Introduction to artificial intelligence concepts, tools, and social impact opportunities.

Building data ecosystems and regulatory framework policies for public sector data.

Applying automation and AI to streamline public services and municipal workflows.

Using predictive models to design evidence-based social policies and interventions.

Implementing machine learning models in public healthcare, sanitation, and social safety nets.

Leveraging IoT, AI sensors, and predictive tools for urban management.

Reviewing successful global AI deployments in development and social sectors.

Applying predictive models for disaster risk reduction and relief logistics.

Identifying and mitigating bias in social sector decision-making algorithms.

Applying UNESCO guidelines and ethical rules to public AI deployments.

Designing natural language processing (NLP) applications for citizen services.

Structuring human-in-the-loop workflows for civil servants.

Managing software procurement, budgeting, and scaling for social initiatives.

Defining KPIs to measure efficiency gains and social return on investment (SROI).

Presenting a fully developed AI integration plan for a social or public entity.