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The »Introduction to
R for Data Analytics and Computational Social Science« offers a complete
introduction to the R programming language for data science and computational
social science. Taking this course students will learn how to:
· - Setting up and handling the RStudio IDE.
· - Import, transform, visualize, and model data;
· - Recognize and handle common data structures;
· - Setup a reproducible data science project;
· - Communicate effectively a project’s insights;
· - Automating common tasks to minimize errors and
time loss.
Data literacy is
increasingly required in business, technology, and academic work because data
is everywhere. R is the lingua franca of data science for its powerful
and easy-to-use tools for statistical analysis and data visualization.
This course is designed
for master’s students specializing in a quantitative-oriented or
computational social science program. No prior experience or knowledge in
data analysis and programming is required. However, students must be curious
and animated by an intrinsic motivation to learn R and data science. The
teaching style is hands-on and participative: instructive phases, which
usually consist of live coding, alternate with individual phases that enable
the participants to deepen their learning and insights. A passive »sit and
listen« attitude is discouraged since this typically undermines effective and
durable learning.
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