Artemis is an interactive learning platform developed as an open-source project at the Technical University of Munich. The learning management system allows organizing courses, hosting lecture content and interactive exercises, conducting exams, and creating automatic assessments with individual feedback. Research shows that every student is outfitted with a unique set of capabilities, previous experiences, and expectations. Treating all students in a course as one entity falls short of this observation. In traditional classroom settings instructors aspire to design a personal learning experience for every student. In Artemis, an instructor currently has no choice other than assigning the same exercises and applying the same static lecture schedule to all students in the course. This thesis solves the described problem by proposing an Adaptive Learning system for Artemis. Instructors are thereby enabled to provide an individual learning experience for every student in their class, even in massive open online courses. After motivating the problem and objectives, we give an overview on competency-based education and adaptive learning. We then present related work before proposing our adaptive learning system by compiling requirements and outlining scenarios as well as use cases. Afterwards, we explicate our system design using numerous models and thereafter discuss selected implementation details. Finally, we summarize our contributions and give an outlook into future work.