Machine Learning for Social Science

Utbildningsfakta

Kod: 771A42

<p>This course provides an overview of the key concepts and tools of machine learning (ML) that are relevant to social science research. First, a general introduction to ML is provided, where foundational ideas are reviewed and contrasted to those of traditional statistics. Then, central techniques in supervised learning (e.g., decision trees) and unsupervised learning (e.g., k-means) are introduced. In computer labs, students learn how to use these techniques in statistical software to solve practical problems relevant for social scientific research. Finally, the intersection between ML and causal inference will be considered.</p>

Behörighet

180 ECTS credits passed including 90 ECTS credits within one of the following areas humanities, social-, cultural-, behavioural-, natural-, computer-, or engineering-sciences 15 ECTS credits passed in one or several of the following subjects: Statistics Mathematics Computer science English corresponding to the level of English in Swedish upper secondary education (Engelska 6 or Engelska nivå 2) Exemption from Swedish

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Machine Learning for Social Science

  Linköping University

  Startdatum: 17 augusti 2026

  Slutdatum: 25 oktober 2026

  Studietakt: 50 %