Prerequisites: ENAI600 and ENAI601

This is the equivalent of ENAI605 for Fall 2026 only

This course develops the student s analytical and practical familiarity with, and understanding of, key generative engineering AI techniques and their application across select engineering disciplines. Students will develop proficiency in the mathematical foundations underlying current and future digital twin technologies, including variational filters for inference, generative models for prediction, and reinforcement learning for decision making, and will explore the potential for digital twins todrive innovation and solve complex engineering problems. Through lectures, hands-on assignments, and projects, students will develop knowledge and skills to harness the power of generative AI in advancing engineering research and practice.