During cybersecurity training, the trainees practice their skills by solving various tasks in a command-line interface. Logging and analyzing the commands submitted by the trainees can reveal interesting insights about their learning processes. The goal of this thesis is to explore patterns that occur during cybersecurity training, such as approaches to solving the tasks, frequently used tools, and trainees’ misconceptions. In the theoretical part of the thesis, the student will provide an overview of the background and related work. In the practical part, the student will apply two data mining methods, association rule mining and sequential pattern mining, to logs from cybersecurity training. The input data will be command-line logs in a pre-defined textual format. The student will use Python and SPMF tool to discover association rules and sequential patterns in the data. Finally, the student will interpret the output, visualize it, and discuss the educational significance of the results.