Data Visualization TMUL 4317

Course description:

Data visualization is a ?eld of growing importance that combines background expertise in computer graphics, scienti?c computing, data mining, and image processing. It couples these ?elds with artistic, psychological, perceptual, and interactivity concerns. The techniques learned in this class are broadly applicable to all ?elds in engineering and science, where the explosion of data we are now able to generate demands e?ective presentation and analysis. This course will cover basic topics of data visualization techniques for multiple data types, manipulation data to describe it in more meaningful ways, and cover data processing techniques.
The Lab introduces data visualization including both the principles and techniques. Students will learn the value of visualization, specific techniques in information visualization and scientific visualization, and how understand how to best leverage visualization methods. The lab lectures addresses four major topics : Acquiring data and using datasets, analysis and parsing data using Processing toolkits, Visualizing data using Processing toolkits, Implementation Dashboards.

Course Aims:

This course aims to enable the student to:
  • Know the basics of data visualization.
  • Understand the importance of data visualization and the design and use of many visual components.
  • Learn to wisely use various visualization structures such as tables, spatial data, time-varying data, tree and network, etc.
  • Learn the basics of colors, views, and other popular and important visualization-based issues.
  • Learn basic algorithms in data visualization.
  • Understand the techniques for multiple data types.
  • Understand why visualization is an important part of data analysis.

Course outcomes:

Upon completion of the course, students should be able to:
  • Understand the role of visualization in the processing and analysis of data coming from a broad range of sources. 
  • Develop software and tools to create visualizations of data that are e?ective for analysis.
  • Be familiar with the cutting edge research ideas in the ?eld of visualization.
  • Undertake creative work and perform research involving visualization topics.