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The course provides a comprehensive overview of artificial intelligence (AI) applications for urban mobility. Beginning with foundational concepts, students delve into AI's historical progression, its challenges, and its specific applications within urban mobility. The subsequent focus on Machine Learning (ML) clarifies its relationship with AI and introduces diverse ML types. Real-world relevance is demonstrated through case studies highlighting AI's contributions to operational efficiency and customer service in urban mobility. The course culminates in a hands-on project employing Google Teachable Machine, where students experiment with image, audio, and pose recognition—bridging theory with tangible AI experimentation.
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