Introduction to Infographics and Data Visualization course

In the last few months, I’ve followed an online class called “Introduction to Infographics and Data Visualization” by Alberto Cairo  (Twitter: @acairo) at the Knight Center for Journalism in the Americas.

It was the second edition of the course and I would recommend you to join a future edition if you are interested in the topic. It was mostly targeted for journalists, so there was a lot of content about infographics and lots of examples are visualizations we see in magazines. However, lots of those concepts can still be applied in IT world and there was some good reading provided about designing dashboards. There are lots of examples to explain why some types of data visualization (pie charts, bubble chart on a map) rarely make any sense for the readers. In any way, it was a great introduction to the topic of data visualization. I wasn’t new to the topic because of my experience with Endeca dashboards and Salesforce dashboards but it’s great to leave the technical aspect of those visualizations and focus on what data visualization can actually mean for to the users.

The class didn’t provide training on technical tools, it was really more about learning about the theory behind the topic. The class provided a trial license for Tableau, which is a nice touch, but I haven’t spent time learning on that.

I was initially planning to do all the homeworks related to the course and apply for an official course certificate at the end of the class. However, I quickly fell behind on the weekly schedule they were proposing and did not have enough time to do all that. So I really only focused on learning on the topic based on the content they provide (youtube videos + PDF reading) and did not do any homework. It really reminded me how I do not miss university!


One reply on “Introduction to Infographics and Data Visualization course”

Hey there!

Thanks for this blog post. It saved me from registering to this MOOC.

I thought of responding to this post right on your blog, rather than in an email, so other people can benefit from the discussion..

I also experienced the über-planning on the early days of a MOOC and then just to see myself falling behind. I guess it felt even worst than uni in my case, because you freely chose to get in for your own benefit, so the moment you realize you didn’t do exercices on time, it’s a crappy moment. But the good thing is that MOOCs seem to be very forgiving in the sense that it’s that you bring back in tyour work-life that really counts. Not the 40% pass-rate pdf certificate.. hehe Also, the one I did part so far was giving you a break on the grades for your 2 worst graded exercices, so it was all good in the end.

For the reference, I was(and still am) doing the BerkeleyX ( Stat2X as a refresher on stats. If anyone’s interested, the work load is quite small, but it barely gets you back in the stats bath if you see what I mean. It’s split in 3 courses (5 weeks each):
2.1X on Descriptive Stats (Aced it, lol)
2.2X on Probabilities
2.3X on Inference

The instructor is very clear on the concepts and in her explanations. Very hgh level at times I find, but I guess that’s the key to keep most of the people interested.

I can report later on this new one I registered not so long ago from coursera: Intro to Data Science. Again, by looking at the schedule it seems very high level. But I can be wrong and if it’s the case, I can get myself in a bit of a pickle, as the topics are a bit remote from by comfort zone (MapReduce, Hadoop, databases, algos..). May 1st’s start date is coming fast..

Anyhow, I don’t know if your Tableau license expired, but if it’s not the case, I suggest uo test-drive it a bit further. It’s a really great tool for quick dashboard prototyping or for mission-critical data exploration. You can really save yourself a lot of work/time by visualizing your data with this tool prior to diving full-blast in a project.

My 2 bit-cents: Infographics are getting over-rated and again, the business world is really where it’s at for the long term. You can really get in the crazy analytics there, something journalists will have a tough time trying to do, due to the wide audience they have to please.

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