"人工智能+"下财经类院校深度学习课程建设探索OA

Against the backdrop of the"Artificial Intelligence+"national strategy and the construction of the New Liberal Arts,this paper addresses critical pain points in Deep Learning courses at finance and economics universities,such as the decoupling of training objectives from management scenarios and the lack of disciplinary characteristics in teaching resources.We propose and implement a three-in-one course construction model:"problem orientation,interdisciplinary integration,and practical application".First,adhering to problem-orientation,the curriculum system is reconstructed around typical management science decision-making tasks,such as demand forecasting and resource scheduling,to clarify the logic that"technology serves decision-making".Second,by strengthening interdisciplinary integration,deep learning algorithms are aligned with optimization theories and statistical intuitions in management science,effectively lowering the cognitive threshold for students of economics and management.Finally,emphasizing practical application,a semester-long integrated case study based on New York City Taxi and Limousine Commission(TLC)big data is designed to guide students through a closed-loop practice,moving from algorithmic modeling to management decision-making within real-world management contexts.The three-in-one model provides a replicable reform paradigm for the cultivation of digital-intelligence-driven composite talents under the framework of New Liberal Arts.