Information Visualization: Advanced Techniques

This is the last course of the excellent Information Visualization Specialisation.
The four weeks of this course cover advanced techniques on a specific topic every week: visualizing geographical data, visualizing network data, visualizing temporal data, and interaction with multiple views.
It continues at the same level of scientific and structured approach with the right balance of practical examples, just as in the earlier courses.

Contrary to the previous courses in this series you have peer-reviewed assignments every week instead of only once. These assignments are among the best I've seen in MOOCs.
After doing exercises with tableau, colour picking apps, and d3js programming in the previous courses, you design advanced graphs using low-fidelity sketches in this last course. These low-fidelity sketches allow you to experiment a lot, try lots of designs before choosing the right one to submit. As usual with this kind of assignments, you will learn a lot from the comments of your peers, from the example solutions and from the solutions from other students. Plenties of opportunities to reflect on the course material and deliberately practice. Far more interesting than the multiple choice quizzes you get in many other courses (this course has no multiple-choice quizzes). I hope that this specialization will attract many more students in the future. So far your work is only reviewed by one student and you also review one other student, most probably because there are not yet enough students on the course to get multiple reviews. In the earlier days when MOOCs were still massive assessments were reviewed by up to 5 other students.

This specialization provides you with the necessary skills to develop advanced web-based applications for visual data analysis. There is not enough time to implement your advanced designs of this last course, but with the skills you build in the previous d3js programming course, you should be able to do so.

After finishing this specialization you are prepared to work on complex data science projects that require the development of interactive visual interfaces for data analysis.