Office of the Registrar
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Organization, Regulations, and Courses 2021-22

QSS 30.11 Applied Machine Learning for Social Science

Machine learning is a framework for modeling data, where patterns encoded in a data are "learned" by a model. These patterns are sometimes used to make predictions about data that the model has not yet "seen." The amount of data available to social science researchers has exploded in recent years. Advances in machine learning have given social scientists new tools to make sense of these data to answer big and important questions.

This course will introduce the theoretical foundations of machine learning, statistical inference, and prediction; explore the many applications of statistical machine learning to social science research, and examine the broader social impacts of algorithms and machine learning on contemporary politics and society.

Distributive and/or World Culture


The Timetable of Class Meetings contains the most up-to-date information about a course. It includes not only the meeting time and instructor, but also its official distributive and/or world culture designation. This information supersedes any information you may see elsewhere, to include what may appear in this ORC/Catalog or on a department/program website. Note that course attributes may change term to term therefore those in effect are those (only) during the term in which you enroll in the course.