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Course Description
Introduction to Deep Learning concepts and applications development techniques required to develop Deep Learning based solutions. Hands-on experience developing models using open-source frameworks and packagesThis course equips students with the skills and knowledge needed to design, deploy, and evaluate interactive dashboards, and use them to generate actionable insight. Students will not only deepen their understanding of effective data visualization but will also learn the foundational principles of combining multiple visualizations into a cohesive and coherent whole. These principles are informed by human-centered design, cognitive science, and perceptual psychology, and include concepts such as dynamic filtering and hierarchical data handling. The course will introduce R Shiny,IBM Watson Studio, and Tableau, then student groups will build a comprehensive dashboard with real world data.
Credit(s)
3.0
Professor of Record
Jeff Hemsley
Audience
Students interested in project management profession and supporting frameworks. data analytics and data science, with a focus on data/information visualization.
Learning Objectives
After taking this course, students will be able to:
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Document, analyze and translate data analytics needs into technical designs and solutions.
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- Build advanced dashboards, using high level tools such as Tableau and more customizable programming solutions such as Shiny (in R).
- Integrate machine learning techniques with interactive visualizations to generate enhanced actionable insight.
- Use dashboards to explore large datasets to find the story in the data.
- Use visualization to explore and explain fairness and bias of potential analytical approaches.
Course Syllabus
IST 700 Fall 2021 Syllabus- Jeff Hemsley
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