INTENSIVE I: Introduction to Information Visualization - Three (3) Credits
Given that not all students enter the program with a comprehensive understanding of information visualization this course will provide a basic introduction of the relevant concepts, issues and practices in this diverse field. Topics covered will include a brief history of data / information visualization; principles of visual literacy; an overview of contemporary systems and techniques used in information visualization; common applications of information visualization; and considerations in analyzing and evaluating applications in information visualization.
Visual Cognition and Perception - Two (2) Credits
This course focuses on introducing students to the science of visual cognition and perception as it relates to information visualization. Focusing on the ways in which the mind acquires, stores, and uses information through vision, the course will give students a working knowledge of how visual information is acquired and processed so as to enable them to develop more compelling and accessible information visualization applications.
Statistics and Multivariate Data Analysis for Information Visualization - Two (2) Credits
This course will introduce students to concepts and methods in statistics and multivariate data analysis that are central to and commonly employed in information visualization. Topics will include data aggregation, descriptive statistics, grouping methods, data mining, and predictive models.
Contexts of Information Visualization I - Two (2) Credits
This course focuses on providing students with a critical background in the historical, cultural, social, economic and political contexts of visualizations and information access. In addition to perspectives and research from the fields of art history, art theory, studies of visual culture, the course will also draw on relevant ideas from the histories of science and technology and science and technology studies to illuminate the complex contexts within which information continues to be visualized.
Statistics and Multivariate Data Analysis for Information Visualization - Part 2 - Two (2) Credits
This course will build on the concepts and methods presented in Part 1. Topics will include industry-specific information and data analysis, using statistics and multivariate data analysis to establish and/or understand relationships between variables, and how to begin transforming information and data into visualizations.
Visual Analytics - Three (3) Credits
Drawing on cognitive science, machine-based decision and learning systems, usability design, human computer interaction and data mining and analysis, this course will introduce students to the principles and techniques of the growing field of visual analytics that involves the synthesis of large amounts of dynamic multivariate data to make it accessible and easy to analyze through the use of interactive visual interfaces.
Principles of Visual Interface Design - Three (3) Credits
Focusing on the challenges of designing visual interfaces that support access and analysis of large multivariate data sets, this course will introduce students to the theories and issues in visual interface design. Topics will include user-centered design, human-computer interaction, graphical user interfaces and adaptive design. Students will be required to identify and critique different visual interface design solutions.
Information Design- Four (4) Credits
This course explores the theoretical issues related to the design and presentation of complex and multivariate information. Students will learn design elements related to presenting information including design theory, aesthetics, visual rhetoric and principles of visual communication. Students will be required to identify and critique case studies in information design.
Information Visualization Applications - Three (3) Credits
As the students will be actively working on identifying and developing their own information visualization projects, this course will provide an overview of a range of information visualization applications through case studies to analyze and critique in ways that will inform their own projects. Case studies of applications in geospatial, business, strategy and planning, social networks, public health, homeland security, etc. will be examined.
Information Visualization Project - Three (3) Credits
Working closely with an assigned advisor from a relevant industry or field in which the student has chosen to develop their information visualization application, the students will be provided with continuous guidance and critique of their project as it develops.