Information Visualization: Advanced Techniques
Created by: Enrico Bertini
Course Description
Instructor Details
- 5.0 Rating
7 Reviews
Enrico Bertini
Enrico Bertini is Associate Professors in the Computer Science and Engineering department at NYU Tandon School of Engineering. He has taught courses on visualization and visual analytics for more than 10 years in public and private institutions across Europe and the United States. Prof. Bertini's research focuses on the development and evaluation of advanced visual interfaces for Data Science. He has numerous publications top visualization conferences and journals and he is the recipient of several awards for his research. He is also the co-host of Data Stories, a popular podcast on data and data visualization.
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Reviews
By Arantxa M P on 26-Oct-19
VEry interesting. I wasn't a newbie but faced very interesting challenges, expecially facing D3.js
By Balakumar K S on 26-Sep-19
A good introduction course!
By Camara L D on 10-Sep-19
The best course about information visualization !
By Aishwarya M on 9-Sep-19
great course. helped me understand the concepts involved in a 'scientific' rather than 'art'.
By Priyansh B on 6-Jul-19
I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand
By Nabil A on 11-Jun-19
Last course on the Specialization. It cover advanced graphics and visualizations, such as visualizing geographical data, temporal data, network data and interactive visualizations with multiple views. What I liked the most is the vast quantity of examples reviewed and the assignments which consisted of producing your very own low fidelity sketches of the topics given in each week.I would totally recomend to anyone who wants to dive deep in data visualization techniques and expand visual vocabulary.
By vignaux on 15-Nov-18
Excellent course; the topics discussed here are essential for learning about complex / multi-faceted data visualisations.
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Quality Score
Overall Score : 100 / 100








