Training eSupport System
  • Log In
    • Log in with UmbrellaID
    • Log in with Helmholtz AAI
    • Login
  • About
  • Events
  • Materials
  • Workflows
  • Collections
  • Learning paths
  • Spaces
  • Directory
    • Providers

PaN-Training makes use of some necessary cookies to provide its core functionality.

See our Privacy Policy for more information.

You can modify your cookie preferences at any time here, or from the link in the footer.

Allow necessary cookies
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Scientific topic
    • Biomedical informatics3
    • Clinical informatics3
    • Cloud computing3
    • Computer science3
    • Data management3
    • FAIR data3
    • Findable, accessible, interoperable, reusable data3
    • HPC3
    • Health and disease3
    • Health informatics3
    • Healthcare informatics3
    • High performance computing3
    • High-performance computing3
    • Medical informatics3
    • Metadata management3
    • Research data management (RDM)3
    • Algorithms1
    • Bioinformatics1
    • Computer programming1
    • Data rendering1
    • Data structures1
    • Data visualisation1
    • Programming languages1
    • Software development1
    • Software engineering1
    • Show N_FILTERS more
    • Content provider
    • Elixir TeSS7
    • Show N_FILTERS more
    • Keyword
    • Python5
    • Clinical data3
    • RDF3
    • GraphDB2
    • Knowledge graph2
    • SPARQL2
    • Automation1
    • Data analysis1
    • Data validation1
    • Data visualisation1
    • Dataset template1
    • FAIR1
    • Foundations of Data Science1
    • Query data1
    • R1
    • RDF graph generation1
    • RDF graph validation1
    • RSE1
    • Research software1
    • SHACL1
    • SQL1
    • Semantic Framework1
    • Semantic artifacts generation1
    • coding skills1
    • fuseki1
    • jupyter-notebook1
    • testing1
    • Show N_FILTERS more
    • Difficulty level
    • Intermediate
    • Not specified148
    • Beginner58
    • Advanced2
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution Share Alike 4.0 International3
    • Creative Commons Attribution 4.0 International2
    • License Not Specified1
    • MIT License1
    • Show N_FILTERS more
    • Target audience
    • Bioinformaticians4
    • Data Managers4
    • Biomedical Researchers3
    • Data Scientists3
    • Research Scientists3
    • Life scientists, bioinformaticians and researchers who are familiar with writing Python code and core Python elements, and would like to use it in their daily data exploration and visualization tasks.1
    • Students1
    • Show N_FILTERS more
    • Author
    • Personalized Health Informatics Group3
    • Avans Hogeschool1
    • David Palecek1
    • Helena Rasche1
    • Jeremy Cohen1
    • Martin Zablocki1
    • Petar Horki1
    • Philip Krauss1
    • Steve Crouch1
    • The Carpentries1
    • Vasundra Touré1
    • Wandrille Duchemin1
    • Show N_FILTERS more
    • Contributor
    • Sabine Österle2
    • Vasundra Touré2
    • Anthony Bretaudeau1
    • Cymon Cox1
    • Helena Rasche1
    • Marius van den Beek1
    • Peter van Heusden1
    • Saskia Hiltemann1
    • Show N_FILTERS more
    • Resource type
    • Video3
    • E-learning2
    • Training materials2
    • e-learning2
    • E-Learning1
    • Mock data1
    • Tutorial1
    • Show N_FILTERS more
    • Related resource
    • Jupyter Notebook (with Solutions)1
    • Jupyter Notebook (without Solutions)1
    • Show N_FILTERS more
    • Status
    • Active6
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Hide materials with broken links
  • Show archived materials
    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month

Training materials

  • Subscribe via email

Email Subscription

Register training material

Max age: 1 month

and Include broken links: true

and Difficulty level: Intermediate

7 materials found
  • Tutorial

    EMO-BON Metagenomics: From Backend Integration to Frontend Processing

    •• intermediate
    Python SPARQL fuseki
  • e-learning

    SQL with Python

    •• intermediate
    Software engineering Foundations of Data Science Python SQL jupyter-notebook
  • Byte-sized RSE Session 3: Testing your Python code

    •• intermediate
    Python RSE Research software coding skills testing
  • e-learning

    Explore and Visualize Your Data with Python

    •• intermediate
    Data visualisation Bioinformatics Data analysis Python
  • E-learning, Mock data, Training materials, Video

    How to use Python and R with RDF Data

    •• intermediate
    Computer science Data management FAIR data Medical informatics Clinical data GraphDB Knowledge graph Python Query data R …
  • E-learning, Training materials, Video

    Validate Graph Data with SHACL

    •• intermediate
    Medical informatics FAIR data Data management Computer science Clinical data Data validation GraphDB Knowledge graph RDF RDF graph validation …
  • E-Learning, Video

    SPHN Dataset Template: Build an RDF schema from an Excel file

    •• intermediate
    Computer science Data management FAIR data Medical informatics Automation Clinical data Dataset template FAIR RDF RDF graph generation …
Training eSupport System
pan-training@hzdr.de
Imprint
Contribute
About PaN-Training
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation

The training portal for the photon & neutron community is supported through the European Union's Horizon 2020 research and innovation programme, under grant agreement 857641, 823852, the Horizon Europe Framework under grant agreement 101129751, and the consortium DAPHNE4NFDI in the context of the work of the NFDI e.V. under the DFG - project number 460248799.