17.835 Machine Learning and Data Science in Politics
Introduces students to politics by analyzing political science data sets with machine learning methodologies. Covers a variety of data science tools, including supervised and unsupervised learning methods, visualization techniques, text analysis, and network analysis. Emphasizes how the research methodologies can be used for studying political science. Topics include lobbying, international trade, political networks, and estimating ideologies of political leaders.
This class has 6.0001 as a prerequisite.
17.835 will be offered this semester (Spring 2019). It is instructed by I. S. Kim.
This class counts for a total of 12 credits. This class counts as a HASS S.
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© Copyright 2015 Yasyf Mohamedali