This page contains the materials and resources posted by the instructors for the classes taught from June 5-9, 2017. A few resources will be updated by Friday June 2, 2017. 

Introduction to Python Data Analytics

Please follow the prerequisites in PDF for installation of necessary tools for this class. The class outline is described here.

The course materials can be downloaded from this link. The lectures slides are here.

Introduction to R

Participants need to come to the class to with working installations of R, RStudio and RTools (for Windows) in order to be ready to code in the class.

The other packages used for the class are: Tidyverse. The book that will be used for the class is R for Data Science. The course materials can be downloaded from this zip file. The updated slides can be downloaded from here.

Download Software: R; RStudio; RTools

​Geovisualization 

Any text edit (something like Sublime Text or Atom) and web-browser is all that is needed for this course. Caglar has put up a website for the participants of this course. Please click here to visit the website.

Social Media Analytics with Python

Please follow the prerequisites in PDF for installation of necessary tools for this class.

The class outline can be downloaded from here. The lectures slides can be downloaded from here. The Jupyter Notebook file can be downloaded from here.

Network Analysis Using R

The prerequisites for this class are a working installation of R, RStudio. The R script and Jupyter notebook can be downloaded from here (networksinR_v2.R and networksinRCode.ipynb). The lecture slides are here