Introduction to Machine Learning for Social Sciences

About

This course is offered as part of the Radboud Summer School in Social Research Methods, in collaboration with MethodsNET (a global network that offers excellent training in social research methods).

Machine Learning is an approach where statistical models “learn” from data to make accurate predictions and decisions. In this course participants will learn the fundamentals of machine learning as a data analysis appro

Course leader

Bruno Castanho Silva Researcher Cologne Center for Comparative Politics University of Cologne

Target group

-Master
-PhD
-Post-doc
-Professional

This PhD level course is open to all researchers aiming at bringing their research to the next level. It is particularly designed for those who have some familiarity with statistics and want to be on top of the most recent developments in quantitative social sciences.

Course aim

After this course you are able to:

-Learn to define the prediction problem you are interested in
-Identify the appropriate method to approach it
-Fit and interpret different types of machine learning models
-Critically read and understand published research using machine learning

Fee info