This course provides a fast-paced introduction to how artificial intelligence (AI) is transforming bridge engineering. It begins with the fundamentals of AI, from machine learning and reinforcement learning to deep learning and optimization, explained in a way that is accessible to engineers. Building on these concepts, the session explores practical applications, including the use of drones and computer vision for automated bridge inspection, digital twins for real-time monitoring, and predictive analytics for maintenance, life-cycle management, and even design support. The attendees will learn how to design with data, including the implementation of Gen AI for conceptual design and the application of AI for seismic performance assessment of bridges. Case studies highlight current work in defect detection and predictive modeling, along with examples of how Canadian agencies and U.S. Departments of Transportation are adopting AI to improve safety, efficiency, and decision-making. This course will also cover ethical responsibilities and legal issues related to AI in engineering, with a focus on the importance of transparency and the avoidance of bias. The course concludes with a forward look at emerging technologies, such as large language models and generative AI, as well as prompt engineering for bridge applications, underscoring their potential to further reshape engineering practice. This course is designed for bridge and structural engineers, transportation professionals, and researchers interested in learning how AI can be integrated into inspection, analysis, and asset management workflows to enhance decision-making and operational efficiency.