PSCI131 - American Foreign Policy

Status
O
Activity
LEC
Section number integer
1
Title (text only)
American Foreign Policy
Term
2022A
Subject area
PSCI
Section number only
001
Section ID
PSCI131001
Course number integer
131
Registration notes
Registration also required for Recitation (see below)
Meeting times
TR 05:15 PM-06:15 PM
Meeting location
ANNS 110
Level
undergraduate
Instructors
Dominic R Tierney
Description
This course analyzes the formation and conduct of foreign policy in the United State. The course combines three elements: a study of the history of American foreign relations; an analysis of the causes of American foreign policy such sa the international system, public opinion, and the media; and a discussion of the major policy issues in contemporary U.S. foreign policy, including terrorism, civil wars, and economic policy.
Course number only
131
Use local description
No

PSCI107 - Intro To Data Science

Status
C
Activity
REC
Section number integer
203
Title (text only)
Intro To Data Science
Term
2022A
Subject area
PSCI
Section number only
203
Section ID
PSCI107203
Course number integer
107
Registration notes
Permission Needed From Instructor
Registration also required for Lecture (see below)
Meeting times
F 10:15 AM-11:15 AM
Meeting location
BENN 16
Level
undergraduate
Instructors
Marc Trussler
Description
Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.
Course number only
107
Fulfills
College Quantitative Data Analysis Req.
Use local description
No

PSCI107 - Intro To Data Science

Status
C
Activity
REC
Section number integer
202
Title (text only)
Intro To Data Science
Term
2022A
Subject area
PSCI
Section number only
202
Section ID
PSCI107202
Course number integer
107
Registration notes
Permission Needed From Instructor
Registration also required for Lecture (see below)
Meeting times
R 12:00 PM-01:00 PM
Meeting location
WILL 220
Level
undergraduate
Instructors
Marc Trussler
Description
Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.
Course number only
107
Fulfills
College Quantitative Data Analysis Req.
Use local description
No

PSCI107 - Intro To Data Science

Status
O
Activity
REC
Section number integer
201
Title (text only)
Intro To Data Science
Term
2022A
Subject area
PSCI
Section number only
201
Section ID
PSCI107201
Course number integer
107
Registration notes
Permission Needed From Instructor
Registration also required for Lecture (see below)
Meeting times
R 08:30 AM-09:30 AM
Meeting location
PCPE 202
Level
undergraduate
Instructors
Marc Trussler
Description
Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.
Course number only
107
Fulfills
College Quantitative Data Analysis Req.
Use local description
No

PSCI107 - Intro To Data Science

Status
O
Activity
LEC
Section number integer
1
Title (text only)
Intro To Data Science
Term
2022A
Syllabus URL
Subject area
PSCI
Section number only
001
Section ID
PSCI107001
Course number integer
107
Registration notes
Permission Needed From Instructor
Registration also required for Recitation (see below)
Meeting times
MW 01:45 PM-02:45 PM
Meeting location
PCPE AUD
Level
undergraduate
Instructors
Marc Trussler
Description
Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.
Course number only
107
Fulfills
College Quantitative Data Analysis Req.
Use local description
No

PSCI010 - Race Crime & Punishment

Status
O
Activity
SEM
Section number integer
401
Title (text only)
Race Crime & Punishment
Term
2022A
Subject area
PSCI
Section number only
401
Section ID
PSCI010401
Course number integer
10
Registration notes
Course is available to Freshmen.
Freshman Seminar
For Freshmen Only
Meeting times
T 01:45 PM-04:45 PM
Meeting location
DRLB 2N36
Level
undergraduate
Instructors
Marie Gottschalk
Description
Freshmen seminars are small, substantive courses taught by members of the faculty and open only to freshmen. These seminars offer an excellent opportunity to explore areas not represented in high school curricula and to establish relationships with faculty members around areas of mutual interest. See www.college.upenn.edu/admissions/freshmen.php
Course number only
010
Cross listings
AFRC012401
Fulfills
Cultural Diversity in the US
Use local description
No

PSCI010 - Authoritarian Politics Through Films

Status
O
Activity
SEM
Section number integer
301
Title (text only)
Authoritarian Politics Through Films
Term
2022A
Syllabus URL
Subject area
PSCI
Section number only
301
Section ID
PSCI010301
Course number integer
10
Registration notes
Course is available to Freshmen.
Freshman Seminar
Meeting times
W 01:45 PM-04:45 PM
Meeting location
PCPE 350
Level
undergraduate
Instructors
Yue Hou
Description
Freshmen seminars are small, substantive courses taught by members of the faculty and open only to freshmen. These seminars offer an excellent opportunity to explore areas not represented in high school curricula and to establish relationships with faculty members around areas of mutual interest. See www.college.upenn.edu/admissions/freshmen.php
Course number only
010
Fulfills
Cross Cultural Analysis
Use local description
No

PSCI995 - Dissertation

Status
O
Activity
DIS
Section number integer
40
Title (text only)
Dissertation
Term
2021C
Subject area
PSCI
Section number only
040
Section ID
PSCI995040
Course number integer
995
Level
graduate
Instructors
Tariq Thachil
Course number only
995
Use local description
No

PSCI995 - Dissertation

Status
O
Activity
DIS
Section number integer
1
Title (text only)
Dissertation
Term
2021C
Subject area
PSCI
Section number only
001
Section ID
PSCI995001
Course number integer
995
Level
graduate
Instructors
Matthew Levendusky
Course number only
995
Use local description
No

PSCI498 - How Int'l Cooperation Wk: How International Cooperation Works

Status
O
Activity
SEM
Section number integer
301
Title (text only)
How Int'l Cooperation Wk: How International Cooperation Works
Term
2021C
Subject area
PSCI
Section number only
301
Section ID
PSCI498301
Course number integer
498
Meeting times
T 12:00 PM-03:00 PM
Meeting location
PCPE 225
Level
undergraduate
Instructors
Julia C Gray
Description
Consult department for detailed descriptions. Recent topics include: Globalization; Race & Criminal Justice; Democracy & Markets in Postcommunist Europe.
Course number only
498
Use local description
No