The curriculum for the one-year M.A. in Digital Studies includes three elective courses of the student’s own choosing in addition to the six core courses required for the degree. The undergraduate minor allows one elective course.
At least one of the three elective courses for the M.A. must deal with digital computing, in some fashion, whether or not the course entails actual coding; the other two may be on any subject of interest to the student. The single elective course allowed for the undergraduate minor must pertain to digital computing.
Please note that students must obtain written approval from the Associate Director of Curriculum and Instruction of the Forum for Digital Culture to take an elective course that does not appear in the list of preapproved elective courses below. This requirement applies both to courses that deal with digital computing and courses on other topics.
Elective courses may be chosen from among the course offerings of any department or program in the Division of the Humanities or the Division of the Social Sciences of the University of Chicago, subject to the enrollment restrictions and prerequisites that may pertain to a particular course. With the exception of certain courses offered by the Department of Computer Science, students will not normally be allowed to enroll in courses offered by other schools or divisions of the University, including the Booth School of Business and the Harris School of Public Policy. However, students who are well prepared to take such courses may, in exceptional cases, be allowed to do so.
Please note that students who have previously passed a college-level course in computer programming or statistics with a grade of B (3.0) or higher may petition the Associate Director of Curriculum and Instruction for an exemption from taking the corresponding core course, i.e., DIGS 20001/30001, “Introduction to Computer Programming with Python,” or DIGS 20002/30002, “Data Analysis I: Introduction to Statistics.” If the petition is granted, the core course(s) will be replaced by additional elective course(s) in the Autumn Quarter.
Elective Courses for Specializations in Digital Studies
There are four areas of specialization in Digital Studies for which elective courses are offered on an annual basis by the Forum for Digital Culture. Descriptions of these courses are provided below. Students in the two-year version of the M.A. program will be required to take courses in their area of specialization. Students doing a one-year M.A. who are interested in one of these areas may choose to take their elective courses in that area. However, one-year students are not required to do a specialization and may choose three unrelated electives.
Digital Texts and Culture
DIGS 20031/30031. Digital Texts I: Corpus Building and Corpus Statistics. 100 units. Winter. The purpose of this course is to introduce students in the humanities to digital methodologies for the study of texts. Students will not only learn how to construct a digital text collection but also how to process text as data. Among the various digital approaches which will be introduced in class are concordances (retrieving occurrences of words), semantic similarity detection (finding similar passages across texts), sentiment analysis, and stylometry (analysis of literary style). The course will highlight how these approaches to text can provide new avenues of research, such as tracing intellectual influence over the longue durée, or uncovering the distinguishing stylistic features of an author, work, or literary movement. Students need no prior knowledge of such methods, and the course will aim at providing both the basics of computer programming in Python and giving students the necessary tools to conduct a digital humanities project. The source material for the course will be drawn from literary sources and students will be free (and encouraged) to use texts which are relevant to their own research interests. Students will need to bring a laptop to class. Instructor: Clovis Gladstone
DIGS 20032/30032. Digital Texts II: Graph Databases and Deep Learning for Textual Studies. 100 units. Spring. This course builds on DIGS 20031/30031, “Digital Texts I: Corpus Building and Corpus Statistics,” by introducing students to two additional methods for studying texts in the context of humanities research: (1) the use of graph database systems (and, in particular, the OCHRE platform) to provide richer digital representations of literary, economic, and historical texts, ancient and modern, and of the complex relationships within and between texts which are the focus of scholarship in the humanities; and (2) the use of deep neural networks (“deep learning”) and large language models to analyze, translate, and generate texts. Students will evaluate these digital methods in comparison to traditional approaches and will gain practical experience by applying them in their own course projects. Prerequisites: DIGS 20001/30001, “Introduction to Computer Programming with Python,” DIGS 20003/30003, “Data Management for the Humanities,” DIGS 20004/30004, “Data Analysis II: Data Visualization and Machine Learning,” and DIGS 20031/30031, “Digital Texts I: Corpus Building and Corpus Statistics.” Instructor: Jeffrey Tharsen
DIGS 20035/30035. Introduction to Cultural Analytics. 100 units. Spring. This course introduces students to the emerging field of cultural analytics — a field that sits at the intersection of cultural studies, information science, and the computational social sciences. At root, the field is oriented around questions of how to study the cultural past and present (whether text, image, or sound) with the aid of data-driven methods, and what such methods imply for our understanding of human culture. The course will begin with a look at how past scholars wrestled with the problem of applying numbers to cultural objects, and some of their initial attempts to do so. We then move to survey the wide variety of scholarship happening today under the influence of new digital technologies and vast new information infrastructures. How have scholars across different humanistic fields adopted new computational tools? What methodological and theoretical problems has this raised? What new discoveries has it yielded? Finally, the course will consider new research directions opened up by recent advances in artificial intelligence and the increasing convergence of cultural production with online platforms that are global in reach (e.g., TikTok, Wattpad, Netflix, Spotify). Students will engage with these questions through primary readings, attempts to replicate past studies, and by designing their own research proposals. Instructor: Hoyt Long
Digital Media and Extended Reality
DIGS 30041/MAAD 20041. Digital Media I: Game Design with Unity. 100 units. Winter. Part one of a two-course sequence, this making-oriented course provides an introduction to the principles, practices, and techniques of game design. Students will develop several small games, gaining hands-on experience with C# and the Unity development platform. The course takes a “ground up” approach: starting with the fundamentals of object- and component-oriented programming, then using those fundamentals to build complex, interactive experiences. While the course focuses on Unity, an introduction to software design patterns and an emphasis on a rapid feedback/iteration cycle will provide tools that translate to other game engines and creative computing projects. Through critique and the close examination of case studies from prior art, students will cultivate their critical eye and articulation, equipping them to discuss, assess, and refine games at various stages of development. Prerequisite: DIGS 20001/30001, “Introduction to Computer Programming with Python” (or an equivalent course in computer programming). Instructor: Cameron Mankin
DIGS 30042/MAAD 20042. Digital Media II: Extended Reality with Unity. 100 units. Spring. Part two of a two-course sequence, this course teaches students how to develop extended reality (XR) environments using the Unity platform. The course emphasizes the creation of augmented reality (AR) and virtual reality (VR) environments, allowing students to gain hands-on experience. Additionally, students will discuss development with their instructor and peers, assisting them in refining their skills and ideas while creating. By the end of the quarter, students will clearly understand the process of transforming ideas into final products, equipping them with the necessary tools for future XR endeavors. Prerequisite: DIGS 30041/MAAD 20041, “Digital Media I: Game Design with Unity” (or an equivalent Unity course approved by the instructor). Instructor: Crystal Beiersdorfer
Additional courses relevant to the specialization in Digital Media and Extended Reality are offered regularly by the Department of Cinema and Media Studies (CMST) and the Department of Computer Science (CMSC) and are listed below as preapproved electives.
Digital Art and Archaeology
DIGS 20021/30021. Digital Archaeology. 100 units. Spring. This course introduces students to a variety of computational methods used in archaeology and art history for the digital representation and analysis of cultural sites, buildings, landscapes, and artifacts. Relevant concepts and techniques are taught by means of both explanatory lectures and hands-on exercises. Software tools used in the course include ArcGIS and QGIS for geospatial data and map-creation; Agisoft Metashape for photogrammetry and 3D modeling; OCHRE for integrated multimedia data management; and Python software libraries for image analysis, feature recognition, and statistics. Gamification and the use of augmented reality and virtual reality in archaeology are discussed briefly; these topics are covered in detail in DIGS 20041/30041, “Digital Media I: Game Design with Unity,” and DIGS 20042/30042, “Digital Media II: Extended Reality with Unity.” Prerequisites: DIGS 20001/30001, “Introduction to Computer Programming with Python” (or an equivalent course in computer programming), DIGS 20002/30002, “Data Analysis I: Introduction to Statistics” (or an equivalent course in statistics), and DIGS 20003/30003, “Data Management for the Humanities.” These prerequisites may be waived in some cases with the instructor’s consent. Instructors: David Schloen and Andrew Wright
Two additional courses relevant to the specialization in Digital Art and Archaeology are offered annually by the Department of Near Eastern Languages and Civilizations:
NEAA 20061/30061. Ancient Landscapes I. 100 units. Autumn. This is the first course in a two-course sequence that introduces students to theory and method in landscape studies and the use of Geographic Information Systems (GIS) to analyze archaeological, anthropological, historical, and environmental data. Course one covers the theoretical and methodological background necessary to understand spatial approaches to landscape and the fundamentals of using ESRI’s ArcGIS software, and further guides students in developing a research proposal. Instructor: Mehrnoush Soroush
NEAA 20062/30062. Ancient Landscapes II. 100 units. Winter. This course covers more advanced GIS-based analysis (using vector, raster, and satellite remote-sensing data) and guides students in carrying out their own spatial research project. In both courses of this two-course sequence, techniques are introduced through the discussion of case studies (focused on the archaeology of the Middle East) and through demonstration of software skills. During supervised laboratory times, the various techniques and analyses covered will be applied to sample archaeological data and also to data from a region/topic chosen by the student. Instructor: Mehrnoush Soroush
Students interested in Digital Art and Archaeology are also encouraged to take “Digital Media I: Game Design with Unity” and “Digital Media II: Extended Reality with Unity,” described above.
Artificial Intelligence and Language
DIGS 30006. Artificial Intelligence and the Humanities. 100 units. Spring. In this course we will look at artificial intelligence (AI) from the perspective of the humanities both to assess the impact of AI on the creation and study of cultural materials and to question its presuppositions. The first part of the course will survey the history of the attempts made over the years to create AI using computational methods and the philosophical critiques of those attempts. Attention will be paid both to symbolic AI that employs explicit digital representations of human knowledge and reasoning and the quite different paradigm of connectionist AI that employs neural networks and predictive models. In the latter part of the course, we will discuss the recent development of “generative AI” systems (e.g., ChatGPT) that use large “foundation models” to create remarkably human-like text and images and we will experiment with these systems via hands-on exercises. We will consider the benefits and drawbacks of such tools for research in the humanities and discuss their social and cultural impact more generally. Instructors: Jeffrey Tharsen and David Schloen
Additional courses relevant to the specialization in Artificial Intelligence and Language are offered regularly by the Department of Linguistics (LING) and the Department of Philosophy (PHIL) and are listed below as preapproved electives.
Preapproved Elective Courses
The following courses offered in the Division of the Humanities and the Division of the Social Sciences that pertain in some way to digital computing are preapproved as elective courses for the Master of Arts in Digital Studies of Language, Culture, and History, the joint BA/MA program, and the undergraduate minor.
This list is provided as a convenient starting point for choosing elective courses that deal in some way with digital computing, keeping in mind that only one of the three electives chosen by MA students must be digitally oriented and the other two can be on any subject of interest. The courses listed below are only examples; they may not be available in a given year and departments may offer other suitable courses that are not listed here.
Students are free to inspect departmental course offerings and choose elective courses that do not appear on the list below, but they must obtain written permission from the Associate Director of Curriculum and Instruction before enrolling in a course that is not listed here.
Please note that courses listed below may not be offered in a given year and some have prerequisites or enrollment restrictions that may prevent Digital Studies students from taking them.
- ARTV 32502, Data and Algorithm in Art
- CEGU 32301, Digital Geographies of Climate Justice
- CLAS 35415, Text Into Data: Digital Philology
- CLAS 35922, Digital Humanities for the Ancient World
- CMSC 20300, Introduction to Human-Computer Interaction
- CMSC 20370, Inclusive Technology: Designing for Underserved and Marginalized Populations
- CMSC 20380, Actuated User Interfaces and Technology
- CMSC 23240, Emergent Interface Technologies
- CMSC 23900, Data Visualization
- CMST 25204, Media Ecology: Embodiment and Software
- CMST 27110, Digital Cinema
- CMST 27815, Introduction to Art, Technology, and Media
- CMST 27916, Critical Videogame Studies
- CMST 35954, Alternate Reality Games: Theory and Production
- CMST 37020, New Media at a Distance
- CMST 37803, Digital Media Theory
- CMST 37911, Augmented Reality Production
- CMST 37920, Virtual Reality Production
- CMST 67021, Performance Captured
- CMST 67820, The Image in the Age of Artificial Intelligence
- CMST 67827, Politics of Media: From the Culture Industry to Google Brain
- CMST 67922, Data-Driven Dystopias
- DIGS 10000, Approaches to Digital Humanities Using Python (Summer)
- DIGS 30006, Artificial Intelligence and the Humanities (Spring)
- DIGS 30021, Digital Archaeology (Spring)
- DIGS 30031, Digital Texts I: Corpus Building and Corpus Statistics (Winter)
- DIGS 30032, Digital Texts II: Graph Databases and Deep Learning for Textual Studies (Spring)
- DIGS 30041, Digital Media I: Game Design with Unity (Winter)
- DIGS 30042, Digital Media II: Extended Reality with Unity (Spring)
- GEOG 30500, Introduction to Spatial Data Science
- GEOG 38202, Geographic Information Science I (Autumn)
- GEOG 38402, Geographic Information Science II (Winter)
- GEOG 38602, Geographic Information Science III (Spring)
- GEOG 38702, Introduction to GIS and Spatial Analysis
- HIPS 25205, Computers, Minds, Intelligence and Data
- HIST 25415, History of Information
- HIST 29523, Data History: Information Overload from the Enlightenment to Google
- HIST 35425, Censorship, Information Control, and Revolutions in Information Technology from the Printing Press to the Internet
- HIST 39530, Introduction to Digital History I
- HIST 39521, Introduction to Digital History II
- KNOW 32011, Data: History and Literature
- KNOW 32208, Posthuman Becoming
- KNOW 36043, The Aesthetics of Artificial Intelligence
- KNOW 36065, Classification as World-Making
- LING 32880, Computational Models in Phonology
- LING 38610, Computational Linguistics I
- LING 38620, Computational Linguistics II
- MAAD 21111, Creative Coding
- MAAD 21500, Metamedia Design Studio
MAAD 22800, 3D Modeling and Sculpting for Video Games
- MAAD 23631, Introduction to Internet Art
- MAAD 23632, Intermediate Internet Art
- MAAD 23640, Embodied Data and Gamified Interfaces
- MACS 30123, Large-Scale Computing for the Social Sciences
- MACS 31300, AI Applications in Social Sciences
- MACS 40400, Computation and the Identification of Cultural Patterns
- MUSI 26618, Electronic Music I
- MUSI 36630, Musical Robotics
- NEAA 30061, Ancient Landscapes I
- NEAA 30062, Ancient Landscapes II
- PHIL 29904, Ethics in the Digital Age
- PHIL 32962, The Epistemology of Deep Learning