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Master in Computational Social Sciences

The Master is composed of three main modules. The Social Sciences Module has a theoretical component (9 ECTS) where students will learn the foundations and possibilities of Computational Social Sciences, gain familiarity with the main behavioral theories and discuss social and ethical issues of Big Data and Artificial Intelligence; in parallel, the methodological component (12 ECTS) features courses on research design, survey methodology and social network analysis. The Statistics Module (12 ECTS) provides a key quantitative foundation, offering various courses on modeling and causal inference. Finally, the Computational Module (18 ECTS) will provide a cutting-edge set of R-based tools for data mining, analysis and visualization.

mucss

Training supplements

Introduction to Programming with R

6 ECTS

Basic Statistics

3 ECTS

First semester

Data visualization

6 ECTS

Data programming

6 ECTS

Data programming

3 ECTS

Research design for Social Sciences

3 ECTS

Foundations of Computational Social Sciences

3 ECTS

Survey research methodology I

3 ECTS

Statistics and data science I

3 ECTS

Statistics and data science II

3 ECTS

Behavioral theories in the Social Sciences

3 ECTS

Total ECTS: 33

Second semester

Survey research methodology II

3 ECTS

Data Harvesting

3 ECTS

Text mining

3 ECTS

Social Networks

3 ECTS

Advance Modeling

3 ECTS

Causal Inference for Social Science

3 ECTS

Social and ethical issues of Big Data & AI

3 ECTS

Iñaki Úcar & Margarita Torre

Master’s Thesis Seminar

3 ECTS

Master’s Thesis

6 ECTS

Total ECTS: 33