This course introduces the use of computational methods for studying culture and society. We will learn how to transform textual and visual material into data, and how we can explore and analyze this data using machine learning and statistical models as both quantitative and qualitative tools. We will also survey and discuss how these methods are applied within the humanities and social sciences, as well as reflect on the challenges, limitations, and ethical issues that arise in the computational study of culture and society. This course counts as an Elective toward the INFORM major.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

This course is an introduction to the concepts and skills involved with the collection, management, analysis, and presentation of data sets and the data products that result from the work of data scientists. Privacy, algorithmic bias and ethical issues are also discussed. Students will work with data from the financial, epidemiological, educational, and other domains. The course provides many examples of real-world data that students work with using various software tools.

This course is an introduction to the concepts and skills involved with the collection, management, analysis, and presentation of data sets and the data products that result from the work of data scientists. Privacy, algorithmic bias and ethical issues are also discussed. Students will work with data from the financial, epidemiological, educational, and other domains. The course provides many examples of real-world data that students work with using various software tools.

The course will cover the technical foundations and use of today's communication networks, particularly the internet. It will also address key social, policy, economic, and legal aspects of these networks, their use (and abuse) and their regulation. This course covers computer science topics, but all material will be presented in a way that is accessible to an educated audience with or without a strong technical background. This course is not intended for Computer Science majors or minors; students interested with a major or minor-level treatment of this material should see COMPSCI 453.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.