Maps

The logic and methods of social network analysis. Emphasis on theoretical underpinnings and applications to sociological research.

The methods and tools of Artificial Intelligence used to provide systems with the ability to autonomously problem solve and reason with uncertain information. Topics include: problem solving (search spaces, uninformed and informed search, games, constraint satisfaction), principles of knowledge representation and reasoning (propositional and first-order logic, logical inference, planning), and representing and reasoning with uncertainty (Bayesian networks, probabilistic inference, decision theory). Graduate-level requirements include additional reading of supplementary material, more rigorous tests and homework assignments, and a more sophisticated course project. Sophisticated application and technique.

Machine learning describes the development of algorithms which can modify their internal parameters (i.e., "learn") to recognize patterns and make decisions based on example data. These examples can be provided by a human, or they can be gathered automatically as part of the learning algorithm itself. This course will introduce the fundamentals of machine learning, will describe how to implement several practical methods for pattern recognition, feature selection, clustering, and decision making for reward maximization, and will provide a foundation for the development of new machine learning algorithms.

Quantitative methods in political science and policy research are changing rapidly. The rise of the internet has brought in new sources of text, network, geographical, image, video, and other data. Meanwhile, computing storage and processing capabilities continue to expand, while data and code sharing norms have made it so that anyone with a computer and internet connection can have access to a growing set of tools and methods for modeling and interpreting patterns. This course focuses on the extraordinary work that is emerging in politics and policy as a result of these recent advances, with a broad set of applications ranging from health and defense to environmental and agricultural policy. The course highlights current trends, challenges, and new directions for political and policy researchers in academia, government, and the private sector, focusing on how these new data sources and methodologies are being used to solve problems in social science and public policy.