1. The Master can make an analysis for a large-scale informatics project. He/she can identify tasks that qualify for automation, can understand underlying business processes and can determine the corresponding consumer needs. This requires the necessary knowledge for fluent communication with people working in other disciplines.
2. The Master can make a design for large-scale informatics systems. He/she can make a decomposition of a specific problem to arrive at a feasible solution. He/she can identify components that could contribute to a solution (e.g. software library, type of network, kind of database). He/she can document the chosen solutions at different levels of abstraction.
3. The Master can support the necessary evolution of informatics systems. He/she can identify problematic components, can select solution strategies, can implement the necessary adjustments without compromising the existing system’s functioning.
4. Quality control. The Master can plan the necessary check-ups while carrying out informatics projects in order to attain the previously specified quality standards (as to reliability, practicality of maintenance, safety …). He/she can draw lessons from informatics projects that have been carried out, in order to optimize quality norms wherever necessary.
5. The Master can weigh up various techniques, methods, languages, architectures, taking into account their inherent limitations and the fact that information on concrete solutions is usually commercially coloured. He/she can make strategic decisions in this respect: e.g. how do we protect our network? What type of database? What role for formal specifications? He/she can scientifically motivate the decisions that have been made.
6. The Master can report on the progress and status of computer science projects to clients (meaning non-information scientists) and experts from other fields, both orally and in writing.
7. The Master has a sense of responsibility. He/she can draw connections between social trends and developments in computer science and can assess the impact of his/her own or someone's actions. He/she has a clear image of his/her future role in society.
8. The Master can lead a team of information scientists, including (a) assessment of the necessary means (instruments, manpower, competences), (b) division of tasks on the basis of technical competences, (c) time planning of the tasks, (d) following and adjusting the planning.
Specialisation computernetworks and distributed systems
9. The Master can design algorithms and protocols for optimal usage in contemporary systems (e.g. wireless networks, cloud computing, …). He/she can also analyze such algorithms and protocols and optimize them depending on the context in which they are to be used..
10. The Master can study the behaviour of contemporary systems (performance, robustness, scalability, …) using models and simulations.
11. The Master is able to assess whether a specific mathematical model is suitable for a given situation. He/she is able to quickly make a (small) adjustment to or a variant of an existing model. He/she can abstract and model simple problems and draws the necessary inseghts and lessons from the obtained results.
Specialisation data science and artificial intelligence
12. The Master can recognize a data science problem and select the best solution strategy for it, such as data mining and machine learning techniques for the analysis of data (e.g. decision trees, association rules, bayesian networks) and data management techniques for the distributed (or not) storage, management and querying of data. He/she can apply data science techniques to large and complexely structured databases and interpret the results. He/she is also able to follow new evolutions in scientific research in data science, to appropriate these and to contribute to them.
13. The Master has extensive knowledge of and expertise in the application of artificial intelligence techniques, such as self-learning systems and artificial neural networks. He/she recognizes situations in which these techniques can be applied (e.g. image processing), and is able to implement a solution and correctly evaluate it. He/she also has a broad theoretical basis that enables him/her to follow and critically evaluate scientific research in artificial intelligence.
14. The Master can select the best database model and the optimal query technique for data intensive applications. He/she can use recent database technology (e.g., distributed and heterogenous databases) inzetten where necessary. He/she has extensive knowledge of the foundations of databases that can be used in developing new techniques and applications.
Specialisation software engineering
15. The Master uses model to describe and quantify all aspects of a computer system. He/she has an overview of the most current modellingformalisms and their main characteristics (pro and cons, specific area of application, ....). He/she has applied some of them in designing a new system and in the analysis or improvement of an existing system. He/she is able to use these models for communication with people active in other disciplines.
16. The Master has experience in available tools for analysis, verification, simulation and transformation of software systems. He/she has insight in their internal workings, which manifests itself in the successful combining, modifying or building of such tools (e.g. making extensions on open-source instruments).