Enrich your competencies in digital research methods and tools through the Digital Research certificate programme.
Computers have played a key role in research for many decades. Today they are essential elements of the research process, across almost all disciplines. They enable researchers to collect and process ever larger amounts of data. The increasing prevalence of computation and digital data analysis in research means that researchers of all career stages need digital skills that go far beyond what is typically taught in traditional degree programmes.
To close this gap, zedif offers advanced training courses on these topics. zedif already issues certificates of attendance for all individual courses. Beyond that, with the Digital Research Certificate it is possible to show participation in a selection of these courses with just a single document. This course selection must cover a certain number of workshops as well as a certain range of topics:
- At least 3 workshops must have been taken from each of the three pillars:
- Research data management
- Research software, data processing and analysis
- Publication and presentation
- A total of at least 15 workshops or 5 ECTS-equivalent points must have been taken through workshops in the entire certificate programme.
There is no limit to the period during which the certificate can be obtained. However, the aim should be that course completion and certificate completion should not be more than five years apart. No registration is required for the certificate. If you have fulfilled the requirements for the certificate, please contact us.
The following table shows sample courses and their allocation to the three pillars. Actual course names may differ. Likewise, workshops that are not listed here but correspond thematically to those listed below (e.g. ‘Programming in language X’) can be credited as well. All of the courses listed here are offered in the qualification portalExternal link, but not necessarily provided by zedif.
Legend:
- RDM: Research Data Management
- RSE-DA: Research Software (Engineering), Data processing and -analysis
- PP: Publication und Presentation
| RDM | RSE-DA | PP | Example Courses |
|---|---|---|---|
| x | Data Management Plans | ||
| x | Research Data Management – Make your data count! | ||
| x | Research data management in the humanities and social sciences | ||
| x | Introduction to Experiment Documentation with eLabFTW | ||
| x | Chemotion Workshop | ||
| x | Data Privacy Basics | ||
| x | x | IF Spreadsheets, THEN | |
| x | x | Introduction to OpenRefine | |
| x | x | Good scientfic practice and handling conflicts in day-to-day research | |
| x | x | Practice Workshop REFODAT | |
| x | x | Open Access, Research Data Management & Co. | |
| x | x | Software and Data Licenses | |
| x | x | Citavi – a compact Webinar | |
| x | Introduction to the Command Line | ||
| x | Advanced Use of the Command Line | ||
| x | Version Control with Git | ||
| x | Collaborative Version Control with Git | ||
| x | Version Control and Project Management with GitLab (CLI) | ||
| x | Version Control and Project Management with GitLab (GUI) | ||
| x | Introduction to Containerization with Docker | ||
| x | First Hands-on Experience with an HPC Cluster | ||
| x | HPC Cluster Usage for Advanced Users | ||
| x | Learning and Teaching scientific writing | ||
| x | Writing Week | ||
| x | Adobe Indesign | ||
| x | Scientifc Writing with LaTeX | ||
| x | Network Analysis with Gephi | ||
| x | Descriptive and inference statistics with SPSS | ||
| x | Machine Learning | ||
| x | Introduction to Programming with Python | ||
| x | Working with Tabular Data in Python and Pandas | ||
| x | Introduction to Programming for the Humanities and Social Sciences | ||
| x | Scientific Computing with NumPy | ||
| x | x | Data visualization with Python and Matplotlib | |
| x | Programming with R | ||
| x | Programming with Julia | ||
| x | Introduction to the Database Query Language SQL | ||
| x | Software Development: Beyond Programming |