Academics

Data Science for Public Policy

Course Number: GAFL 531

Course Overview

In the 21st century, “Big Data” surround us. Data are being collected about all aspects of our daily lives. To improve transparency and accountability, an increasing number of public organizations are sharing their data with the public. But data are not information. You need good information to make sound decisions. To be an effective public leader, you will need to learn how to harness information from available data.

This course is designed to expand upon core concepts in data management and analysis that you learned in GAFL 640: Program Evaluations and Data Analysis. This course will introduce you to key elements of data science, including data transformation, analysis, visualization, and presentation. An emphasis is placed on manipulating data to create informative and compelling analyses that provide valuable evidence in public policy debates. We will teach you how to present information using interactive apps that feature software packages. As in all courses at Fels, we will concentrate on more practical skills than theoretical concepts behind the techniques.  

Course Structure

The course proceeds in four sections. The first section reviews data visualization in R. The second section introduces tools of data management, storage, and manipulation. The third section presents descriptive and predictive data mining techniques to identify patterns in data. The final section exposes students to Shiny, a web application program in R. R-Shiny apps are interactive visualizations of data. The apps help to present the most important relationships or findings to diverse audiences (after the long, hard work of cleaning, managing, and analyzing a dataset!).

Semesters Offered

Instructor: Nelson Lim
Course Section: 001
On-Campus Day(s): Tuesday
On-Campus Time: 2:00pm-5:00pm
Course Description:

Course Overview

In the 21st century, “Big Data” surround us. Data are being collected about all aspects of our daily lives. To improve transparency and accountability, an increasing number of public organizations are sharing their data with the public. But data are not information. You need good information to make sound decisions. To be an effective public leader, you will need to learn how to harness information from available data. 

This course is designed to expand upon core concepts in data management and analysis that you learned in GAFL 640: Program Evaluations and Data Analysis. This course will introduce you to key elements of data science, including data transformation, analysis, visualization, and presentation. An emphasis is placed on manipulating data to create informative and compelling analyses that provide valuable evidence in public policy debates. We will teach you how to present information using interactive apps that feature software packages. As in all courses at Fels, we will concentrate on more practical skills than theoretical concepts behind the techniques.  

Course Structure

The course proceeds in four sections. The first section reviews data visualization in R. The second section introduces tools of data management, storage, and manipulation. The third section presents descriptive and predictive data mining techniques to identify patterns in data. The final section exposes students to Shiny, a web application program in R. R-Shiny apps are interactive visualizations of data. The apps help to present the most important relationships or findings to diverse audiences (after the long, hard work of cleaning, managing, and analyzing a dataset!). 

Data Science for Public Policy Fall 2016 On-Campus
Instructor: Nelson Lim
Course Section: 001
Day(s): Monday, Wednesday
Time: 10:00am-11:30am
Course Location: On-Campus
Course Description:

TBA

Social Media

Facebook
Twitter
LinkedIn
Flickr

Contact Information

Fels Institute of Government
University of Pennsylvania
3814 Walnut Street
Philadelphia, PA 19104

Phone: (215) 898-2600
Fax: (215) 746-2829

felsinstitute@sas.upenn.edu