📖Program Curriculum
The programme starts by providing students with different backgrounds a common foundation, as well as basic knowledge in digital image analysis, which is one of the programme's two pillars. It continues with introducing basics of machine learning, which is the second pillar the programme. These two subjects define, at an early stage, the identity of the programme, which is further developed and deepened by the education on deep machine learning which also clarifies the strong link between machine learning and modern image processing and analysis. A course in ethics is included in the programme at an early stage. Courses that provide theoretical in-depth and progression towards specialisations and where the subjects image analysis and machine learning are linked together and form the programme's main area follow. Students are given a possibility to specialize within one of the following application fields where the combination of image analysis and machine learning has a central role and where they can further develop their ability to apply in practice acquired theoretical knowledge:
medical image analysis,
biomedical image analysis,
document analysis and digital humanities,
scientific visualisation,
social robotics.
In a project-based course that integrates a range of competencies and skills, such as oral and written presentation, group collaboration, problem solving, scheduling and project management, ethical considerations, students may carry out a well defined but realistic and challenging project focused on industrial needs or research. The Master's programme ends with an independent work where acquired knowledge is applied in a relevant project at a company or academic research unit.
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