Data Visualization, SMM635 ― README
This is the GitHub repository for the course Data Visualization, SMM635. The repo is alive and will be updated throughout the term.
Why a Data Visualization Course?
This module is a journey into the art and science of creating memorable charts, which grab the attention of the audience and successfully convey insights and narratives. Pleasant journeys require good companions: infographic --- i.e., the field that investigates the representation of information, data, and knowledge --- will offer the theoretical platform for the module; Python will make things happen (at least on our screen). Consistently with the teaching philosophy of the module leader, each lecture integrates theory and practice.
Learning Objectives
In terms of learning objectives, by the end of the module, students should be able to:
- Generate and evaluate visual forms for appropriateness, context, and meaning;
- Design and execute statistical charts with a particular emphasis on massive datasets;
- Design and execute multidimensional visualizations involving temporal and geo-spatial dimensions;
- Design and execute interactive visualizations;
- Leverage the visualization capabilities of best in class Python modules, namely, Matplotlib and Plotly, and specialized software such as Tableau and Tikz/PGF.