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Generative AI has moved from pilots to everyday practice, delivering gains in productivity and accessibility while surfacing present-day risks—hallucinations and reliability failures, bias and unfairness, prompt-injection attacks, and so on. These trends make AI safety education a core competency. In this paper, we survey global AI safety curricula and, in the Japanese context, observe strong policy momentum but relatively few courses that explicitly combine capability instruction with systematic safety evaluation. In response, we developed a 7-week, graduate-level intensive at a private science and engineering university in Japan, with enrollment open to international exchange students at both the undergraduate and graduate levels. The curriculum progresses from machine-learning foundations to generative models and alignment, with introductory agent topics included to support risk reasoning. Delivery combines weekly lectures, invited talks from academia and industry, structured group discussions, and a final presentation plus a paper-style final project focused on risk evaluation and mitigation planning. An end-of-course survey indicates high perceived learning and positive experience and one student project later resulted in a peer-reviewed workshop paper at ICLR 2025.