All core courses are offered in Session A (May 26 - July 2, 2026)
Required Core Course
DigHum 100 - Theory and Methods in the Digital Humanities
In this course, we evaluate a variety of digital humanities projects through theoretical scholarship in the field to critically assess the kinds of knowledge these methods produce—and what they leave out. We weigh digital approaches in relation to traditional humanities methods, with attention to interpretation, evidence, and argument.
We also examine how contemporary platforms, algorithms, and generative AI reshape humanities work (e.g., authorship, authority, provenance, bias, and scale). The course prepares students to apply digital methods in ethical, reflective, and responsible ways—understanding both the potential and the limits of computation within the humanities.
Required Core Course
DigHum 101 - Python Programming for Digital Humanities
This hands-on course introduces foundational approaches in data science through a digital humanities lens, emphasizing practical application and reproducible workflows. Students gain proficiency in Python programming in Jupyter Notebooks, using key data science libraries such as Pandas.
Using real datasets, we explore web scraping, social network analysis, computational text analysis, and introductory machine learning. We also discuss how to work responsibly with contemporary AI tools in research settings—focusing on verification, transparency, and how to document computational decisions so results remain interpretable and accountable.
All elective courses are offered in Session D (July 6 - August 14, 2026).
Three electives are required for completion of the Minor or Certificate in Digital Humanities.
Elective Course
DigHum 150A - Digital Humanities and Archival Design
Immersive Digital Archives: Cultural Heritage and the Future of Digital Humanities
Archival design can make rare sources accessible to a broad audience in ways that offer conceptual structure, critical analysis, and user flexibility. Students learn to transform primary sources into dynamic digital archives, with training in both scholarly research and public-facing digital projects.
Online archival resources for cultural heritage are at the forefront of public digital humanities. How can the past be captured in digital form—and who gets to decide how it is described? What happens when automation or AI is used to classify, translate, or summarize cultural materials? Can advanced media visualization (including augmented and virtual reality) offer new insights without flattening context? How can we ensure that digital cultural achievements endure, remain accessible, and remain ethically governed?
This course pairs readings on theory and practice with critique of existing cultural heritage platforms and trends in digitization, metadata, and access. The final project is the creation of a new digital cultural heritage resource (e.g., augmented/virtual reality, location-based games, or a combination), using visual and textual archival data from sources such as the UC Berkeley Hearst Museum of Anthropology, Museum of Fine Arts Boston, and the National Museum of Sudan (or an approved open-access source of the student’s choosing).
Elective Course
DigHum 150B - Digital Humanities and Visual and Spatial Analysis
Visual and Spatial Analysis: Maps, Graphs, and Letters
This course explores how digital tools for interactive visualization can help investigate humanities questions—and how visual forms can shape interpretation as much as they display information. We examine visualization and spatial methods as both analytical techniques and rhetorical choices.
Spatial analysis (especially GIS) applies digital cartographic tools to historical maps, geographically based events, demography, migration, textual production, and movement over time. Alongside technical skills, we emphasize critical perspectives on mapping: uncertainty, missing data, categorization choices, and how computational systems can reproduce bias.
An introduction to visual and spatial questions and tools in the humanities. Our primary focus is on visualizing the social data contained within literary correspondence; other areas of emphasis include network theory, color theory, data visualization tools, GIS, and how these methods can illuminate literary and cultural objects.
Elective Course
DigHum 150C - Digital Humanities and Textual and Language Analysis
Introduction to Computational Literary Analysis
Textual and language analysis addresses a range of language use, from the literary to the informal. Computational approaches can support humanistic inquiry by revealing patterns at scale—while raising interpretive questions about meaning, context, and what counts as evidence.
This course introduces computational literary analysis (the quantitative study of literature) and assumes no computer science background. We learn techniques such as stylometry, topic modeling, and word embeddings in Python. We also discuss contemporary AI language models as both tools and objects of critique—focusing on questions of bias, representation, and how computational “readings” relate to close reading.
Elective Course
DigHum 160 - Critical Digital Humanities
This course will concentrate on training a critical eye on the field, and analyzing what impact the digital has on the study of the humanities and on the culture at large. Even as computational and digital capacities allow us to ask new questions, they also powerfully shape how we organize and receive knowledge. Courses in the Critical Digital Humanities will provide a necessary space to critically evaluate how the modes and content of information-age technologies influence and impact the modes and content of humanistic inquiry.
This class meets online, asynchronously.
Elective Course
DigHum 161 - Decolonial Digital Humanities
This course examines how digital humanities methodologies can reinforce or challenge colonial legacies while contributing to decolonization through ethical, critical frameworks. Integrating perspectives from Decolonial Studies, Black Feminist Studies, Indigenous Studies, Cultural Studies, and Environmental Studies, students will learn to critique and create digital storytelling projects through decolonial lenses. The course introduces digital humanities tools such as text mining, structured data analysis, and visualization, emphasizing technical skills and critical literacy. No prior experience with digital humanities is required, but basic computing competency is expected.
Elective Course
DigHum 162 - Data Science for Social Justice
This course trains students to do end-to-end data work on social problems—while making the value choices in that work explicit and testable. Instead of treating “ethics” as an add-on, we focus on the concrete places where harm or injustice can enter a project: problem formulation, data collection, labeling, measurement, modeling, evaluation, and deployment. Students will build practical skills in data analysis (cleaning, exploratory analysis, visualization, simple modeling) and learn applied techniques for responsible practice, such as documentation, bias/impact checks, subgroup evaluation, and communicating uncertainty and limitations. Case studies emphasize real-world domains where data science has high stakes: policing and criminal legal systems, housing and eviction, health access, education, labor and hiring, and platform governance.