I have designed a new course in visual analytics that I am teaching this spring 2022 at Ohio University. The visual analytics hands-on course trains students to work on interactive visual interfaces that support analytical reasoning and reveal vital actionable insights. This course introduces students to concepts, tools, and best practices in visual analytics as they examine and uncover hidden opportunities deep within big data. Interactive visual representations are integrated within underlying analytical processes, including descriptive and predictive analytics, to facilitate high-level data-driven decision-making. Based on readings, cases studies, tutorials, and analytics assignments, course emphasis is on providing a thorough understanding of visual analytics tools. Students learn to go beyond charts and graphs to create multi-dimensional exploratory views of data. The aim is to equip students to think like data analysts equipped with the knowledge and understanding of visual analytics principles, creating effective dashboards and visual analytics solutions using Tableau.
Learning outcomes
Students fully engaging with this class and completing all the assignments successfully will, as a minimum be able to:
- Access and connect data to support high-quality analyses.
- Visually transform data to support assessment, planning, and decision-making.
- Create, analyze, and evaluate representations of dynamic data in dashboards.
- Demonstrate the recognition of patterns within data through perceptual inference of relationships.
- Identify patterns of predictive analytics in the appropriate contexts.
You can access the syllabus of the Visual Analytics course in pdf format here: syllabus
Laeeq Khan, Ph.D. 