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Georgetown University


Detailed Course Information


Spring 2019
Jan 20, 2022
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PPOL 565 - Data Science II: App Stat Lng
This second course in the core data science sequence offers students an applied understanding of three key data science skills: data collection, data wrangling, and machine/statistical learning. Students will learn to gather raw data (using web scraping techniques and APIs); clean, structure, and manipulate data in a variety of formats; effectively explore and visualize data; and analyze datasets using a variety of machine learning models including regression, naive Bayes, K-nearest neighbors, decision trees and random forests, and support vector machines. Throughout the course, emphasis will be placed on effective visualization, model refinement and validation, and ethics. Students will engage with a number of policy-relevant data case studies throughout the course and will work on a policy-focused data science project.

3.000 Credit hours
3.000 Lecture hours

Levels: MN or MC Graduate
Schedule Types: Lecture, Seminar

Public Policy Department

Must be enrolled in one of the following Majors:     
      Data Science for Public Policy

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