Introduction to R

About

This course offers you an interactive online learning environment using advanced pedagogical tools, and is specifically designed for advanced students, researchers, and professional analysts. The course is limited to a maximum of 16 participants, ensuring that the instructor can address the unique needs of each individual.

ECTS Credits
3 ECTS credits awarded for engaging fully in class activities.
1 additional ECTS credit awarded for completing a post-course assignment

Course leader

Akos Mate is a research fellow at the Centre for Social Sciences in Hungary. His key research area is the political economy of the European Union and its members’ fiscal governance. He uses a wide variety of methods in his research, particularly automated text analysis (and attached various machine learning approaches), network analysis and more traditional econometric techniques

Target group

Social science researchers

Course aim

The goal of this course is to make R more accessible to beginners and provide them with the skills and confidence needed to perform common analysis tasks in R. The course covers important topics such as data cleaning, exploratory data analysis, visualisation, and academic writing using RMarkdown. By the end of the course, learners should feel comfortable approaching these tasks with R.

While R has a reputation for being difficult to learn, the course aims to dispel this myth by showcasing recent developments that have made R more accessible to newcomers. By the end of the course, learners should be able to use R effectively and confidently for their data analysis needs

Fee info