The goal of this course is to develop the key data analytics skill sets necessary to inform evidence-based policy. Its design offers hands-on training in how to make sense of and use large scale real world heterogeneous datasets in the context of addressing real world problems. Students will learn how to scope a policy problem, understand the data generation process, how to manage, combine, and structure data, and how to create, measure and analyze the effect of different data decisions. They will also learn the basics of machine learning and visualization as well as inference, bias, privacy, and ethics issues. It is designed for graduate students who are seeking a stronger foundation in data analytics, although undergraduates with strong foundations in data and statistics will be considered for admission. The professor is a former senior White House advisor on the Federal Data Strategy and member of two White House Committees: the Advisory Committee on Data for Evidence Building and the National AI Research Resources Task Force.
The online textbook provides more information.
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