Course Overview

The course offers an introduction to programming logic and computational tools for the social sciences graduate students. The course focus on procedures to (1) gather (2) organize and (3) present social data. The course aims to develop programming skills for handling data with academic purposes. Notice that this is not a methods, data analysis or computational social science course. The course is divided in two parts. In the first part we focus on preparing the computational enviroment, getting used with the tools and developing programming literacy in R, Git, SQL, Markdown, and other languages required in class. In the second part we apply the skills acquired in the first part to handle big datasets, webscrapping and third party APIs, digital files management for textual analysis, graphs, maps and other topics of interest.

Learning Achievement

This course aims to fill a gap _common among social science students- providing the training in data management and computational skills

Competence

Course prerequisites

Grading Philosophy

Weekly activities (50%) and a final project (50%).

Course schedule

1 - Basics of R Programming 2 - Data structures and data management in R 3 - Tables and graphs in R 4 _ R + SQL basics 5 - Git basics 6 - Markdown basics 7 - LaTex basics 8 - Webscraping 9 - Text, corpus and natural language processing 10 - Maps and GIS 11 - Networks and graphs

Course type

Online Course Requirement

Instructor

Glauco Peres da Silva, Leonardo Sangali Barone

Other information

Site for Inquiry