AI Development

3 Credits · Level: Graduate

In today's rapidly evolving technological landscape, Artificial Intelligence has become integral to solving global challenges in health, education, agriculture, and more. This course delves deep into AI and machine learning applications to policymaking, offering students a hands-on journey through the entire policy intervention process. Through a mix of lectures and hands-on exercises, students will build a strong theoretical foundation of AI concepts and methods such as reasoning, causal analysis, big data analysis, knowledge-based modeling, machine learning techniques, and generative AI. The course will draw on various case studies such as predicting agricultural yields with satellite data and improving urban transport with cell phone records. The class aims to be highly interactive. It will include engagement with expert guest lecturers, peer discussion on applications of AI and Machine learning in design and evaluation of policies and interventions as well as potentials and risks of AI, ethical considerations, biases, and privacy concerns. As a final project, students will work together in groups on developing an AI solution to a real-world problem. Upon completion of the course students would be able to decide which AI methods and tools are relevant and useful in the context of a specific development problem where big data may or may not be readily available. No prerequisites.