创新创业理论研究与实践 ›› 2024, Vol. 7 ›› Issue (17): 51-53.

• 教学革新 • 上一篇    下一篇

新质生产力时代要求背景下的大学机器学习课程探索与研究

焦文华, 李丽娟, 张印强, 梅雪, 王莉, 刘芃   

  1. 南京工业大学 电气工程与控制科学学院,江苏南京 211816
  • 出版日期:2024-09-10 发布日期:2024-11-28
  • 作者简介:焦文华(1990—),男,江苏江阴人,博士研究生,讲师,研究方向:工业人工智能与大数据。
  • 基金资助:
    江苏省教改课题“面向流程工业转型的‘智能+'专业群学科交叉人才跨院跨界培养模式”(2023JSJG345); 南京工业大学教改课题“工程意识视角下项目贯穿多教学环节的教学方法探索”(20230050); 南京工业大学教改课题“‘课程牵引轴—平台落实轴—竞赛训练轴'三轴联动的智能制造工程双创人才培养模式”(20230010)

Exploration and Research on University Machine Learning Courses in the Context of the Requirements of New Productive Forces

JIAO Wenhua, LI Lijuan, ZHANG Yinqiang, MEI Xue, WANG Li, LIU Peng   

  1. College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing Jiangsu, 211816, China
  • Online:2024-09-10 Published:2024-11-28

摘要: 该文针对新质生产力要求背景下的机器学习课程体系进行探索,对课程在大学创新型人才培养中的必要性、教学设计和实践教学评价等问题进行研究;明确机器学习对于新时代创新人才培养的重要性,设计创新培养教学方案,研究以能力培养为导向的教学评价方案,加强新质生产力要求下的创新人才培养教学体系建设。

关键词: 新质生产力, 创新人才, 产教融合, 机器学习, 课程教学, 人才培养

Abstract: This paper explores the machine learning curriculum system under the background of new quality productive forces, focusing on the necessity of the course in fostering innovative talent in universities, instructional design, and practical teaching evaluation. The importance of machine learning in cultivating innovative talent in the new era has been clearly defined. An innovative training teaching plan has been devised, additionally, a teaching evaluation scheme guided by competency development has been investigated to strengthen the construction of the educational system for cultivating innovative talent in line with the requirements of new productive forces.

Key words: New quality productive forces, Innovative talent, Industry-academia integration, Machine learning, Course teaching, Personnel training

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