A profile can be chosen as part of your study programme to expand the thematic range of your Master's programme. A profile is a coherent set of courses totaling 30 study points. The courses are on a single theme that is usually not a standard part of your Master's programme. The 30 study points that comprises the profile can be done as part of the total 120 study points of your Master's programme.

To incorporate a profile into a Master's programme without compromising the essential content of the programme, master's programmes have a separate set of rules for elective courses when a profile is chosen. These are listed in the programme annex of the Education and Examination Regulations. They apply only when the chosen profile is actually completed successfully by the student, otherwise the standard elective rules apply.

Before choosing a profile, you are advised to discuss this with your Programme Coordinator. Students are free to chose a profile as a part of any Master's programme, but special admissions conditions may apply. Please check the individual profile pages below.

The Educational Profile (30 EC) can be taken as part of your GSNS master’s programme. If you are passionate about sharing your knowledge, and you would consider a career as a teacher in secondary education, this profile might be right for you.

A major feature of the profile is the emphasis on practitioner skills and school-based activities. Throughout the programme, learning theories and teaching methods will be taught closely linked to your day to day work in the classroom. This programme is tailored to meet the professional development needs of teachers in the early stages of their careers. 

The total number of EC of each master's programme will NOT be increased by completing the Master's Educational Profile.

If you have already completed an ‘educational minor’, or if you obtained a second degree (i.e., a limited teacher degree allowing you to teach until 9th grade) in teaching elsewhere, your educational profile will lead to a first degree teacher certificate. This allows you to teach secondary and higher education (excluding university level, of course). The Educational Profile will comprise of the following courses:

Start September 2018

  • Teaching Practice 2 (15 EC, GSTMS2)
  • Teaching Methodology 2 (3.75 EC, GSTALGD2)
  • Subject Teaching Methodology 2 (3.75 EC,GSTVD2 + subject IN/NK/SK/WK)
  • Introduction Educational Research (3.75 EC, GSTPGO1)
  • Practice Based Research (3.75 EC, GSTPGO2)   

Start February 2019

  • Professional in Practice 2 (10 EC, GSTPIP2)
  • Pedagogy 2 (2,5 EC, GSTPED2)
  • Subject Teaching Methodology 2 (7,5 EC, GSTVAKD2+subject IN/NK/SK/WK)
  • Pedagogical elective (5 EC, choose from GSTPKC01 – GSTPKC07)
  • Elective (5 EC, choose from GSTOKC01 – GSTOKC10, FI-MSECSIS)

If you are new to teacher education, you will join the first semester of the teacher training programme (Educatieve module). After your master’s, you will be eligible to complete your first degree teacher programme in only half a year. Your master’s profile will comprise of the following courses:

  • Professional in Practice 1a (10 EC, GSTPIP1A)
  • Professional in Practice 1b (10 EC, GSTPIP1A)
  • Subject Teaching Methodology 1 (5 EC, GSTVAKD1+subject IN/NK/SK/WK)
  • Pedagogy 1 (5 EC, GSTPED1)

This first semester of teacher training (Educatieve Module) will lead to a (limited) second degree teaching qualification for lower secondary education (vmbo-t and the lower grades in havo and vwo), provided your bachelor’s programme is registered in the 'Verwantschapstabel'. In any case, after having completed the “Educatieve Module” successfully, you are halfway obtaining a first degree teaching qualification for secondary education (only 30 EC left). Please check Admission and enrolment, deadlines and procedure for more information on your admissibility.

The educational profile starts twice a year in September or February. By default, the profile will be completed in a single semester of full time study. Students who start per September 2018 will start with classes on August 20th, 2018.

In order to get admitted to this profile, you will have completed a substantial part of your current programme. Moreover, there are specific requirements upon the match between your disciplinary background and the school subject you would like to teach (physics, mathematics, chemistry or computer science). Please, check the ‘Verwantschapstabel' to see if you meet the entry requirements.

In order to apply for this profile, please go to OSIRIS Online Application

  • Choose your language.
  • Click: “change solisID”
  • Fill in your details
  • You will receive an email from Osiris with username and password to start your application.

Please register before June 1 (start in August*), or October 15 (start in February). Late applications will be considered, but placement cannot be guaranteed.

Once your disciplinary background has been found to be in accordance with the requirements, you will be invited for the matching activities to assess your eligibility.

As the educational profile is primarily targeted towards teaching in the Dutch school system, the courses and the internships are by default in Dutch. Non-native candidates are welcome to follow the educational profile and obtain the Dutch “limited second degree in teaching”, provided they have a basic proficiency in Dutch. Should a non-native student start per September and do the educational profile during the first semester of the academic year, most of the courses will be in English. The course in subject-related methodology, however, will be in Dutch. There will be limited placement opportunities in bilingual or international schools.

Admission is possible if the candidate masters the Dutch language for reading and listening at B2 level. Sufficient passive control of the Dutch language can be demonstrated 1) during an interview or 2) by passing the Reading and Listening components of the State Examination NT2 before the start of the course (minimum score 500 points).

If a student start the educational profile in February all courses will be in Dutch, which means they need enough command of the Dutch language to follow all classes in Dutch. This command can be demonstrated through the aforementioned NT2 test or during an interview. The programme will try to find an internship in a bilingual or international school. If you already have a Dutch second degree in teaching and want to obtain a first degree in teaching, it is necessary to understand and speak Dutch fluently. Please contact mastertoelating.gst@uu.nl for information on the first degree in teaching.

For this programme you may qualify for a contribution of €5000 towards your tuition. Visit www.wordleraarinhetvo.nl or the website of DUO (both in Dutch) for more information and the conditions that must be met.

Further information

  • For questions about the contents of the programme, prospects after the programme etc., contact the study advisor: studieadviseur.gst@uu.nl
  • For questions about your eligibility and about the admissions procedure, contact the admissions office at: mastertoelating.gst@uu.nl

The coördinator for this profile is Manon Thijssen.

For questions about your planning please contact the programme coordinator of your own Master’s programme.

*Please note that the profile starts one or two weeks before the start of the academic year (for September 2018: education starts on August 20th, 2018) to align with the start of the secondary schools. Full participation in this first week is a requirement for further participation in the profile.

Applied Data Science Profile

Data are everywhere. From the sciences to industry, commerce, and government, large collections of diverse data are becoming increasingly more indispensable for decision making, planning, and knowledge discovery. But how can we sensibly take advantage of all the opportunitities that these data potentially provide while avoiding the many pitfalls? The Master’s profile Applied Data Science addresses this challenge.
Applied Data Science is a multidisciplinary profile for students who are not only interested in broadening their knowledge and expertise within the field of Data Science, but are also eager to apply these capabilities in relevant projects within their research domain. The two mandatory courses provide a thorough introduction to data science, its basic methods, techniques, processes, and the application of data science within a specific domain. The foundations of applied data science include relevant statistical methods, machine learning techniques and programming. Moreover, key aspects and implications of ethics, privacy and law are covered as well.

The multidisciplinary nature of the Applied Data Science profile is also embodied in the collaborative design of the mandatory courses and (optionally) the research project. This means that both the teaching staff and students will have different backgrounds as means to help broaden perspectives and stimulate creativity. We investigate data science methods and techniques through case studies and applications throughout the life sciences & health, social sciences, geosciences, and the humanities. Therefore, students applying for this master’s profile should have an affinity for this multidisciplinary approach. You can register for the ADS profile by clicking the Register button below and then filling out the form.

Register for ADS profile GSNS

 

 

 

 

 

Curriculum

 

The master’s profile comprises 2 mandatory multidisciplinary courses (15 EC) complemented with either a research project (15 EC) OR a selection of 2 elective courses (15 EC) from a list of preapproved elective courses.

  1. Two mandatory courses (15 EC)
    1. Data Science & Society (coordinator: dept. Computer science / GSNS; in period 1)
    2. Data Analysis & Visualisation (coordinator: dept. Methods & Statististics / GSSBS; in period 2)
    • NB: By registering for the ADS profile, you are automatically registered for the obligatory DS&S and DA&V courses, even without OSIRIS enrollment beforehand.
  2. Research project on an Applied Data Science topic (15 EC) OR Two elective courses (15 EC)
    1. Research project on an Applied Data Science topic (15 EC). Focus should be on interdisciplinary aspects and at least two supervisors from different departments/faculties should be involved. The topic should not correspond to the topic of the master thesis, however if the master reseach project deals with an applied data science subject, it is for certain master’s programmes permitted to combine the research project of the master’s profile Applied Data Science (15 EC) with the master research thesis. Both parts must be separately assessed and a supervisor from a different department or faculty is involved in this part of the research project. The topic should be approved by a member of the Applied Data Science steering committee who is involved, and by the programme director of the master programme for which the student is admitted.
    2. Two elective courses (15 EC). The elective courses list below is still incomplete. Please ask your Master’s programme coordinator for up to date information.

Please note that the total number of EC of each master’s programme will NOT be increased by completing the master profile Applied Data Science. Students receive a certificate by completing the Master’s profile Applied Data Science.

Learning outcomes

  1. Understands the basic methods and techniques in data science
  2. Is able to apply this knowledge and analyse large datasets in a specific domain
  3. Understands the potential and risks of applying data science for research and society
  4. Is able to work in interdisciplinary teams

Eligible elective courses

Master's programme

 Elective course OSIRIS code and URL
Artificial Intelligence Cognitive Modeling  INFOMCM
Artificial Intelligence Experimentation in Psychology and Linguistics  INFOMEPL
Artificial Intelligence Logic and Computation WBMV13005
Artificial Intelligence Logic and Language  TLMV13020
Artificial Intelligence Multi-agent learning  INFOMAA
Business Informatics  Business intelligence  INFOMBIN
Business Informatics  Software Architecture INFOMSWA
Climate Physics  Measuring Analyzing and Interpreting Observations NS-MO501M
Computing Science  Big Data INFOMBD
Computing Science  Data mining INFOMDM
Computing Science  Pattern recognition INFOMPR
Computing Science  Pattern set mining INFOMPSM
Experimental Physics  Statistical Data Analysis NS-EX414M
Game and Media Technology  Multimedia Retrieval INFOMR
Game and Media Technology  Pattern Recognition INFOMPR
Mathematical Sciences  Network Dynamics WISL116
Mathematical Sciences  Parallel Algorithms WISL603
Mathematical Sciences  Seminar Scientific Computing  WISM470

Methodology and Statistics for the
Behavioural, Biomedical and Social Sciences 

 Computational inference with R  201300004