Face to Face Courses

The Face to Face training includes advance level courses with a high degree of required knowledge and skills. The topics have been primarily defined according to the requirements of the EO African community and the EO AFRICA Research Projects. Except for the first two F2F courses, all participants, should have proven knowledge on cloud computing, use of Jupyter notebooks and knowledge on EO. This knowledge is covered in the MOOC and the first two On-line courses ("Cloud Computing and Algorithms for EO analyses" and "Principles of and Advances in Earth Observation"). A self-assessment questionnaire will be provided for the applicants to evaluate their knowledge. In case of gaps, the applicants are advised to study the MOOC and the material of the on-line courses.

The courses will make use of Virtual Machines (VM), and will explore the use of the Innovation Lab as much as possible. The number of participants will be restricted to maximum 25. The selection of candidates will be done on the basis of academic background, affinity with EO in the related field and the type of organization the applicant works for. University staff and Researches are the preferred audience for this course modality.

All F2F training have a comparable set-up. On day 1, the general set-up of the EO AFRICA R&D facility will be introduced, followed by developing hands-on skills related to the Copernicus Program, cloud computing, use of Jupyter notebooks and EO data access. Day 2, 3 and 4 will be dedicated to an application topic. Day 5 will be spent on presentations by trainees on their achievements to demonstrate their skills acquired during the training, followed by a closing session (evaluation, open discussion, handing over of the certificates and formal closing).

*Due to the COVID-19 situation, the first F2F course was held on-line in the form of live sessions. In that set-up, the course consisted of 5 days intense training combining theory, practical exercises and discussions with participants.

Topic
1   Advances in Earth Observation
2   Earth Observations for Water Resources Monitoring and Management
3   Cloud Computing and Algorithms for EO Analyses
4 EO for Agriculture and Vegetation
5 to 10 TBD