Introduction to Computational Tools for Social Science
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01_Introduction
02_Unix-Bash
03_r-basics
04_r-data-analysis
05_r-visualization
06_APIs
07_html-css-javascript
08_webscraping
09_qualtrics-mturk
10_python-basics
11_FINAL PROJECTS
12_text-analysis-python
13_text-analysis-r
14_machine-learning
15_best-practices
.DS_Store
.gitignore
A_Syllabus.md
B_Install.md
C_final-projects.md
README.md

README.md

PS239T

Introduction to Computational Tools for Social Science

This course will provide graduate students the technical skills necessary to conduct research in computational social science and digital humanities, introducing them to the basic computer literacy, programming skills, and application knowledge that students need to be successful in further methods work.

The course is currently divided into four main sections. In the first section, students learn how their computers work and communicate with other computers using git and bash. In the second, we turn our attention to the structure, analysis, and visualization of data, with an emphasis in R. In the third, students learn applications to collect new data (e.g., using APIs and webscraping). In the fourth, students learn additional means of analyzing and visualizing data, including tools like text analysis and machine learning.

Please note that materials are still in development, and will be changing.

Contact

Instructor: Rachel Bernhard: rbernhard@berkeley.edu