English Data Science for Global Challenges — RIO 1016O1728
Programme evidence at a glance
This unit has 1 contextual record containing 1 retained source row, with 1 distinct provider code. These are source-record counts, not separate degrees, available places or open applications. Source-name aliases do not create extra contextual records.
- Original programme names (NAAM_LANG)
- Data Science for Global Challenges
- International names reported by the source (INTERNATIONALE_NAAM)
- Data Science for Global Challenges
- Reported level labels (NIVEAU)
- WO-BA
- Reported degree labels (GRAAD)
- BACHELOR
- Recognised programme codes (ERKENDEOPLEIDINGSCODE)
- 59026
- Reported study-form labels (VORM)
- VOLTIJD
- Reported study-load values (STUDIELAST)
- 180
- Teaching-language codes (VOERTAAL)
- NLD
Source collection date (UTC): 2026-10-20. Collection dates describe the stored evidence, not the current application year.
Compare the recognition evidence for this unit →
This link matches the original unit code only. The two sources may describe different institutions, campuses, study forms or dates; they do not establish matching current admissions.
Compare the reported contexts
Read across each row to keep its provider, location, study form and teaching language together. Values from different rows should not be combined into one offering.
| Provider and source code | Reported place and location code | Study form | Teaching-language code | Evidence |
|---|---|---|---|---|
| Wageningen University 114A640 |
Wageningen 111X486 |
VOLTIJD | NLD | Source fields 1 → |
What to verify for this unit
- Use unit code 1016O1728 and the exact provider and location codes when checking the intended programme with its provider.
- Match VORM and VOERTAAL within the same contextual row, then check the current curriculum and teaching-language requirements with the provider.
- Check the original offering and intake dates below. An empty end date does not confirm an open intake or a current application deadline.
Original DUO RIO overview of funded current and future higher education education records. OPLEIDING means a programme and VARIANT a programme variant. Each unit page groups only the original OPLEIDINGSEENHEIDCODE; an offering or location is not counted as a separate degree. The list does not cover every private provider or guarantee that applications are open.
Reported start, end and intake dates remain source evidence rather than a promise of current availability. A missing end date does not establish an open intake. Names, qualification labels, codes, languages and missing values remain in Dutch. No CIP equivalence, inferred admissions conditions or institution-name matches are added. Contextual offering records and source-name aliases are preserved together.
Source: DUO official dataset and Creative Commons Attribution licence statement; official RIO delivery specification v2.0. Original language nl; English explanations and grouping added by CollegeVerse, which DUO does not endorse. Verify current availability with the provider.
Original RIO unit 1016O1728; observed 2026-10-20. 1 contextual records below.
Original source fields
OPLEIDING · 1016O1728
Original record 2389
- AANGEBODEN_OPLEIDINGCODE
- b80cca66-4d2f-414c-a4ed-7b3e2ad60645
- AANGEBODEN_OPLEIDING_BEGINDATUM
- 2025-09-01T00:00:00
- AANGEBODEN_OPLEIDING_EINDDATUM
- Not provided (null)
- BEGINDATUM
- 2025-09-01T00:00:00
- BUITENLANDSEPARTNER
- Not provided (null)
- DEFICIENTIE
- GEEN_DEFICIENTIES
- EERSTE_INSTROOMDATUM
- 2025-09-01T00:00:00
- EIGENNAAM
- Bachelor's Data Science for Global Challenges
- EIGENNAAM_DUITS
- Not provided (null)
- EIGENNAAM_ENGELS
- Bachelor's Data Science for Global Challenges
- EIGEN_AANGEBODEN_OPLEIDINGSLEUTEL
- b80cca66-4d2f-414c-a4ed-7b3e2ad60645
- EINDDATUM
- Not provided (null)
- EISEN_WERKZAAMHEDEN
- GEEN_EISEN
- EQF
- 6
- ERKENDEOPLEIDINGSCODE
- 59026
- ERKENNER
- NVAO
- GRAAD
- BACHELOR
- INTERNATIONALE_NAAM
- Data Science for Global Challenges
- LAATSTE_INSTROOMDATUM
- Not provided (null)
- NAAM_LANG
- Data Science for Global Challenges
- NIVEAU
- WO-BA
- NLQF
- 6
- OMSCHRIJVING
- The objective of the BSc Data Science for Global Challenges is to educate students to build bridges between data science and life sciences and thereby contribute to solutions to global challenges. Think about food security, human health, climate change.\n\nThe programme is interdisciplinary and is characterised by the integration of data science knowledge and skills with an understanding of the domains agri-food, health and environment. Graduates of this programme speak both the language of content experts in life sciences and the language of computer scientists and data specialists. This enables them to contribute to solutions to challenges in the life sciences using data science methodologies and, vice versa, to contribute to the further development of data science methodologies based on developments and issues in life sciences.\n\nDuring the BSc Data Science for Global Challenges programme, students develop state-of-art data science knowledge and skills on the one hand, and they learn the key concepts of life sciences on the other hand. To be able to interconnect the domains of agri-food, health and environment with data science they will develop unique skills and the attitude of a bridge builder.\n\nA bridge builder in the context of this bachelor programme is someone with the following characteristics. They are comfortable with speaking both the language of data scientists and life scientists. They possess strong knowledge both in data science and AI quantitative methods and techniques and disciplinary knowledge and skills. The depth of data science and AI and disciplinary knowledge may differ per student, but a minimal level of both data science and domain knowledge defined by the programme learning outcomes must be met. It is important to empathize with the interests and concerns of life scientists in data science and the other way around (i.e. data scientists interests and concerns in life sciences)\n\nFurthermore, a bridge builder promotes 'technology pull' based on requirements coming from the application fields. They understand the potential added value of data-driven solutions in life sciences and are able to convince stakeholders of this. They also think and act interdisciplinarily, integrating perspectives or insights through interaction. The didactical implementation of this profile is explained in the educational principles and methods.
- ONDERWIJSAANBIEDERID
- 114A640
- ONDERWIJSAANBIEDER_NAAM
- Wageningen University
- ONDERWIJSBESTUURID
- 107B451
- ONDERWIJSBESTUUR_NAAM
- Wageningen University
- ONDERWIJSLOCATIECODE
- 111X486
- ONDERWIJSLOCATIEPLAATS
- Wageningen
- ONDERWIJSLOCATIESTRAAT
- Droevendaalsesteeg
- OPLEIDINGSEENHEIDCODE
- 1016O1728
- PENVOERDER
- Wageningen Universiteit/ Wageningen University
- PROPEDEUTISCHE_FASE
- GEEN_PROPEDEUTISCHE_FASE
- SAMENWERKEND_MET
- Not provided (null)
- SOORT
- OPLEIDING
- STUDIEKEUZECHECK
- STUDIEKEUZE_CHECK_VERPLICHT
- STUDIELAST
- 180
- VARIANT_VAN
- Not provided (null)
- VERSNELD_TRAJECT
- GEEN_VERSNELD_TRAJECT
- VOERTAAL
- NLD
- VORM
- VOLTIJD
- WAARDEDOCUMENTSOORT
- GETUIGSCHRIFT
- WEBSITE
- Not provided (null)