Data, AI, and Development

3.0 credits · Undergraduate

This course introduces students to the practical and critical use of data in addressing global development challenges, including poverty, food security, environmental sustainability, and climate adaptation. Through two hands-on modules, students first learn data interpretation, management, and analysis using open-access tools to work with imperfect but widely available datasets such as World Bank indicators. The second module introduces geospatial analysis with Google Earth Engine, focusing on environmental change, land use, and remote sensing applications in development. Both modules emphasize climate change and sustainability, encouraging exploration of data-driven strategies for adaptation resilience. The course also provides an accessible introduction to Artificial Intelligence (AI), highlighting how machine learning can inform development practice and policy while critically engaging with the ethical considerations inherent to data-driven approaches.