Analysis of course co-enrollment at the Faculty of Computer and Information Science

Network analysis and consequently numerous network measurements allow an insight into the characteristics of network and therefore have an important role in its understanding. In this thesis the analysis of the professional and masters study programme of the Faculty of Computer and Information Science is conducted. The purpose is to find groups of courses based on how the students co-enroll them. We have achieved this by using five already established approaches intended for revealing characteristic groups in a network and with the help of widely-accessible software tools such as Gephi, Visone and Pajek. For revealing groups we use the approaches for core-periphery structure, modularity optimization, label propagation, blockmodeling and stochastic blockmodeling. The results obtained with the introduced approaches are compared and, in the last part of the thesis, we provide the interpretation of those we find interesting and useful from our point of view. Courses of a particular study module or courses of instructors from the same laboratory are not assigned to just one of the groups, but they do, however, get close in some cases