iSchool @ UW

This special topic course will delve into the opportunities and challenges associated with generative AI systems. Generative AI systems have been rapidly proliferating and are widely used by laypeople, students, researchers, and developers. While they offer practical human-AI interaction settings, their impact on society remains poorly understood. We will explore how to responsibly use, develop, and deploy generative AI systems while also raising awareness about the numerous open questions that are critically important to the sciences and society.

Special topics for iSchool undergrad major and minor, MSIM, MLIS, and PhD.

Course website: TBA

Introduces techniques and theory for designing, developing, and evaluating interactive visualizations of structured data such as numbers, text, and relationships. Emphasizes a human-centered approach grounded in cognitive science, perceptual psychology, and visual analytics. Students gain practical experience building web-based visualizations, with attention to usability, accessibility, and empirical evaluation. Topics include visual perception, visual encoding, prototyping, and interaction design.

Prerequisite: INFO 340 or CSE 154; CSE 123, CSE 143, or CSE 163; and either QMETH 201, Q SCI 381, STAT 220, STAT 221/CS&SS 221/SOC 221, STAT 290, STAT 311, or STAT 390.

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Introduction to database systems, focused on relational models, languages, and systems and the application of conceptual, logical, and physical database design. Key topics include the relational model, SQL, entity-relationship modeling, three-tier architectures, implementation of database applications, and non-relational databases. Links data modeling decisions to social justice outcomes.

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Introduction to data justice. Addresses historical and contemporary problems of injustice and inequality linked to data, statistics, and computation. Situates topics within broader theories of justice, in particular gender, racial, and socioeconomic justice. Covers core issues, including: data discrimination and violence; statistics, norms, and governmentality; surveillance and data capitalism.

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Introduction to human-centered design, development, and evaluation of data visualizations. Coursework focuses on techniques for designing and coding visualizations of structured data, including evaluating usability and accessibility. Topics include principles of visual perception; fundamentals of visual analytics; technical dimensions of visual encoding; prototyping; and usability testing.

Course website: TBA