The Data Train training program is offered to doctoral researchers across institutes and disciplines and therefore focusses at basic competencies in Research Data Management and Data Science.
It is currently composed of two training components: Courses that are allocated into "Tracks", i.e. course series, and invited talks from industry and academia: "Data Stories".
The Data Train Curriculum: Improve your data skills!
In the ‘Starter Track’, thematic overview lectures provide a general knowledge of important topics in data literacy, research data management, and data science. This track is intended for anyone who wants to get started in research data management and data science.
Operator Track ‘Data Steward’
In the Operator Track ‘Data Steward’, essential competencies for the efficient handling of data in accordance with the „FAIR data principles“ (data should be findable, accessible, interoperable and reusable) are taught. FAIR data form the basis for sustainable and future-oriented research that exploits its potentials. The track includes hands-on workshops on programming languages, versioning, data management plans, reproducibility, data preparation, data provisioning, and database skills.
Operator Track 'Data Scientist'
Data science is concerned with extracting information and gaining knowledge from data using computational analysis methods such as statistical techniques, but also artificial intelligence (e.g. machine learning). In the Operator Track ‘Data Scientist’ participants learn methods from mathematics, statistics, artificial intelligence and computer science for data analysis as well as data visualization skills.
Data Stories: Think outside your box!
Everyone is cordially invited to take part in our Data Stories!
In exciting talks, we will listen to inspiring stories about data handling, data management and data science applied in the private sector or in academia. The speakers shed light on the importance of data competences with regard to their individual working fields and will discuss current challenges.