RSS02.E6 Introduction to Machine Learning for Social Sciences
From customer-recommendation systems to policy design and implementation, machine learning algorithms are ubiquitous in a big data world. Their potential is now being explored in the social sciences.
In this course participants will learn the fundamentals of machine learning as a data analysis approach for social sciences, and will have an overview of the most common and versatile classes of ML techniques in use today.
The goal is that at the end participants will be able to identify what kind of technique is more suitable for their question and data, and how to design, test and interpret their models. They will also be equipped with sufficient basic knowledge to proceed independently for more advanced applications.
This is an introductory course for those who are comfortable with social science statistics but have no background in machine learning or computer science.
|26 June 2023 - 30 June 2023|
Early Bird Regular: €895 (application deadline* April 1st)
|Scholarships and discounts||Find more information here|
*Your application is only completed when the course fee has been paid
|Course leader||Jens Wäckerle|
|Level of participant||
|Admission requirements||Participants should be familiar with linear and logistic regression, and have a working knowledge of R (how to open and manipulate data, and to run models/regressions).|
|Mode of Study||On Campus|
|ECTS||2 or 4 Find more information here|