基于Gitee与学科竞赛任务驱动的机器学习实践课程教学设计与探索
Design and Exploration of Machine Learning Practice Course Teaching Based on Gitee and Subject Competition Task Driven
夏吉安1
作者信息
- 1. 南京工业职业技术大学 计算机与软件学院,江苏南京 210023
- 折叠
摘要
该文针对目前职教本科院校人工智能相关专业人才培养的新目标和实际教学需求,分析了机器学习实践教学中存在的不足和问题,以学科竞赛任务为驱动进行理念设计与开发实践课程内容.此外,该文结合Gitee虚拟化教学平台,进行实践课程内容的组织与教学,创新实践课程的设计方法,提高机器学习实践课程的教学质量,丰富实践教学设计方式.
Abstract
Aiming at the new goal and demand of artificial intelligence-related talents training in vocational education colleges,this paper analyzes the shortcomings and problems existing in practical teaching of machine learning.Design and develop practical course content through the concept of subject competition task driven.In addition,combining with the virtual teaching platform of Gitee,the organization and teaching of practical course content are carried out to innovate the design method of practical course,improve the teaching quality of machine learning practical course and enrich the methods of practical teaching design.
关键词
机器学习/实践教学/竞赛驱动/Gitee平台/创新实践/教学改革Key words
Machine learning/Practical teaching/Competition driven/Gitee platform/Innovative practice/Teaching reform引用本文复制引用
基金项目
2022年度中国高等教育学会科学研究规划课题(22GDZY0405)
2020年度中国高校产学研创新基金项目(2020HYB02005)
2020年度江苏省工业软件工程技术研究项目(ZK20-04-12)
出版年
2024
NETL
NSTL
维普
万方数据