Python for marine modelers using MIKE IO and ModelSkill

Note

This course material is no longer maintained. It has been superseded by the 2026 ModelSkill course: DHI-Internal/modelskill-course-2026 (DHI staff only — requires access to the DHI-Internal org).

The notebooks in this repo remain available as-is.

https://dhi.github.io/book-learn-mikeio-modelskill/

Would you like to use Python to become more efficient as a marine modeler?

WHO SHOULD ATTEND?

This course has been designed for MIKE 21/3 modelers with some Python experience, e.g. from the course Getting started with dfs files in Python using MIKE IO or similar, that would like to use Python for more pre- and post-processing.

CONTENT

The course comprises typical data processing tasks in connection with MIKE 21/3 modelling, preparing input data, converting forcing data from other formats, creating roughness maps, concatenating files, extracting data from output files (e.g. vertical profiles), visualization, assessing the skill of MIKE 21/3 by comparing to station and satellite track observation data. We will use Jupyter notebooks with Python packages such as NumPy, pandas and xarray as well DHI's own MIKE IO and ModelSkill packages.

BENEFITS

After the course, you will have improved your skills and knowledge on how to conduct typical MIKE 21/3 modeling workflows using MIKE IO and ModelSkill.