Behavioral and Humanities Data Science (BHD)
BHD 301 Introduction to Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. Three lecture hours a week for one semester.
Grading: Student Option
Repeatable for credit: No
Academic Level: Lower Division
BHD 315 Programming for Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. Only one of the following may be counted: Behavioral and Humanities Data Science 315, Liberal Arts 301L (Topic: Intro Dig Methods Humanities), Rhetoric and Writing 314. Three lecture hours a week for one semester.
Grading: Student Option
Repeatable for credit: No
Academic Level: Lower Division
BHD 319 Gateway to Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. Behavioral and Humanities Data Science 319 and English 310D may not both be counted. Three lecture hours a week for one semester.
Grading: Student Option
Repeatable for credit: No
Academic Level: Lower Division
BHD 119S, 219S, 319S, 419S, 519S, 619S, 719S, 819S, 919S Topics in Behavioral and Humanities Data Science 1-9 Hours
1,2,3,4,5,6,7,8,9 Lecture Hours 0 Lab Hours
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.
Grading: Student Option
Repeatable for credit: May be repeated for credit when the topics vary.
Academic Level: Lower Division
BHD 321 Research Methods for Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. Three lecture hours a week for one semester.
Pre/Corequisites: Behavioral and Humanities Data Science 319.
Grading: Student Option
Repeatable for credit: No
Academic Level: Upper Division
BHD 129S, 229S, 329S, 429S, 529S, 629S, 729S, 829S, 929S Topics in Behavioral and Humanities Data Science 1-9 Hours
1,2,3,4,5,6,7,8,9 Lecture Hours 0 Lab Hours
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.
Grading: Student Option
Repeatable for credit: May be repeated for credit when the topics vary.
Academic Level: Upper Division
BHD 340 Advanced Programming for Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. Three lecture hours a week for one semester.
Pre/Corequisites: Behavioral and Humanities Data Science 315.
Grading: Student Option
Repeatable for credit: No
Academic Level: Upper Division
BHD 145, 345, 445 Topics in Behavioral and Humanities Data Science 1,3,4 Hours
1,3,4 Lecture Hours 0 Lab Hours
For each semester hour of credit earned, the equivalent of one lecture hour a week for one semester.
Pre/Corequisites: Upper-division standing.
Grading: Student Option
Repeatable for credit: May be repeated for credit when the topics vary.
Academic Level: Upper Division
BHD 350 Project Management for Humanities Data Science 3 Hours
3 Lecture Hours 0 Lab Hours
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. The equivalent of three lecture hours a week for one semester.
Pre/Corequisites: Upper-division standing.
Grading: Student Option
Repeatable for credit: No
Academic Level: Upper Division
BHD 360 Conference Course 3 Hours
3 Lecture Hours 0 Lab Hours
The equivalent of three lecture hours a week for one semester.
Pre/Corequisites: Upper-division standing and consent of instructor.
Grading: Letter Grade
Repeatable for credit: Yes (02 times)
Academic Level: Upper Division