Curriculum for Digital Humanities Degree

There is a difference between what science is, its history and meaning, and what science does through experimental and applied practices. This interdisciplinary course invites students to examine how scientific knowledge is defined, constructed, and communicated. Students will critically analyze different examples of science in society to understand how science shapes and is shaped by culture, power, and people. By the end of the course, students will be equipped to evaluate the ways in which science reflects and transforms the world around us.

This course introduces students to the notion of creative work as knowledge work-unique ways of understanding the world through the arts, design, humanities, and media. Drawing on diverse creative work, including their own, students will explore the potential for varied creative practices and tools to make meaning and how systems-political, economic, cultural-influence what people can make and whether it holds value. Students will also learn to apply critical frameworks in examining the world of creative expression and cultural production.

How does technological change impact people across the globe? What gets lost-or found-in translation? Through interdisciplinary analysis, this course examines technological change as a global phenomenon. We will examine how innovations from one perspective can be exploitative from another, investigating how technologies evolve and affect each other across different times and places. The course emphasizes ethical inquiry and considers how the economic, political, and cultural forces driving technological change affect people's lives differently depending on context, identity, and access. Students will leave with a deeper understanding of how science and technology shape and are shaped by the world.

In this course, students will examine how historical forces have influenced the emergence of creative technologies and cultural production. They will learn to apply critical frameworks, including theories, to explore how power structures have intersected with popular appeal to alternately foster and limit creative innovation and expression. Students will also explore the dynamic nature of global culture, investigating how aesthetic ideas and creative practices have developed, spread, and influenced artists and creative production over time.

This course equips students with interdisciplinary tools and methods to analyze and respond to complex, real-world problems. Drawing on diverse frameworks and theories, students will explore how their own identities and experiences shape their understanding of contemporary issues. Emphasis is placed on synthesizing knowledge across fields to develop innovative, contextually relevant solutions. Students will communicate their insights effectively through a range of expressive modes tailored to varied audiences and purposes.

The course provides students with opportunities to develop specialized projects in art, humanities, and media production. Students will apply critical frameworks, including theories, and use interdisciplinary methods to explore how culture is shaped by popular appeal, innovation, and mechanisms of power. Students will work individually and collaboratively to bring creative work-narratives, images, multimedia forms-and rigorous scholarship to complex challenges in varied contexts.

Data visualization-representing complex data in a visual format-is a way to communicate and explore patterns, trends, and relationships in a data set. In this course, students will examine a variety of data sets to create data visualizations and use them to explore, interpret, and present information. After transforming data sets into visual graphics, students will then create business reports and presentations designed to drive effective decision-making.

This course introduces students to data mining and its various applications. Students will gain proficiency in supervised data mining techniques for building prediction models such as decision trees, random decision forests, bootstrapping, training and testing using multi-fold cross-validation and using entropy measures for weighting features. Students will also use unsupervised data mining techniques such as clustering and association analysis. Both methods are used for discovering patterns and associations in data.