【摘要】 为突破人工智能领域多学科交叉研究生培养面临的高校建制及学科边界的壁垒,创新人工智能领域研究生多学科交叉培养模式,面向国家人工智能发展战略和山东省人工智能产业布局实施顶层设计,构建知识精密耦合的多学科融合课程体系,建设产教深度融合的创新实践基地,强化过程考核,多方位构建激励与约束机制,通过研究生基层组织建设实施网格化管理。该模式依托济南大学人工智能研究院,在电子信息类研究生培养过程中进行推广应用,近3年培养人工智能领域研究生150余名,建成2个省级研究生培养基地、8门省级优质课程及相关案例库,研究生科研成果获学科竞赛奖项5项,4篇学位论文获评省级优秀硕士学位论文,可为省属高校多学科交叉背景下的研究生培养提供有益的参考借鉴。更多还原

【Abstract】 Focusing on the interdisciplinary postgraduate training in the field of artificial intelligence,a novel talent training model is proposed to break the barriers of the university structure and disciplinary boundaries. First,based on the national development strategy and industrial programming of Shandong Province for artificial intelligence,the top-level design of training model is proposed. After that,a multi-disciplinary integrated curriculum system is designed with high precision coupling of interdisciplinary knowledge. Meanwhile,many innovation practice platform is established with deep integration of industry and education in artificial intelligence. The multi-viewed incentive and constraint mechanism is designed to reinforce the process assessment. What’s more,the grid management of graduate students is implemented based on the multi-grassroots organization construction. By applying the proposed talent training model in Artificial Intelligence Research Institute of University of Jinan,more than 150 graduate students in the field of artificial intelligence have been trained. Meanwhile,various achievements have been reached,including 2 provincial postgraduate training bases,8 provincial quality courses and case library,5 discipline competition awards,and 4 provincial excellent Master′s thesis. The proposed postgraduate talent training model provides the beneficial reference for postgraduate talent training for electronic engineering degree in artificial intelligence under multi-disciplinary of provincial colleges and universities.更多还原