Good course but need some thing to do:

1. More material. Some topics are just looked superficially.

2. Need provide addition video lessons ore provide information to student that he need know some visualization tool. Excel, Tableau, any thing.

3. There is some errors what still not corrected for many months - in week 4 some video is empty, some misunderstanding information on video slide.

Too much background information, not enough information critical to applicable demands.

The fundamental concept part and assignments are good.

But I think since it is related to visualization, the course can spend more time on how to make a visual.

Very generic ideas, not sure if worth it.

most horrible specialization in coursera! Time wasted

Very nice course. It encourages you to learn different data visualization tools for completing the assignments. And, peer graded assignments are too beneficial since, they give you a sight of how other peers are completing their work and all. Lecture videos too are awesome!!

It's always with Coursera providing amazing courses for students to enhance their skills and adding their part to the success of students in their life's.

This Amazing course data visualization starts from very basic, like which colour our eye attracts more to reaches the top of data visualization topics like visualizing complex network graphics.

Thanks for Coursera for this amazing course.

One of the best courses that i have attended during my entire life. I have worked as BI consultant for 15 years and the contents availed in this course is a must to have for anyone working in BI field. Thanks Illinois University for this amazing course

The lectures introduces various ways of visualizing data.

There are fewer details on Tableau software usage and hand-on network graphing tutorial, students will have to search for more knowledge in these parts during the class.

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.

I found the class to be very informative. The assignments on creating charts and graphs for large data sets were practical and helped me understand the concepts taught in the course.

Really like this course which leads me to Tableau. After the course, I take about 8 hours to learn Tableau and I think my ability of data visualization ballooned.

Before learning any BI tools or Visualization library, this course content needs to be known

seemed to me the best course of the specialization

Very solid data visualization class for people interesting in visualization. It explains a lot of knowledge under the hood. Not that fit for people who just want to learn some tools and quick skills. It is computer science.

Bueno para obtener ideas de que hacer, pero necesitas saber programar a nivel basico

Outdated materials, theory is taught and then praxis is tested. Course needs an update to materials and either teach AND test theory, or teach AND test praxis. I passed this class by switching sessions multiple times in order to use the time to learn the practical skills in data visualization I needed to pass the tests.

Additionally, the presented materials and the lecture format are very uninspiring.

too theoretical without enough practical quiz and assignment

waste

Professor has a soft, easy to follow teaching style but the course structure has several pitfalls:

It gets too theoretical in week 3 and 4 and you really don't need complex algebra or statistics to pass the course but it'd be hard to understand the core matters without them. Week 4's assignment is only a quiz and I think there should have been a project to really test student's ability to apply the learned materials in real situations. Besides, you don't need programming skill to complete the assignments, but it takes a lot of time to learn free, ready-made datavis tools and they are too limited to deliver the outcomes we want.

I think if anyone is serious about learning data visualization, you can't get away with not knowing programming and statistics and those two should be prerequisites.

The course introduces one to more parameters and considerations to account for when building data visualizations than they would probably imagine. From human perception of visuals to 2-D and 3-D rendering to ideal plots for different series of data, the course covers a lot of ground and introduces some very interesting concepts. The programming assignments don't really require programming knowledge if you are able to generate graphs using off the shelf tools. One thing to keep in mind is that although the course suggests you can build a web site or page with your visualizations if desired, the assignment submissions do not allow for the submission of a URL link to a website or a page. Links can however be embedded into additional comments associated with the submission.

Pros:

The course was well organized so that an individual can focus on coursework only. There is enough time to complete the homework and quizzes directly relate to the material (i.e. student is not expected to do much reading outside the course videos). The material is informative and accomplishes the goals stated in the beginning of the course.

Cons:

Some minor things such as not being able to see the programming assignments very well when grading other's work due to Coursera's UI not designed well for that. Also, the collaboration between students is not as good as it was made out to be based on the emphasis that was given to that by Coursera and course organizers. Not sure if Coursera or organizers can do much more than they have already regarding that.

Amazingly informative and instructive course. Recommended for beginners, but much highly recommended for people who are already conceptually aware of these things/who're in the line of application of these concepts but need a firmer grasp on the theory and concepts behind depicting data points through a visualization to better architect their implementations. I am one of the latter category, and I've found this course extremely useful in aligning my thoughts and tasks in the right direction :)

Earth temperature is good assignment to apply the data vis knowledge, as the dataset not overcomplicated but also not trival, and during its peer grading, there are different type of solutions from different learners. Peer grading is thus important part of this course because the grader need to apply data vis knowledge with critical thinking to judge various solutions, in term of different design tradeoff.

Para una persona que no tiene idea sobre conceptos básicos de ingenieria y estadística en curso puede resultar un poco dificil, más no imposible de aprobar. Tiene contenidos muy interesantes, sobre todo en sus dos primeras semanas de estudio. La tercera y cuarta semana para mi representaron un reto y una exploración interesante que me hacen sentir satisfecha por haber logrado terminarlo.