2019 Curriculum

Oceanhackweek curriculum consists of hands-on tutorials, visual presentations and collaborative hack projects. Tutorials and presentations will take place mostly in the mornings, with the afternoons devoted to project brainstorming and project work. This year we plan to focus on access strategies for diverse data systems and workflow for interoperating different types of ocean data and models.

The tutorials will be based on the scientific Python stack, which is an ecosystem of interrelated Python packages for scientific computing and analysis. Tentative topics include:

  • Data science and collaboration tools: Git, Conda, Jupyter
  • Interoperating ocean data and models: APIs and ERDDAP servers
  • The landscape of ocean data systems and data access workflow
  • Spatial statistics and geospatial mapping tools: e.g. Rasterio, Gdal
  • Working with data efficiently using open source Python tools: e.g. Xarray, Dask
  • Large-scale data processing frameworks: e.g. Pangeo, cloud computing
  • Data visualization tools: e.g. PyViz, Bokeh, Seaborn, Altair
  • Machine learning methods and tools: e.g. dimensionality reduction, classification, scikit-learn

We will also have open discussion sessions on:

  • Code of conduct in collaborative research
  • Reproducible and replicable research
  • Open science challenges and ethics