The digital footprint of Life, Environmental, Social, Food and Nutrition Sciences is increasing at unprecedented speed, bringing opportunities for data-driven innovation in both research and industry. To be successful, scientists need to master both domain expertise and data science skills to solve practical problems.
|Course code||Name||Offered Periods||CS/RO||Credits|
|BIF-51306||Biological Data Analysis and Visualization||2AF||CS||6|
|INF-22306||Programming in Python||1AF||RO||6|
|GRS-51306||Geo-information Science for Society||1AF||RO||6|
This minor targets students with analytical ambitions in their domain of studies and offers a learning path for applying data management, programming, analytics, and visualization techniques, and how to employ these for big data discoveries. Students will learn Python and R through hands-on practice and project-based learning experiences grounded in real-world data from the Wageningen domains. See also more information on https://tinyurl.com/DataScienceMinor
After successful completion of this minor students are expected to be able to:
- Employ a data lifecycle approach to organize their data driven research;
- Identify appropriate analysis techniques when confronted with new datasets and questions;
- Design and implement databases for applications in the WUR domain;
- Write efficient and well-documented computer programs;
- Apply and evaluate relevant visualization and quantitative data analysis methods;
- Communicate research findings by data storytelling;
- Consider broader issues related to data collection, processing and dissemination, including licensing and privacy issues.
Target group and Assumed Knowledge
This minor is relevant for all BSc programmes.
First semester (period 1, 2 and 3)
Programme or thematic