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.

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!!

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.

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.

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.

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.

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

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 :)

Very nice overview for the subject. Great introduction that focuses for every kind of professional interested in data visualization (eg.: programmers and designers, analysts and decision makers). I really appreciate the projects and the peer-review model. It was an amazing challenge and I definitely will take the sequence of Data Visualization courses. Thanks Coursera :)

My name is Jose Antonio. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors.

Regards.

Jose Antonio.

Very interesting course that shows you how to present your data set in a way that you can actually deduce what is going on in one look.I like how Professor John C. Hart had shared with us that we are building Data Visualization Charts eventually for Human Audience, thus, a little bit understanding about the human eyes, ears, brain is good.

I really liked this course on Data Visualization,and Prof Hart is a wonderful instructor. the course is very interesting and sets one's basics right .The assignments were very interesting, but I don't fully agree with the system of peer graded assignment. would be better if some teacher graded us.

A really helpful primer. I lays out a broad map of the concepts that inform the craft of data visualization and provides a basic set of examples and exercises. It's up to the student to take this map and really explore each if s/he hopes to master the subject. Thank you, Professor Hart!

I really enjoyed this course. It is a very good source for learning how to represent numerical and relational data in a way that conveys information effectively. I also used this course as a platform to learn javascript in order to solve the assignments using the amazing library D3.js.

I really enjoyed this course. It gives very insights on useful knowledge, and opens the door to dig deeper into more specific knowledge, but is also possible to understand the concepts and succeed on the assignments without deep previous knowledge on programming or linear algebra.

Wonderful course! Open a new window to me. Appreciate it professor Hart.

This course helps me a lot. I first heard there are so many things to think over considering data visualization. From human to computer, numerical to non-numerical, biology to aesthetics, chart to graph.

I started this training with great anticipation by the central theme (Data Mining) and was surprised with an excellent training on data visualization. The richness of detail and material supply should inspire other training also the Coursera I have accomplished.

Really nice course, finally got a chance to dig into some big datasets and see for myself what kind of challenges arise by trying to communicate information to users. I found it to be very useful first step toward getting deeper understanding on data mining.