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 opportunities that these data potentially provide while avoiding the many pitfalls? The master’s profile Applied Data Science addresses this challenge.

Note: there are master’s programmes for which the overlap in content between the master and the ADS profile is too large. This implies that students from these masters cannot follow the profile. For the GSNS this holds for all Master’s programmes in Information and Computing Sciences.

Applied Data Science (ADS) 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. Two mandatory courses provide a thorough introduction to data science, its basic methods, techniques, processes, and the application of data science within specific domains. The foundations of applied data science include relevant statistical methods, machine learning techniques and programming skills.

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.

Learning outcomes

Upon completion of the Master’s profile Applied Data Science the student:

  • Understands the basic methods and techniques in data science
  • Is able to apply this knowledge and analyse large datasets in a specific domain
Profile curriculum. Image description available in the dropdown 'Contents of the Profile' below

For the GSNS the ADS profile comprises two mandatory multidisciplinary courses (15 EC), complemented with either a selection of two elective courses (15 EC) from the elective courses table listed below, OR a multidisciplinary research project (15 EC, INFOMADSRP).

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.

Two mandatory courses (15 EC)

  1. Data analytics 1: Supervised learning and visualization (Period 1, INFOMDA1)
  2. Data analytics 2: Battling the curse of dimensionality (Period 2, INFOMDA2)

Both courses are coordinated by the department Methods & Statistics of the Faculty of Social and Behavioural Sciences, that also coordinates the Focus area Applied Data Science.

Research project (15 EC)

Research project on an Applied Data Science topic.

Focus should be on interdisciplinary aspects and at least two supervisors from different departments/faculties should be involved. The student is responsible for the involvement of two eligible supervisors. The project is to be approved by the ADS profile coordinator, based on a 1-page research proposal outlining the research trigger, main question and approach.

The topic should not correspond to the topic of the master thesis.

Complementary course(s) (15 EC)

  • Two elective courses (15 EC for GSNS, and 7.5 EC for GSLS, see under Contents)

Instead of a research project, you can also choose two additional courses from the elective courses list below. Note that you can select courses from any of the participating master's programmes, as long as your own master's programme coordinator also agrees with the inclusion of the selected ADS profile courses as eligible electives within your own master's curriculum (i.e. you need permission from both the ADS profile coordinator and your master's programme coordinator).

This list is not exhaustive; for elective course suggestions, email the ADS profile coordinator for approval.
 

Masters programme

Elective course

Osiris code

Artificial Intelligence

INFOMAA
INFOMCM INFOMEPL TLMV13020 WBMV13005 INFOMNLP

Business Informatics Process Mining INFOMPROM
Climate Physics Simulation of Ocean, Atmosphere and Climate NS-MO501M
Computing Science INFOMDM INFOMPSM INFOMBD INFOMPR INFOMDIS
Experimental Physics Statistical Data Analysis NS-EX434M
Game and Media Technology INFOMR
INFOMPR
Mathematical Sciences

WISL603

WISL116

WISL11

Methodology and Statistics for the Behavioural, Biomedical and Social Sciences Computational inference with R 201300004
Utrecht School of Economics Algorithms in Finance ECMAF

 

It is assumed that you have already completed a bachelor level course in statistics and/or programming before starting the ADS profile. If not, you must have completed a certified introductory MOOC course on basic statistical methods and/or programming in preferably Python or otherwise R beforehand instead.

To apply for the ADS profile, you should first contact the coordinator of your master’s programme and ask for permission. When you have permission, register via the online application form. The ADS profile coordinator will then assess your profile. You can apply for the profile throughout the year, there are no deadlines for registration.

Transitional arrangement for students who started Applied Data Science before academic year 2021-2022

With effect from 2021-2022 the content of the Applied Data Science profile has been changed in such a way that a transitional arrangement has been introduced. Students who have started the profile up to and including the academic year 2020-2021 and have not yet completed it, will be given up to and including the academic year 2023-2024 to complete the profile as it was designed in the Exam Regulation (in Dutch: OER) of 2020-2021.

They may also choose, in consultation with the profile coordinator, to complete the profile in the new form, whereby they may or may not maintain the components already followed. Ultimately, the profile coordinator decides whether the components taken together suffice, whereby the student must in any case have obtained 30 EC.

As of the academic year 2024-2025, this transitional arrangement will expire and every student who enrolled in the ADS profile before course year 2021-22 and who wishes to complete the ADS profile must meet the requirements as determined in the Education and Examinations regulations (OER) of that year.

For questions or more information, please contact: ads-profile@uu.nl.