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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
The most recent pitch for the Applied Data Science Profile for GSLS students can be found HEREThe official GSNS profile info page is here.

Data are everywhere. From the life 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 GSLS Master’s profile Applied Data Science (ADS) (33 ECTS) addresses this challenge.

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. The three mandatory courses, one elective course, and overarching portfolio assignment together 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 ADS profile is also embodied in the collaborative design of the mandatory courses. 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.

Curriculum

The ADS master’s profile comprises three mandatory multidisciplinary courses (22.5 EC) complemented with one applied data science-related elective course (7.5 EC). A portfolio assignment (3 EC) concludes the Master’s profile Applied Data Science. The illustration below visualises the Master’s profile Applied Data Science.
  1. Three mandatory courses (22.5 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)
    3. Computational Thinking (coordinator: dept. Computer science / GSNS; in period 3)
  2. One elective course (7.5 EC)
    • The elective courses list below is still incomplete. Please ask your Master’s programme coordinator for up to date information.
  3. Portfolio assignment (3)
    • <todo>
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.

Eligible elective courses

Per Master's programme the elective options may differ. Ask your own master programme coordinator whether an elective course from a different programme is eligible for your studyplan as well.
Master's programmeElective course OSIRIS url
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