90-866 Large Scale Data Analysis for Public Policy
6 units, Carnegie Mellon University
The past decade has seen the increasing availability of very large scale data sets arising from the rapid growth of transformative technologies such as the Internet and cellular telephones along with the development of new and powerful computational methods to analyze such datasets. Such methods developed in the closely related fields of machine learning data mining and artificial intelligence provide a powerful set of tools for intelligent problemsolving and datadriven policy analysis. These methods have the potential to dramatically improve the public welfare by guiding policy decisions and interventions and their incorporation into intelligent information systems will improve public services in domains ranging from medicine and public health to law enforcement and security. This course will provide a basic introduction to large scale data analysis methods focusing on three main problem paradigms prediction modeling and detection. Students will learn how to translate policy questions into these paradigms choose and apply the appropriate artificial intelligence and machine learning tools and correctly interpret evaluate and apply the results for policy analysis and decision making. We will emphasize tools that can scale up to realworld policy problems involving reasoning in complex and uncertain environments discovering new and useful patterns and drawing inferences from large amounts of structured highdimensional and multivariate data. No previous knowledge of artificial intelligence or machine learning is required. Note this course was previously listed as Artificial Intelligence Tools for Policy and is not open to students who have previously taken 90866.
Prerequisites: (90-707 (min C) or 95-796 (min C) or 90-777 (min C) or 90-711 (min C)) and (94-842 (min C) or 90-812 (min C) or 95-888 (min C))
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