Module 1: Foundations of AI and Machine Learning in Humanitarian Contexts
1. Understanding Artificial Intelligence, Machine Learning, and Generative AI
2. Key types of AI and ML models explained simply
3. Applications of AI in humanitarian and development sectors
4. Opportunities, limitations, and risks of AI in humanitarian settings
Module 2: AI Tools for Productivity, Communication, and Reporting
1. AI tools for daily humanitarian work (writing, summarizing, planning)
2. AI for emails, reports, proposals, and donor communication
3. AI for translation, advocacy, and content creation
4. Hands-on practice with generative AI tools
Module 3: Data, Machine Learning Basics, and Humanitarian Analytics
1. Humanitarian data types and data management principles
2. Data cleaning, preparation, and quality assurance
3. Introduction to machine learning concepts (classification, prediction, clustering)
4. Basic AI/ML applications for humanitarian datasets
Module 4: AI in Humanitarian Programming, Operations, and Decision-Making
1. AI in emergency response, health, WASH, protection, and education
2. AI for logistics, supply chain, and resource management
3. AI for MEAL, monitoring, evaluation, and reporting
4. Predictive analytics and decision support systems in humanitarian action
Module 5: Ethical AI, Risk Management, and Organizational Integration
1. Ethical considerations in AI and ML use (bias, fairness, transparency)
2. Data privacy, protection, and humanitarian accountability
3. Responsible AI use in crisis and conflict settings
4. Integrating AI into organizational systems and developing adoption plans