The work of the program over the next two years is to transform a selection of courses featuring computation into a curriculum that integrates computing throughout the liberal arts.
If you are a prospective student or parent with questions about the future direction of this curriculum, feel free to email the chair (Matt Jadud, email@example.com) with your questions.Courses
DCS 102. The Design of Digital and Computational Systems.A first exploration of the design of computational systems. Like art, music, and literature as well as physical and social systems, computational systems have an underlying structure and beauty. This course introduces those structures and encourages the exploration of how we can manipulate them to create dynamic and engaging systems that represent both the world around us as well as universes imagined. The course lays foundations for computer programming, explores questions regarding gender and race in digital communities, and creatively investigates digital and computational ideas throughout the liberal arts. Enrollment limited to 18. Normally offered every year. M. Jadud.
DCS 103. People, Places, Prose, and Programming.
People, Places, Prose, and Programming
This course introduces digital and computational methods for the study of traditionally humanist objects, including letters, fiction, prose, maps, or other kinds of documents. The course will involve reading, critical reflection, and computer programming. Student projects will combine computer assisted methods and traditional humanities questions about authors, style, and how we understand literary works in a rich context, including historical, geographical, and cultural concerns, among others. Topics may include text analysis, topic modeling, mapping and geocoding, and network analysis (among others). This is an excellent course to explore for students new to programming. New course beginning Fall 2018. Enrollment limited to 18. Normally offered every other year. M. Jadud.
DCS 104. Data Cultures.The computational humanities are a fast-growing and exciting field that is changing the way scholars work and think. This class provides an opportunity for students to immerse themselves in semester-long projects in digital environments, moving from "analog" archives, through data structuring, and quantitative analysis, and culminating with a project that makes both the humanities and quantitative analyses legible for people from many diverse backgrounds. New course beginning Fall 2018. Enrollment limited to 18. Normally offered every other year. Staff.
DCS 202. Nature of Data, Data of Nature.This first course in data structures and data analytics is built around the collection of data from the world around us, and the analysis and visualization of those data through computational methods. Students explore the structure of data, which enables them to write increasingly complex programs. They study the analysis and presentation of data because the collection and presentation of information is a critical part of all courses of study in the liberal arts. Finally, they practice and discuss how to actively engage in both of these activites in community and collaboration with others. New course beginning Winter 2018. Enrollment limited to 24. [Q] Normally offered every year. M. Jadud.
DCS 303. Discrete Structures for Modeling.This course introduces students to the discrete structures and the methodologies used in discrete approaches to modeling socio-ecological phenomena. In developing their toolkit for systems modeling, students will explore questions about the nature of events, change, uncertainty, and interconnectedness in natural, physical, and social systems. In and out of the classroom, students will engage actively with terminology, theoretical foundations, strategies for developing and testing mathematical and computational models. That learning will then be communicated through symbolic, numeric, visual, and verbal means against the backdrop of the complex, interconnected world we experience. Prerequisite(s): DCS 202. New course beginning Fall 2018. Enrollment limited to 19. Normally offered every other year. C. Eaton.
INDC 352. Preserving the Vibration: Digitizing the Legacy of Vertamae Smart-Grosvenor.This course introduces public and digital humanities through the life and work of noted journalist, food anthropologist, and public broadcaster Vertamae Grosvenor. Public humanities is concerned with expanding academic discourse beyond academia and facilitating conversations on topics of humanistic inquiry with the community at large. Digital studies provide a plethora of unconventional ways to engage community in public dialogues for the greater good. Drawing from books, operas, NPR audio segments, interviews, cookbooks, and other artifacts of Grosvenor, students create and curate a digital archive. Themes include Gullah culture, African American migration, foodways, memoir, public memory, and monuments. Leading theories and methods of black feminism, material culture, race, food studies, new media and digital humanities are foregrounded. Cross-listed in African American studies, American cultural studies, digital and computational studies, and gender and sexuality studies. Prerequisite(s): one of the following: AA/AC 119; AA/HI 243; AAS 100; ACS 100; AC/AV 340; AC/EN 395B; AV/GS 287; GSS 100; INDS 250 or 267; REL 255 or 270. Enrollment limited to 15. M. Beasley.
DCS 360. Independent Study.Students, in consultation with a faculty advisor, individually design and plan a course of study or research not offered in the curriculum. Course work includes a reflective component, evaluation, and completion of an agreed-upon product. Sponsorship by a faculty member in the program/department, a course prospectus, and permission of the chair are required. Students may register for no more than one independent study per semester. Open to first-year students. Normally offered every semester. Staff.
DC/EC 368. Big Data and Economics.Economics is at the forefront of developing statistical methods for analyzing data collected from uncontrolled sources. Since econometrics addresses challenges in estimation such as sample selection bias and treatment effects identification, the discipline is well-suited for the analysis of large and unsystematically collected datasets. This course introduces statistical (machine) learning methods, which have been developed for analyzing such datasets but which have only recently been implemented in economic research. The course also explores how econometrics and statistical learning methods cross-fertilize and can be used to advance knowledge in the numerous domains where large volumes of data are rapidly accumulating. Prerequisite(s): ECON 255. Enrollment limited to 19. Normally offered every year. N. Tefft.
DCS s12. Community-Engaged Computing.A first course in design thinking and programming in the context of community engagement. Students—with no prior experience assumed—engage collaboratively in the iterative design and development of software applications that benefit the community in a multitude of ways. In addition to significant engagement with community partners in this development process, students communicate through multiple modes and media (writing, audio, video) about their work and their reflections on themselves and the community in which they are taking part. New course beginning Short Term 2018. Enrollment limited to 30. (Community-Engaged Learning.) M. Jadud.
This course is referenced by the following General Education Concentrations
DC/MU s13. Music in Video Games.This course is a study of how music and sound is used in interactive media, specifically video games. We will study how to compose music for video games using simple online tools and reflect on how music and sound affect our own experiences when we play games. We will also survey the brief history of video game music and the technological innovations that drove its development and explore how music and sound fit into the science of game design. New course beginning Short Term 2018. Open to first-year students. Enrollment limited to 30. B. Hansberry.
DC/MA s45T. Mathematical Image Processing.Digital image processing is a field essential to many disciplines, including medicine, astronomy, astrophysics, photography, and graphics. It is also an active area of mathematical research with ideas stemming from numerical linear algebra, Fourier analysis, partial differential equations and statistics. This course introduces mathematical methods in digital image processing, including basic image processing tools and techniques with an emphasis on their mathematical foundations. Students implement the theory using MATLAB. Topics may include image compression, image enhancement, edge detection, and image filtering. Students conceive and complete projects—either theoretical or practical—on an aspect of digital image processing. Prerequisite(s): MATH 205. Enrollment limited to 29. K. Ott.