Learning Outcomes
Our world and in particular professional life are increasingly governed by data. Due to steadily amount, complexity, and importance of data, properly dealing with data has emerged as one, if not the most important competency today - basically regardless of business domain. This course will cover a “tool box” of methods for dealing with data and information, following the information life cycle. This includes approaches to collect data (e.g., by surveys, experiments, web crawling techniques), structuring and pre-processing (e.g., filtering, clustering), data visualization (e.g., static, online, networks), as well as analytical methods (network analysis). Moreover, the course covers fundamental statistical questions and applies the learned content directly within tools such as Java and R. The covered content is complemented and practically recapitulated by means of case studies and data-based examples. Moreover, the course is accompanied by guest lectures from practice. As a result, the course’s participants will learn to independently design and implement data-based projects.
