Artificial Intelligence (AI) for Monitoring & Evaluation (AIME)
Course Overview:
This course introduces participants to the applications of Artificial Intelligence (AI) and Machine Learning (ML) in the field of Monitoring and Evaluation (M&E). It bridges the gap between traditional M&E approaches and emerging digital innovations, demonstrating how AI can automate data collection, enhance analysis, generate insights, and improve decision-making in development and humanitarian projects.
Learning Objectives:
By the end of the course, participants will be able to:
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Understand the basics of AI and machine learning in the context of M&E.
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Identify appropriate AI use cases across the M&E lifecycle.
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Use AI tools to automate data collection (e.g., chatbots, image recognition).
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Apply machine learning techniques for trend analysis and predictive modeling.
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Build basic AI-powered dashboards for monitoring.
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Evaluate ethical considerations and data privacy in AI-powered M&E.
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Design a use case for AI integration in a real or hypothetical M&E system.
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What is AI? What is Machine Learning?
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Evolution of M&E: From manual to intelligent systems
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Where AI fits in the M&E cycle
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Examples from real projects (agriculture, education, WASH, health)
Tools and Platforms Used:
- Python (Jupyter, pandas, scikit-learn)
- Power BI / Tableau / Google Data Studio
- KoBoToolbox / ODK
- Google Teachable Machine / Google AutoML
- ChatGPT
Certification:
Participants who complete all modules and the capstone project will receive a Certificate in AI for Monitoring & Evaluation.