Introduction to core concepts, methods, and tools in data science from a liberal arts perspective with an emphasis on both technical skill-building and critical reflection. Discuss data ethics, machine learning, archival processing, and the cultural contexts of computational research.

Introduction to computer programming for the humanities and to digital humanities as a research area. Examine basic programming concepts, data types, functions, and Application Programming Interfaces (API). Learn the first steps in building data pipelines and explore introductory natural language processing (NLP) techniques through humanities-centered applications.

Introduction to digital humanities research. Examine how data, algorithms, Machine Learning/Artificial Intelligence, and interpretation shape cultural inquiry in the humanities through hands-on experimentation and critical tinkering using computer programming. Utilize exercises in artifact, text, image, and metadata analysis.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the College of Liberal Arts. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

Explore approaches to research design in humanities data science with an emphasis on mixed methods, critical and theoretical connections between data science and humanities research programs, ethical frameworks, and the formulation of research questions within specific cultural, disciplinary, and cross-sectoral professional contexts.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the College of Liberal Arts. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

Focus on building and refining custom data pipelines and applications in a self-guided research project. Discuss research and data flow planning, critical evaluation, Natural Language Processing (NLP) and computational cultural artifact analysis, including archive processing. Explore modular programming, adapting tools for humanities-specific use cases, and interface design.

Introduction to strategies for managing digital humanities projects from research design and planning to deployment. Discuss team collaboration, corpus and artifact curation, Institutional Review Board (IRB) protocols and legal questions, documentation practices, and navigating the institutional, ethical, and technical dimensions of humanities data science research.