In recent years Machine Learning has started to influence all aspects of human life, and education is no exception. In this seminar course, we will introduce basic concepts of machine learning and education and learn how Machine Learning is employed nowadays to solve day-to-day problems, which are the most common in higher education. The problems include data manipulation, feature engineering, drop-out prediction and visualisation of student characteristics. Students will learn basics of Machine Learning using one of the most prominent Data Science languages R in the context of higher education data. To pass, students must finish all tasks and submit a short essay/state-of-the-art evaluation (1000 - 1500 words) on the selected topic from a given list.
- Kursverantwortliche/r: Jakub Kuzilek
- Kursverantwortliche/r: Clara Schumacher
- Kursverantwortliche/r: Prof. Dr. Raphael Zender