Pathways for Cultivating Artificial Intelligence Talent in the Context of New Engineering Education Development
- DOI
- 10.2991/978-94-6463-502-7_61How to use a DOI?
- Keywords
- New Engineering Disciplines; Artificial Intelligence; Talent Cultivation Path
- Abstract
Currently, China has proposed the concept of “construction of new engineering disciplines,” and new engineering majors, represented by artificial intelligence, have new demands for talents that align with industry development needs. These demands include comprehensive knowledge, practical ability, innovative consciousness, and a forward-looking perspective. This paper constructs an AI talent training system from four aspects: interdisciplinary integration, curriculum system, practical platform, and teaching staff, aiming to cultivate application-oriented, innovative, and compound talents with engineering theoretical capabilities that meet the needs of engineering career development. It is hoped that under the dual drive of the construction of new engineering disciplines and “Double First-Class” initiatives, artificial intelligence technology will contribute to the construction of an innovative country.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Fei Wang PY - 2024 DA - 2024/08/31 TI - Pathways for Cultivating Artificial Intelligence Talent in the Context of New Engineering Education Development BT - Proceedings of the 2024 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024) PB - Atlantis Press SP - 585 EP - 594 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-502-7_61 DO - 10.2991/978-94-6463-502-7_61 ID - Wang2024 ER -