For a list of upcoming classes see here.

INSH 7910. NULab Project Seminar
This workshop course supports the project development component of the certificate in Digital Humanities, aimed at graduate students enrolled in MA and PhD programs in humanities and social sciences. Students in the course will engage in a sustained, interdisciplinary exploration of digital humanities methods and projects as they plan and develop their own research projects during their progress on the certificate. As needed, the course will also organize working groups on special topics to cover additional skills and methods. The course is designed to be taken in successive years by students in the certificate program, but may also be taken on its own. No prior technical experience or familiarity with digital humanities or digital tools is required, but participants should be prepared to identify an area of research interest that is connected in some way with the general domain of digital humanities, computational social science, and related fields.

ENGL 7370. Topics in Digital Humanities: Introduction to Digital Humanities
This course offers an intensive introduction to the tools, methods, and intellectual history of the domain now known broadly as digital humanities. We’ll begin with a critical orientation to the field that considers its various myths of origin and definition exercises and what they have at stake, and we’ll ask what we seek from the field and its distinctive competencies. The remaining units of the course will be structured around three core concepts: data, tools, and work. In each unit we’ll investigate how digital humanities distinctively re-imagines and repositions these concepts with respect to the humanities, through a combination of readings, discussion, and practical exploration. Students will come away with a well-grounded understanding of the overall landscape and a set of foundational skills that will support their future research projects. The course assignments will give students both practical hands-on experience and opportunities for critical reflection, and will include experiments in data creation and manipulation, reflective essays, and a grant proposal.

HIST 7370. Texts, Maps, and Networks: Readings and Methods for Digital History
Introduces the methods and practice of history in a digital age. Offers students an opportunity to see the wide variety of work being done computationally by historians and other humanists today and to obtain the background to be creative producers of new work and critical consumers of existing projects. The rise of computing technology and the Internet has the potential to reshape all parts of historical practice, from curation to research to dissemination. Examines the historian’s craft in three primary domains: the creation of digital sources, the algorithmic transformations that computers can enact on cultural materials like texts, and the new ecologies of publishing and scholarly communication made possible by new media.

ARTG 5100. Information Design Studio 1: Principles
Explores the theories and practices of information design through studio projects. Investigates visual systems and information structures such as maps, timelines, charts, and diagrams. Emphasizes the creative process of organizing, visualizing, and communicating data by seeking to make complex information easier to understand and use. Requires graduate standing or permission of program coordinator or instructor.

ARTG 5120. Information Design Research Methods
Examines qualitative and quantitative research methods pertinent to information communication systems. Through discussion and writing activities, offers students an opportunity to investigate varied inquiry toward the development of researchable questions, argument formation, and assessment methodologies. Requires graduate standing or permission of program coordinator or instructor.

CS 6120. Natural Language Processing
Provides an introduction to the computational modeling of human language, the ongoing effort to create computer programs that can communicate with people in natural language, and current applications of the natural language field, such as automated document classification, intelligent query processing, and information extraction. Topics include computational models of grammar and automatic parsing, statistical language models and the analysis of large text corpuses, natural language semantics and programs that understand language, models of discourse structure, and language use by intelligent agents. Course work includes formal and mathematical analysis of language models, and implementation of working programs that analyze and interpret natural language text.

CS 7290. Special Topics in Data Science: Visualization for Network Science
This course will cover the principles of information visualization in the specific context of network science. It will introduce students to visually encoding data and our understanding of human vision and perception; interaction principles including filtering, pivoting, aggregation; and both quantitative and human subjects evaluation techniques. It will cover visualization techniques for several types of networks, including multivariate networks with attributes for entities and relationships, evolving and dynamic networks that change over time, heterogeneous networks consisting of multiple types of entities, and geospatial networks. Students will learn about the design of layout algorithms for node-link and matrix visualizations.

ENGL 7370. Topics in Digital Humanities: The Shape of Data in the Humanities
This course is intended as an introduction to the concepts and basic practices of data modeling for researchers in digital humanities. We will move from discussions of very simple data formats to more complex formats such as databases and XML, with hands-on explorations including Omeka and XML schema-writing. The readings provide critical context and help situate the theory and practice of data modeling within the domain of digital humanities research. Students will come away with a strongly grounded understanding of how humanities data is shaped and used, and how those practices affect critical and scholarly practice. No prior technical experience is assumed, although at times the course will move quickly; we will organize lab sessions and opportunities for extra help as needed.

DSSH 6302. Information Design and Visual Analytics
Introduces the systematic use of visualization techniques for supporting the discovery of new information as well as the effective presentation of known facts. Based on principles from art, graphic design, perceptual psychology, and rhetoric, offers students an opportunity to learn how to successfully choose appropriate visual languages for representing various kinds of data to support insights relevant to the user’s goals. Covers visual data mining techniques and algorithms for supporting the knowledge-discovery process; principles of visual perception and color theory for revealing patterns in data, semiotics, and the epistemology of visual representation; narrative strategies for communicating and presenting information and evidence; and the critical evaluation and critique of data visualizations. Requires proficiency in R.

HIST 7219. Humanities Data Analysis
Data analysis in the humanities presents challenges of scale, interpretation, and communication distinct from the social sciences or sciences. It also, some argue, opens up new opportunities for creative storytelling and narrativity. This seminar will explore the emerging practices of data analysis in the digital humanities from both a critical and a practical perspective. What light can algorithmic approaches shed on live questions in humanistic scholarship? What new forms of research are enabled by the use of data? What sort of data do practicing humanists want museums and libraries to make available? Our goal in this class will be to explore the new emerging forms of data analysis taking place in humanities scholarship, both in terms of applying algorithms and in terms of better investigating the presuppositions and biases of the digital object. We’ll aim to come out much more sophisticated in the use of computational techniques and much more informed about how others might use them.

HIST 7219. Digital Space and Place
What is the “spatial turn” and how does it intersect with the digital humanities? This course offers an introduction to major theories of space and place and how they are being applied through technologies such as Geographic Information Systems (GIS), data visualizations, and 3D modeling. This is a hands-on course in which students will develop digital skillsets, including creating online maps and visualizations, analyzing spatial datasets, and designing virtual exhibits – all within a humanities framework of spatial theory. Classes will consist of a combination of discussion, practicums, walking tours, and field trips. Students will emerge from the course with spatial literacy: the ability to critically read, analyze, and interpret a wide variety of spaces and places (neighborhoods, landscapes, museums) along with ways of representing these geographies in maps, narratives, video games, and other media.

INSH 6406. Analyzing Complex Digitized Data
Introduces cutting-edge ways of structuring and analyzing complex data or digitized text-as-data using the open-source programming language Python. Scholars across multiple disciplines are finding themselves face-to-face with massive amounts of digitized data. In the humanities and social sciences, these data are often in the form of unstructured text and un- or under-structured data. Encourages students to think about novel ways they can apply these techniques to their own data and research questions and to apply the methods in their own research, whether it be in academia or in industry.

JRNL 6341. Telling Your Story with Data
Explores select topics in data journalism and support data-driven storytelling projects of various kinds. Offers students an opportunity to learn how to navigate the often-competing demands of rigorous analysis and accessible narrative and storytelling. Course units are designed to foster moderate technical learning of applications and software, incorporate theories from relevant fields in data visualization and data science, and emphasize storytelling for broad public audiences.

JRNL 6340. Fundamentals of Digital Journalism
Offers students an opportunity to learn the fundamentals of digital journalism and to place those skills within the context of a changing media environment. Studies multimedia tools within an intellectual framework—i.e., offers students an opportunity to learn hands-on skills and also to study best practices and theory. May include guest speakers and a consideration of the future of news. Requires students to produce a final project that consists of storytelling across a range of digital platforms.

JRNL 6355. Seminar in Investigative Reporting
Introduces students to the world of investigative reporting as it is practiced at major metropolitan newspapers. Asks students to work as members of investigative reporting teams and introduces them to advanced reporting techniques and standards in the classroom. Provides an opportunity to learn how ideas for investigative reporting projects are developed; how to identify and interpret public records and online databases; and how to do interviews and write investigative stories. Working in small teams, the students are given an opportunity to develop and write investigative stories for publication.

POLS 7334. Social Networks
Offers an overview of the literature on social networks, with literature from political science, sociology, economics, and physics. Analyzes the underlying topology of networks and how we visualize and analyze network data. Key topics include small-world literature and the spread of information and disease. Students who do not meet course prerequisites may seek permission of instructor.

PPUA 5301. Introduction to Computational Statistics
Introduces the fundamental techniques of quantitative data analysis, ranging from foundational skills—such as data description and visualization, probability, and statistics—to the workhorse of data analysis and regression, to more advanced topics—such as machine learning and networks. Emphasizes real-world data and applications using the R statistical computing language. Analyzing and understanding complex data has become an essential component of numerous fields: business and economics, health and medicine, marketing, public policy, computer science, engineering, and many more. Offers students an opportunity to finish the course ready to apply a wide variety of analytic methods to data problems, present their results to nonexperts, and progress to more advanced course work delving into the many topics introduced here.

PPUA 5302. Information Design and Visual Analytics

Introduces the systematic use of visualization techniques for supporting the discovery of new information as well as the effective presentation of known facts. Based on principles from art, graphic design, perceptual psychology, and rhetoric, offers students an opportunity to learn how to successfully choose appropriate visual languages for representing various kinds of data to support insights relevant to the user’s goals. Covers visual data mining techniques and algorithms for supporting the knowledge-discovery process; principles of visual perception and color theory for revealing patterns in data, semiotics, and the epistemology of visual representation; narrative strategies for communicating and presenting information and evidence; and the critical evaluation and critique of data visualizations. Requires proficiency in R.

PPUA 5263. Geographic Information Systems for Urban and Regional Policy

Studies basic skills in spatial analytic methods. Introduces students to some of the urban social scientific and policy questions that have been answered with these methods. Covers introductory concepts and tools in geographic information systems (GIS). Offers students an opportunity to obtain the skills to develop and write an original policy-oriented spatial research project with an urban social science focus.