From 25 to 29 November 2019, Matheus E. Leusin attended the doctoral course "An applied introduction to machine learning for social science and humanities scholars" at Aalborg University in Denmark. The course offered some useful insights into the concepts and fields of application in the context of data science, taking into account different data types.

Given the growing importance of "Big Data" in the course of increasing data availability of websites, social media and electronic applications, the possibilities to make this data usable for science are growing. At the same time, increasing computing power and algorithms of artificial intelligence offer the possibility of adequately recording and analyzing vast volumes of data. The doctoral course specifically covered the topics "Exploratory Data Analysis" and "Unsupervised Machine Learning," "Network Analysis," "Block Modelling," "Text as Data" and "Web Scraping".

Matheus E. Leusin is a member of the Diginomics group of the Faculty of Business Studies and Economics at the University of Bremen. His research focuses on the worldwide development and dissemination of artificial intelligence based on patent and publication data. He will use the knowledge gained in the doctoral course for text analysis of patents and publications, e.g., by Natural Language Processing. Likewise, the methods taught in the course will allow him to analyze future patent and publication behavior, e.g., by supervised machine learning. In addition, his advanced knowledge of methods in the field of web scraping allows him to generate new data from sources that have not been systematically accessible so far.