GDEV 5045

Data, AI, and Development

Course Description

Course information provided by the 2025-2026 Catalog.

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 and 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.

Distribution Requirements (DLG-AG, SBA-AG)

Last 4 Terms Offered 2025SP, 2023FA, 2022FA

Learning Outcomes

• Critically evaluate ethical implications and responsibilities associated with using data-driven methods and AI technologies in global development contexts.
• Manage and analyze country-level development data, including importing, cleaning, and summarizing datasets.
• Create clear and informative data visualizations using graphing tools to support evidence-based storytelling.
• Demonstrate understanding of AI concepts, including how machine learning is used for predictive modeling and geospatial classification.
• Communicate technical findings effectively through reproducible reports, visual narratives, and live presentations.
• Graduate students will also be able to: Reflect critically on the role of data, technology, and ethics in shaping development interventions and environmental decision-making.

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