MSc in Computing Science

Students in Computing Science learn to analyse and develop the concepts, design methods, and techniques underlying all aspects of modern information and software systems, in order to understand their possibilities and limitations and to apply them in practice.

The programme covers the whole spectrum from software technology to algorithmic modelling and applications design, and provides you with excellent ways to specialize in the design issues and complexities of competitive information systems and their application. Algorithmic models are crucial in many sciences, in order to achieve better decision-making and information handling in many branches of industry and business and in many organizations in society. (See also MSc program Computing Science.)

Study lines in the MSc programme

You will spend a little over a year (5 periods) on the courses, seminars or small projects. In addition you will participate in the colloquium series of the groups to broaden your view of the discipline. After the first block of the second year you will be prepared for the final MSc Thesis project. Projects can be done either in-house or with another party in science or industry. As a graduate of the Computing Science programme, you perfectly qualify for research positions at universities and in science labs in computer science and in interdisciplinary research, and for IT careers in industry.

Every MSc-student must have his/her MSc programme approved by the programme`s graduate student advisor ( see below ) before starting in Computing Science. Every programme must satisfy the requirements of the `onderwijs- en examenreglement' of the MSc curriculum.

Your studies in the MSc programme Computing Science

• Core courses in a specific area of the programme, with every course for 7.5 ects, as indicated in the following guideline for sample study lines (tentative):
  • Programming technology: Advanced functional programming, Compiler construction, Automatic program analysis, Generic programming, Program verification.
  • Algorithm design and complexity: Algorithms and networks, Algorithmic computational biology, Intelligent agents, Scheduling and time-tabling, Simulation.
  • Advanced planning and decision making: Algorithms and networks, Evolutionary computing, Probabilistic Reasoning, Scheduling and time-tabling, Simulation.
  • Algorithmic data analysis (`Big data`): Advanced data mining, Multimedia retrieval, Geographic data processing, Pattern recognition, Queries and retrieval
    Note: these study lines are guidelines. Your actual study line may differ and may be based on a different core set e.g. in case of a well-motivated study line that you propose yourself. Your actual study line must be approved by the graduate student advisor before you start in the programme.
• Colloquium (5 ects): during your two-year MSc program you have to attend at least 30 meetings of the colloquium series of the programme.
  • In the Computing Science Colloquium series, regular presentations are given by MSc students, PhD students, scientific staff and (research-)visitors on current issues and results in Computing Science research. Talks can vary from official lectures, try-outs for conferences, a literature study, or just trying out a half baked idea. Attendance is registered.
• Experimentation project(s) (7.5 or 15 ects): optional. The goal of an experimentation project is to carry out a small, individual project in modelling, design or experimentation on an interesting research problem from theory or practice.
• Electives: further courses from the following list of courses offered in 2011-2012 including e.g. (tentative):
  • block 1: Advanced data Mining, Generic Programming, Intelligent agents, Multimedia retrieval, Probabilistic Reasoning.
  • block 2: Advanced functional programming, Evolutionary computing, Pattern recognition, Queries and retrieval.
  • block 3: Algorithms and networks, Compiler construction, Geometric algorithms, Multi-agent programming, Simulation, Seminar `Dependently Typed Programming'.
  • block 4: Algorithmic computational biology (Seminar), Automatic program analysis, Geographic data processing, Scheduling und time-tabling, Seminar `Programming language implementation/Type checking'.
  • all blocks: (experimentation-)projects (after your first two blocks)
  • And/or some suitable courses (as electives) from other MSc programmes of the Department (some are included above), an independent study, and/or up to two courses from outside of the CS programme (e.g. in biology, business, etc).

  NB: the cursory part must add up to a total of at least 75 ects (e.g. ten courses including core courses, electives, seminars and/or projects). Normally up to two courses (15 ects) per block are followed: core, elective or project. students who begin the program in 2011: the 5th period is normally (partly) devoted to experimentation projects, seminars and/or capita selecta as preparation of your MSc project.

• MSc research project in Computing Science (45 ects pnts, only after all cursory parts are completed and including the colloquium requirement): in the department or in a company. We offer many possibilities for MSc research, e.g. in the following areas, provided you take the right preparatory study line in the programme:
  • algorithmic data analysis,
  • algorithmic systems,
  • decision support systems,
  • software technology,
  • novel themes in neighboring areas,

• Course Schedule: see the education pages of the department.

• Graduate student advisor (Computing Science): Dr Ad Feelders, with Dr Wishnu Prasteya.

Further links

• MSc programme: Computing Science.
• Graduate School of Natural Sciences and its MSc programmes
• Center for Algorithmic Systems.

Last modified: 2012