Research on the Teaching Content of Deep Learning Courses in Higher Vocational Education for the Integration of Industry and Education, and the Integration of Science and Education

Abstract

Abstract: With the widespread application of artificial intelligence technology, vocational colleges have begun to attach importance to the construction of artificial intelligence technology application majors. As one of the core courses in vocational education, deep learning faces challenges such as rapid technological updates, broad knowledge domains, and steep learning curves. In order to address these issues, this article explores the problems faced in transforming technological achievements from the industry into deep learning teaching resources from the perspectives of industry education integration and science education integration. At the same time, guided by projects, it explores the design of deep learning curriculum content and verifies it through practical teaching and industry university research cooperation practices.

Key words: Integration of industry and education, Integration of science and education, Artificial intelligence technology application major, Deep learning, Project orientation, Content of courses

CLC Number:

G712

SONG Guiling, LYU Lixin, LI Feifei. Research on the Teaching Content of Deep Learning Courses in Higher Vocational Education for the Integration of Industry and Education, and the Integration of Science and Education[J]. The Theory and Practice of Innovation and Enntrepreneurship, 2024, 7(23): 47-49.

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