Trajectories - MSc Data Science for Food and Health
The fibre of the curriculum is formed by threads of didactic elements, lines in the curriculum design along which you progresses from basic to advanced. These so-called 'learning trajectories' are each connected to a number of learning objectives and have a minimum size, to ensure every student will attain the programme’s intended learning outcomes. You follow all of the learning trajectories. The Data Science for Food and Health programme contains four such learning trajectories:
Data Science
The Data Science learning trajectory focuses on the application of the complete data science lifecycle in the context of the Food and Health domain. You learn the main concepts and approaches of collecting, cleaning, processing and visualizing data related to the application domain Food and Health. You also learn advanced statistical techniques and to analyse structured and unstructured data of different types. You get acquainted with the potential of artificial intelligence and its relevance and suitability to design data-driven interventions. Finally, you apply data science knowledge by integrating it into food and health-related problems.
Food and Health
Within the Food and Health learning trajectory you can choose a health-related subdomain to focus on: consumer behaviour, nutrition or lifestyle. You opt from a set of domain courses, varying from intermediate to advanced level. These courses also prepare you for the thesis project of your choice.
Integration
In the Integration learning trajectory you learn to connect the disciplines of data science and the application domain. Through group work, peer learning, real-life cases and practical assignments you 'learn by doing'. You will be confronted with case studies which ask for context and user driven approaches. You will interview domain experts, make an analysis of different user groups involved and conduct a user needs assessment, so as to design interventions and solutions that are feasible and fitting. In the reflection report that is part of the internship in the second year you explicate what you have learned in the Integration learning trajectory.
Research
The Research learning trajectory prepares you for independently conducting research. The thesis-preparation courses in the first year pay attention to research methodology, while the second year offers ample opportunity for the thesis itself.
Each learning trajectory employs a diversity of learning activities, which in turn are interwoven through courses of a different character. Or, put differently, all courses integrate elements of the learning trajectories in different ways and to varying degrees. This set-up allows you (within limits) to give prominence to topics that suit your particular interests or ambitions, or that complement your previous knowledge. You will finalise the content of the four learning trajectories by choosing certain courses in consultation with your study adviser. In this process you take into account your educational background and the prior knowledge required for each course. Your selection of courses must be approved by the Examining Board.