the course.

the content of week 1 seems really long and redundant to me. feels like the course can be shortened and more down-to-the-point.

I chose the "Data Mining" specialization to learn more about data mining ;-)

I'm not so interested to present data

el idioma dificulta entender al orador, mucha informacion y poca practica y poco acompañamiento en la practica.

There should have been more focus on the plotting tools. The theory portion is informative.

Peer review is not effective at all

I think that is very basic.

It's not necessary for me

Not much in it.

Very Shallow

Nice course

有点水

The course material is inherently interesting, but the videos are not very engaging. The presentation is quite monotonous and the wording / phrasing is confusing to follow. I'd suggest preparing a new set of script that explains the concepts and clarifies the details while cutting out *very* generic pronouns like "this node" or "that thing" or vague acronyms

Too basic.