Graduate Courses
How to find electives:
- Review the master list of approved electives. Note: “Grad” denotes graduate courses, “LD” denotes lower division, and “UD” denotes upper division courses.
- Identify courses you’re interested in.
- Check the course schedule to see if the courses of interest are offered in the next quarter.
- Register!
Please fill out this form if you’d like to petition for an elective. Include all the information you can, including a syllabus, if available. Petitions will be reviewed at least once a quarter. Please email Deanna Finlay if you have additional questions.
Upcoming Courses
Please note that even though some these courses may be offered as undergraduate classes, graduate students are encouraged and welcome to register for them. We have also updated the course codes for a number of our frequently offered classes. Any of the following classes, except DH 101, may be taken to fulfill the DH 250 requirement, and any non-DH classes advertised here will fulfill elective requirements.
Winter 2026
·DH 250 – Special Topics in Digital Humanities
Instructor: Wendy Kurtz
Seminar, three hours. Enforced requisite: course 201. Introduction to advanced research method or thematic issue in digital humanities, such as digital textual analysis, digital mapping database and visualization technologies, or social media technologies. Acquisition of familiarity with particular set of technologies by learning practical research methods and theoretical issues to carry out advanced research in this area. Examination of critiques of theoretical underpinnings of such technologies and issues that they raise. May be repeated for credit with topic change. Letter grading.
·DH M221 / Social Science M240 – Data and Society
Instructor: Nour Joudah
Introduction to way data and computing technologies increasingly play pivotal role in social life. Students pose critical questions about social impact of data, while also gaining literacy in engaging digital and data tools. Students learn to recognize historically and institutionally produced biases in data research and science. Engagement is encouraged with how to work with data for social justice aims. S/U or letter grading.