Contacts | Minor in Digital Studies of Language, Culture, and History | Summary of Requirements for the Minor | Advising and Grading | Digital Studies of Language, Culture, and History Courses
Department Website: https://digitalstudies.uchicago.edu
The minor in Digital Studies of Language, Culture, and History introduces students to computer programming and the use of cutting-edge software tools for representing, exploring, analyzing, and publishing the products of human language and culture. These products range from everyday speech and writing to historical documents and literary texts, and they encompass music and art as well as mundane objects, places, and institutions. The courses in this minor will help students not just to understand and use digital tools but to see digital computing as a cultural activity in its own right—an activity to be studied with respect to its historical development, social setting, cultural impact, and aesthetic qualities, as well as the ethical problems it creates in our increasingly digitized and networked world. This minor does not require a background in mathematics or computing but is designed for students who are majoring in the humanities or humanistic social sciences. It will also be of interest to students majoring in the sciences who want to acquire programming skills in the context of linguistic, cultural, and historical studies.
Minor in Digital Studies of Language, Culture, and History
Students must take six courses to complete the minor in Digital Studies of Language, Culture, and History. They break down as follows:
1. One course in computer programming. Either DIGS 20001 Introduction to Computer Programming Using Python, which is offered annually in the Autumn Quarter; or one of the following courses offered by the Department of Computer Science: CMSC 12100 Computer Science with Applications I, CMSC 14100 Introduction to Computer Science I, CMSC 15100 Introduction to Computer Science I, or CMSC 16100 Honors Introduction to Computer Science I. Note that CMSC 12100, 15100, and 16100 will no longer be offered as of the academic year 2022–2023 and CMSC 14100 will henceforth be the introductory course offered by the Department of Computer Science.
2. One course in data analysis: Either STAT 22000 Statistical Methods and Applications, which is offered every quarter, or DIGS 20002 Introduction to Statistics Using Python, which is offered annually in the Autumn Quarter. Note that STAT 20000 Elementary Statistics does not fulfill this requirement, although STAT courses that are more advanced than STAT 22000 would do so.
3. One course in data management: DIGS 20003 Data Management for the Humanities, which is offered annually in the Autumn Quarter.
4. One course in data publication: DIGS 20005 Data Publication for the Humanities, which is offered annually in the Spring Quarter.
5. One of the following courses:
- DIGS 20004 Data Visualization for the Humanities (Autumn)
- DIGS 20007 History and Theory of Computing for the Humanities (Winter)
- DIGS 20031 Digital Texts I: Corpus Building and Corpus Statistics (Winter)
- DIGS 20032 Digital Texts II: Natural Language Processing and Deep Learning (Spring; not offered every year)
Note that DIGS 20004, DIGS 20005, and DIGS 20006 each have as a prerequisite DIGS 20001 or an equivalent introduction to computer programming. Note that DIGS 20004 also has as a prerequisite DIGS 20002 or an equivalent introduction to statistics.
Note that students who have taken courses in computer programming and/or statistics to fulfill the requirements of their major(s) or other minor(s), or to fulfill the general education requirements, cannot double-count those courses to reduce the number of courses required for the Digital Studies minor. In that case, they will take additional DIGS course(s) from the list above in lieu of DIGS 20001 and/or DIGS 20002.
6. One elective course in the humanities or humanistic social sciences that has a digital component, broadly defined, and has been approved by the Director of Digital Studies. Students who wish to use their elective slot to do their own digital project and create a software product for their portfolio may do so by means of a DIGS independent study course that will count as their elective.
Note that the particular courses on offer will vary from year to year and some courses may have prerequisites. Examples of potentially suitable courses include:
CMST 25204 Media Ecology: Embodiment & Software
CMST 27110 Digital Cinema
CMST 27815 Introduction to Art, Technology, and Media
CMST 27920 Virtual Reality Production
ENGL 25980 Technorelations: Intimacy, Bodies, Machines
ENGL 25990 Always Already New - Printed Books & Electronic Texts
GEOG 28201 Intro to Geographic Information Systems
HIPS 25205 Computers, Minds, Intelligence & Data
HIST 25415 History of Information
HIST 25425 Censorship, Info Control, & Revolutions in Info Technology from the Printing Press to the Internet
HIST 29523 Data History: Information Overload from the Enlightenment to Google
LING 28600 Computational Linguistics
MUSI 26618 Electronic Music: Composing with Sound
Summary of Requirements for the Minor
| DIGS 20001 | Introduction to Computer Programming Using Python | 100 |
| or CMSC 12100 | Computer Science with Applications I | |
| or CMSC 14100 | Introduction to Computer Science I | |
| or CMSC 15100 | Introduction to Computer Science I | |
| or CMSC 16100 | Honors Introduction to Computer Science I | |
| DIGS 20002 | Introduction to Statistics Using Python | 100 |
| or STAT 22000 | Statistical Methods and Applications | |
| DIGS 20003 | Data Management for the Humanities | 100 |
| DIGS 20005 | Data Publication for the Humanities | 100 |
| DIGS 20004 | Data Visualization for the Humanities | 100 |
| or DIGS 20007 | History and Theory of Computing for the Humanities | |
| or DIGS 20031 | Digital Texts I: Corpus Building and Corpus Statistics | |
| or DIGS 20032 | Digital Texts II: Natural Language Processing and Deep Learning | |
| One elective, approved by the faculty director | 100 | |
| Total Units | 600 | |
Advising and Grading
Courses in the minor may not be double counted with the student's major(s), other minors, or general education requirements. Courses in the minor must be taken for quality grades, and more than half of the requirements for the minor must be met by registering for courses bearing University of Chicago course numbers.
Students who elect the minor must meet with the academic director before the end of Spring Quarter of their third year to declare their intention to complete the minor. The director's approval for the minor program should be submitted to a student's College adviser by the deadline above using the Consent to Complete a Minor Program form.
Digital Studies of Language, Culture, and History Courses
DIGS 10000. Approaches to Digital Humanities Using Python. 100 Units.
This course introduces students to (1) current work in digital humanities with examples of the software applications being used and the computational research being done in literary, historical, linguistic, and cultural studies; and (2) the principles and practices of computer programming using the Python programming language. (Taught remotely via Zoom in the Summer Session; undergraduate only.)
Instructor(s): Clovis Gladstone Terms Offered: Summer
Equivalent Course(s): DIGS 30000
DIGS 20001. Introduction to Computer Programming Using Python. 100 Units.
This course provides an introduction to computer programming and computational concepts using the Python programming language. Students are also introduced to the use of Visual Studio Code as an industry-standard source code editor. This course is a prerequisite for most of the other Digital Studies (DIGS) courses. Students enrolled in one of the Digital Studies programs (MA, joint BA/MA, undergraduate minor, or graduate certificate) who have previously passed an equivalent college-level course in computer programming with a grade of B (3.0) or higher may petition the Associate Director of Curriculum and Instruction of the Forum for Digital Culture for an exemption from taking this course and permission to take an additional elective course instead.
Instructor(s): Clovis Gladstone Terms Offered: Autumn
Equivalent Course(s): DIGS 30001
DIGS 20002. Introduction to Statistics Using Python. 100 Units.
This course provides an introduction to statistics and computational data analysis using Python and Jupyter Notebook. It is a prerequisite for "Data Analysis II: Data Visualization and Machine Learning" (DIGS 20004/30004) in the Winter Quarter. Topics covered include probability, distributions, and statistical inference, as well as linear regression and logistic regression. Students will gain additional practice in Python coding and will learn how to use Python libraries for statistics and plotting. The textbook for this course is OpenIntro Statistics, which is available online, free of charge. Students enrolled in one of the Digital Studies programs (MA, joint BA/MA, undergraduate minor, or graduate certificate) who have previously passed an equivalent college-level course in statistics with a grade of B (3.0) or higher may petition the Associate Director of Curriculum and Instruction of the Forum for Digital Culture for an exemption from taking this course and permission to take an additional elective course instead.
Instructor(s): Brooke Luetgert Terms Offered: Autumn
Equivalent Course(s): DIGS 30002
DIGS 20003. Data Management for the Humanities. 100 Units.
This course introduces concepts and techniques related to the representation and management of digital data with emphasis on the forms of data encountered in the humanities. Topics covered include: (1) digital text encoding using the Unicode and XML standards, with attention to the TEI-XML tagging scheme of the Text Encoding Initiative; (2) digital typefaces ("fonts") for displaying encoded characters; (3) digital encoding of 2D images, 3D models, sound, and video; (4) database models and querying languages (especially SQL for relational databases and SPARQL for non-relational RDF-graph databases), with attention to methods for integrating and querying the kinds of semi-structured and heterogeneous data characteristic of the humanities; (5) ontologies, the Semantic Web, and related technical standards; and (6) cartographic concepts (e.g., coordinate systems and map projections) and the basics of geospatial data management using Geographic Information Systems. This course has no prerequisite; i.e., prior knowledge of computer programming is not required.
Instructor(s): Miller Prosser Terms Offered: Autumn
Equivalent Course(s): DIGS 30003
DIGS 20004. Data Visualization for the Humanities. 100 Units.
This course introduces best practices for visualizing data sets to assist the study of human languages, cultures, and history. Python-based tools will be used to create data visualizations, enhancing familiarity with that programming language. The emphasis will be on displaying data in a clear and elegant manner that is appropriate for the type of information we wish to showcase. Students will learn exploratory and explanatory data visualization techniques both to analyze the data and to communicate ideas via data-based storytelling. Possible biases in the way data is presented will be noted so students can learn to guard against them. Examples of data sets derived from research in the humanities will be used to develop creative and technical skills to produce standard 2D and 3D plots for descriptive summaries of the data, to identify outliers, and to do statistical correlations and model predictions that reveal underlying trends and potential anomalies. Social network analysis (a method widely used in the humanities and social sciences) will also be introduced, as well as tools for data visualization using geographical maps and timelines. Prerequisites: DIGS 20001/30001, "Introduction to Computer Programming Using Python," or an equivalent course in computer programming and DIGS 20002/30002, "Introduction to Statistics Using Python," or an equivalent course in statistics.
Instructor(s): Brooke Luetgert Terms Offered: Winter
Prerequisite(s): DIGS 20001/30001, “Introduction to Computer Programming with Python” (or an equivalent course in computer programming) and DIGS 20002/30002, “Data Analysis I: Introduction to Statistics” (or an equivalent course in statistics).
Equivalent Course(s): DIGS 30004
DIGS 20005. Data Publication for the Humanities. 100 Units.
This course introduces software techniques and tools for building Web browser apps written in HTML5, CSS, and JavaScript with emphasis on user interfaces for presenting information to researchers and students in the humanities. Students will take an active role in evaluating approaches and outcomes of existing digital publications. Topics covered include: (1) the use of application programming interfaces (APIs) to integrate into Web apps the various analysis, visualization, and database services provided by external systems; (2) the transformation of data into formats appropriate for publication on the Web; and (3) the nature of data in the humanities as pertains to digital publication.
Instructor(s): Miller Prosser Terms Offered: Spring
Prerequisite(s): DIGS 20001/30001, “Introduction to Computer Programming with Python” (or an equivalent course in computer programming).
Equivalent Course(s): DIGS 30005
DIGS 20006. Artificial Intelligence and the Humanities. 100 Units.
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.
Instructor(s): Jeffrey Tharsen Terms Offered: Spring
Equivalent Course(s): DIGS 30006
DIGS 20007. History and Theory of Computing for the Humanities. 100 Units.
This course surveys (1) the history and theory of digital computing, (2) the ways computers have been used in the humanities, (3) recent theoretical debates surrounding the contested concept of "digital humanities," (4) the philosophical issues raised by digital knowledge representation and artificial intelligence, and (5) the ethical and public policy issues raised by the pervasive use of digital technology in present-day societies.
Instructor(s): David Schloen Terms Offered: Winter
Prerequisite(s): DIGS 20001/30001, “Introduction to Computer Programming with Python” (or an equivalent course in computer programming) and DIGS 20003/30003, “Data Management for the Humanities.” These prerequisites may be waived in some cases with the instructor’s consent.
Equivalent Course(s): DIGS 30007
DIGS 20021. Digital Archaeology. 100 Units.
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."
Instructor(s): David Schloen Terms Offered: Spring
Prerequisite(s): 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.
Equivalent Course(s): DIGS 30021
DIGS 20031. Digital Texts I: Corpus Building and Corpus Statistics. 100 Units.
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(s): Clovis Gladstone Terms Offered: Winter
Equivalent Course(s): DIGS 30031, RLLT 24550, RLLT 34550
DIGS 20032. Digital Texts II: Natural Language Processing and Deep Learning. 100 Units.
This course builds on DIGS 20031/30031, "Digital Texts I: Corpus Building and Corpus Statistics," by introducing students to advanced computational methods for studying texts, including deep learning (AI), with emphasis on the needs of research in the humanities. Students will evaluate these methods and gain practical experience in applying them. Prerequisites: DIGS 20001/30001, "Introduction to Computer Programming with Python," DIGS 20004/30004, "Data Analysis II: Data Visualization and Machine Learning," and DIGS 20031/30031, "Digital Texts I: Corpus Building and Corpus Statistics," or equivalent prior preparation.
Instructor(s): Jeffrey Tharsen Terms Offered: Spring
Prerequisite(s): 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.”
Note(s): Prerequisites may be waived by permission of the instructor for students who have sufficient background in the subject.
Equivalent Course(s): DIGS 30032
DIGS 20043. Digital Media III: Creating 3D Worlds in Blender. 100 Units.
This course introduces students to digital rendering, modeling, and sculpting using the Blender platform. Prerequisite: DIGS 20001/30001, "Introduction to Computer Programming Using Python" or an equivalent course in computer programming.
Equivalent Course(s): MADD 20043, DIGS 30043
DIGS 26021. Sense & Sensibility & Science @UChicago. 100 Units.
In Sense & Sensibility & Science, you will learn how to better incorporate into your thinking and decision making the problem-solving techniques of science at its best. Many insights and conceptual tools from scientific thinking are of great utility for solving problems in your own day-to-day life and in a democracy. Yet, as individuals, as groups, as whole societies we fail to take full advantage of these methods. The focus in this course is on the errors humans tend to make, and the approaches scientific methodology has developed (and continues to develop) to minimize those errors. The course includes a discussion of the nature of science, what makes science such an effective way of knowing, how both non-scientific thinking and scientific thinking can go awry, and how we can reason more clearly and successfully as individuals, as members of groups, and as citizens of a democracy. The undergraduate course will be simultaneously taught at UC Berkeley, Harvard and UChicago in spring 2024, with an opportunity for students from all three courses to participate remotely in the same deliberative polling capstone experience. UChicago's spring 2024 course premiere builds on a decade of experience developing and teaching the popular course at Berkeley and Harvard's adoption of its own version in 2021.
Instructor(s): Reid Hastie, Jordan Kemp, Julia Koschinsky Terms Offered: Spring
Prerequisite(s): PQ: Third or fourth-year standing.
Equivalent Course(s): SCPD 26021, PBPL 26021, HIPS 26021, BPRO 26021, SOSC 26021