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Course details 2012-2013  
Important notice on language
This programme is mainly taught in Dutch.
Our English programme Master of Computer Science can be found here.

Qualification awarded
In order to obtain the degree of Master of Science in Computer Science the student
  • should be enrolled for the programme in question under a diploma contract or under an exam contract to obtain a diploma
  • should have taken all the exams that the programme encompasses
  • should previously have registered for the programme with the examination board.
  • should have acquired at least 120 ECTS-credits
The programme consists of 120 ECTS-credits.
In a model academic year, the student takes between 54 and 66 ECTS-credits.
Admission requirements

Direct: academic bachelor in information sciences, computer science or engineering sciences: computer science.

With preparatory programme: academisch bachelor of Mathematics, Physics, Industrial Sciences and Engineering Sciences (Architecture, Chemical and Materials Engineering, Chemical Engineering, Civil Engineering, Electrical Engineering, Electromechanical Engineering, Engineering Physics, Geotechnical and Mining Engineering, Materials Engineering, Mechanical Engineering)

Objectives and learning outcomes
A degree in Computer Science at the University of Antwerp corresponds with competent computer scientists with a scientific background. After obtaining the degree such students will be able to (a) adopt new technological developments in the respective disciplines within computer science; (b) exploit these developments where applicable in their professional context; (c) when required, make original contributions to the further development of the discipline.
Analysis for large-scale informatics projects. Identifying tasks that qualify for automatization, understanding underlying business processes, determining the corresponding consumer needs. This requires the necessary knowledge for fluent communication with people working in other disciplines.
Design of large-scale informatics systems. Abstraction and decomposition of the specific problem to arrive at a feasible solution. Identifying components that could contribute to a solution (e.g. software library, type of network, kind of database). Documenting the chosen solutions on different levels of abstraction.
Restructuring existing informatics systems. Identifying problematic components, selecting solution strategies, implementing the necessary adjustments without compromising the existing system’s functioning.
Quality control. Planning 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 …). Drawing lessons from informatics projects that have been carried out, in order to optimize quality norms wherever necessary.
Selecting techniques, methods, languages, architectures, taking into account their inherent limitations and the fact that information on concrete solutions is usually commercially coloured. Making strategic decisions in this respect: e.g. how do we protect our network? What type of database? What role for formal specifications? Scientific motivation of the decisions that have been made.
Reporting the progress and status of informatics projects to clients (meaning non-information scientists) and experts from other fields, both orally and in writing.
Leading a team of information scientists, including (a) assessment of the necessary means (time, budget, 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.
What does it meen for a master to be “scientifically trained”?
Has theoretical and practical experiences with instruments, techniques and methods used in scientific research of a specific subfield of information sciences.
Research and development in a product-oriented environment.
This means (a) being able to set up experiments to determine if certain techniques are usable for a company; (b) recognising opportunities to improve products and production processes; (c) estimate costs/benefits of new techniques and methods; (d) using new techniques to gain an strategic advantage over the competition.
Fundamental research. Have the necessary skills needed to independently start scientific research, for instance in order to obtain a PhD. This means (a) having insight in current research questions within a subfield of Information Sciences; (b) being able to see the implications of recent research results; (c) being able to independently apply publicised results or techniques in a new context.
Access to further studies
Further studies with direct access
Master of Statistical Data Analysis,  Information Management, Project Management
Specific Teacher Training

Further studies with conditional access
Master of International Relations and Diplomacy

Final examination
A student’s final result is a weighted average of the exam results the student has obtained for all the programme components of his/her training programme. In calculating the final result, the credits corresponding to the various programme components are used for weighting the results obtained for those components.

The final result is expressed as an integer out of 100.

A student whose final result is less than 50 out of 100 can never be declared successful.

A student is successful for the training programme if he/she has obtained credits for all the programme components in his/her training programme. 
For more information see the Education and Examination regulation.
ECTS co-ordinator

Prof. dr. B. Goethals,