Prepares participants for ScHARe research collaborations by covering:
- Choosing computational strategies (AI, ML, statistics)
- An overview of Python data science libraries
- The significance of testing and monitoring in algorithm development
- The role of open science in ensuring reproducible and transparent AI-based research
For researchers and students at all levels who want to collaborate on ScHARe to develop innovative and publishable research projects