NYU Shortcourse -- "Data Science and Social Science" materials
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README.md

New York University Shortcourse: Data Science and Social Science

Co-sponsored by

January 20-22, 2016

Instructors

(with materials prepared by Alex Hanna)

Teaching Assistants

  • Denis Stukal
  • Kevin Munger
  • Peter Crosta
  • Varun D N

Description

This is a three-day short course covering key topics at the intersection of Data Science and Social Science. Each day is structured as a series of modules that will combine instruction on data science methods with implementation using real data in R. his course covers an introduction to the R programming and statistical language, modeling and visualization, automated textual analysis, social network analysis, and web scraping & APIs.

Setup and Preparation

You will need to bring a laptop to all sessions of the workshop. You will need R and RStudio installed. Follow the instructions here to install both.

Instructions for using course materials on GitHub

You have three options for downloading the course material found on this page:

  1. You can download the materials by clicking on each link.

  2. You can "clone" repository, using the buttons found to the right side of your browser window as you view this repository. This is the button labelled "Clone in Desktop". If you do not have a git client installed on your system, you will need to get one here and also to make sure that git is installed. This is preferred, since you can refresh your clone as new content gets pushed to the course repository. (And new material will get actively pushed to the course repository at least once per day as this course takes place.)

  3. Most simply, you can choose the button on the right marked "Download zip" which will download the entire repository as a zip file.

You can also subscribe to the repository if you have a GitHub account, which will send you updates each time new changes are pushed to the repository.

Schedule

Day Time Topic Instructor
Jan 20 09:00-12:00 Intro to R and Data Munging Dan
Jan 20 13:30-16:30 Data Modeling and Visualization Dan
Jan 21 09:00-12:00 Automated Textual Analysis Pablo
Jan 21 13:30-16:30 Social Network Analysis Pablo
Jan 22 09:00-12:00 Web scraping & APIs Pablo
Jan 22 13:30-16:30 Research Practicum Dan