Learn how to do FAIR compliant professional Data Management. Experience and practice with the latest software to manage and analyze data!
Data Science is a new methodology to better understand the complexity of environmental, living and societal systems and to exploit the huge amount of data being generated for scientific and business interests.
Professional Data Science requires a deep understanding in techniques for efficient Data Management. It is not surprising that scientific labs and also industry are desperately looking for well-trained Data Scientists (DS) and Data Managers (DM).
Therefore, ENVRI Plus cluster project (active in the environmental science) and the Research Data Alliance (RDA Europe, globally active in defining social and technical recommendations), join forces to organise this summer school supported by several institutions and initiatives.
For five days, experienced teachers will first present data management and analysis concepts and methods and then support hands-on sessions in such a way that at the end of the course the participants will be able to successfully deal with a wide range of Data Science related activities.
Environmental data will be used during the course; however, the applied methods are widely independent of the nature of the data.
The course will be of interest for young environmental master students, PhD students, post docs or experts from start-ups. Due to the hands-on part some knowledge about programming is necessary as scripting languages such as Python or PHP will be used.
The deadline for applications is 5th May 17.00 CET and the course is limited to a maximum of 25 participants.
Training is free of charge and coffee breaks and lunches during the course is kindly provided by ENVRI-Plus, RDA Europe and CSC. The participants are requested to pay the costs for travel, accommodation and dinner from their own funding sources. After the training event participants can apply for reimbursement up to 700 Euros per person as a contribution towards expenses.
Source: Research Data Alliance (RDA)