Building AI Hardware Expertise: Edge AI Curriculum Design and Implementation in German Universities - Gursch, Ann-Marie; Luo, Xuanshu; Hasse, Lilian; Trinitis, Carsten; Lucke, Ulrike; Werner, Martin; Krstic, Milos (Proceedings of the AAAI Conference on Artificial Intelligence, 2026)
Edge artificial intelligence (AI) redistributes AI computation from distant cloud to local processors for real-time processing and enhanced privacy. This fundamental shift underscores a critical gap in current university curricula, which predominantly focus on AI fundamentals and algorithms while often neglecting essential AI hardware topics. To address this deficiency, this paper presents Edge AI, a postgraduate curriculum co-designed by two universities in Germany. Guided by the Dagstuhl triangle, the curriculum is designed to comprehensively cover technical, sociocultural, and application perspectives. Courses are developed using the Four-Component Instructional Design model to encourage action-oriented skill development, with a Learning Management System template available to assist in the design of individual courses. Selected practical courses are formulated as self-managed projects and inverted classrooms, enabling students to learn at their own pace with just-in-time guidance. All curriculum materials are accessible online and maintained by the Open Science Framework to enhance collaboration across institutions and promote applicability in diverse domains. Evaluation results from 176 students over two years (2023-2025) demonstrate universal satisfaction across various curriculum components.