Minor in Data Science in the Humanities

The 15-unit minor is necessarily flexible to accommodate the various backgrounds and goals of its students. The curriculum addresses data management, statistics, text analysis, geospatial analysis, digital prosopography, data visualization and information design. It entails experience in digital project work, and features a good deal of cross-disciplinary engagement. Our goal is to enrich the analytic skills that students can bring to bear on traditional and emerging topics across the humanities.
 

Course Requirements

6 units from Core Curriculum:

• IPH 3123: Introduction to Digital Humanities (3 units)
• IPH 431 Statistics for Humanities (3 units) 
• IPH 430 Data Manipulation for the Humaniteis (1 unit) 
• IPH 432 Programming for Text Analysis (3 units)

3-8 units of Directed Research via Internships

• L93 IPH 399 Internship in Digital Humanities (3-8 units)
• This course may be repeated for up to 8 credits.  Students intern on a facutly Digital Humanities research project either during the academic year or in summer through the HDW summer workshop.

6 units from Elective (below electives are those approved for Fall 2022) 

• E81 CSE 131: Introduction to Computer Science  (3 units)
• E 81 CSE 204A: Web Development (3 units)
• E81 CSE 247: Data Structures and Algorithms (3 units)
• E81 CSE 247R: SEminar: Data Structures and Algorithms (1 unit)
• L14 E Lit 313W: Bots, Drones, and Cyborgs: Being Human in the Age of Intelligent Machines (3 units)
• E81 CSE 330S: Rapid Prototype Development and Creative Programming (3 units)     
• L53 Film 337: Retro Game Design (3 units)
• L15 Drama 390: Immersive Story Studio (3 units)
• E81 CSE 457A: Introduction to Visualization (3 units)
   

L93 IPH 3123  Introduction Digital Humanities (3 units)

It is a truism that computers have changed our lives and the way we think and interact. But in fact systematic efforts to apply current technologies to the study of history and culture have been rare. This course will enable students to consider how these technologies might transform the humanities. We will explore the various ways in which ideas and data in the humanities can be represented, analyzed, and communicated. We will also reflect on how the expansion of information technology has transformed and is continuing to transform the humanities, both with regard to their role in the university and in society at large. Readings and classwork will be supplemented by class presentations and a small assigned group project.

L93 IPH 430 Data Manipulation for the Humanities (1 unit)

The course will present basic data modeling concepts and will focus on their application to data clean-up and organization (text markup, Excel, and SQL).  Aiming to give humanities students the tools they will need to assemble and manage large data sets relevant to their research, the course will teach fundamental skills in programming relevant to data management (using Python); it will also teach database design and querying (SQL).  

L93 IPH 431 Statistics for Humanities Scholars (3 units)

A survey of statistical ideas and principles.  The course will expose students to tools and techniques useful for quantitative research in the humanities, many of which will be addressed more extensively in other courses: tools for text-processing and information extraction, natural language processing techniques, clustering & classification, and graphics.  The course will consider how to use qualitative data and media as input for modeling and will address the use of statistics and data visualization in academic and public discourse.  By the end of the course students should be able to evaluate statistical arguments and visualizations in the humanities with appropriate appreciation and skepticism.

L93 IPH 432: Programming for Text Analysis (3 Units)

This course will cover the core data-scientific concepts required for analyzing large corpora of texts and will introduce basic programming together with text-analysis techniques relevant to the humanities. (There will be very slight overlap with the programming instruction in the statistics and data-management courses.)