| Study program / study programs: Advanced data analytics |
| Degree level: Master |
| Course: Master thesis |
| Teacher: All teachers participating in the study program |
| Course status: Required |
| ECTS points: 10 |
| Prerequisites: Qualification paper |
| Course objectives: To complete master thesis, after defining the relevant area, topics and state of the art in that area through the work on the qualification paper. |
| Learning outcomes: Qualifications for conducting research. The ability to implement the required study methods and the acquired fundamental, scientific, technical and professional skills, and solve specific complex problems in the selected discipline of advanced data analytics with the use of modern computer technology and tools. |
| Course structure and content: The content of the master thesis depends on the selected topic and complies with the established standards in the field and the thesis objective(s). The thesis covers the research topics and objective(s), the initial hypotheses, research methods, description of the research and results, an overview of the thesis contributions and conclusions. |
| The number of class hours per week: Lectures: 0 Labs: 0 Workshops: 0 Research study: 0 Other classes: 3 |
| Teaching methods: After defending the qualification paper and discussing the thesis topics with the supervisor who approves the topics and objectives, the student starts to work on the thesis. During this work, the advisor conducts regular discussions with the candidate in order to learn about his/her progress, critically evaluates the progress and gives the student additional instruction in the form of guidelines or a reference to relevant literature. The supervisor also guides the student in publishing the research results. |
| Evaluation/Grading (maximum 100 points): Pre-exam requirements: 50 Oral defense: 50 |
