Affiliations: [a] Department of Electrical Automation, Hebei University of Water Resources and Electric Engineering, Cangzhou, China | [b] Marxist College of Hebei University of Water Resources and Electric Engineering, Cangzhou, China
Correspondence:
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Corresponding author: Chunyan Wu, Marxist College of Hebei University of Water Resources and Electric Engineering, Cangzhou, China. E-mail: [email protected].
Abstract: With the continuous development of deep learning and artificial intelligence, its application potential in the field of education has attracted wide attention. This study mainly discusses the application of deep learning in college students’ career planning and entrepreneurship. First, through a comprehensive review of existing literature, the gaps and challenges of current research are revealed. Subsequently, empirical research methods were used to collect data on college students’ attitudes and feelings towards deep learning in career planning and entrepreneurship. This study develops and validates a model that predicts how deep learning interventions affect college students’ career choices and entrepreneurial intentions, while also proposing a series of strategic recommendations. The findings suggest that deep learning can be used as an effective tool to help college students better plan their careers and enhance their entrepreneurial abilities. This study not only provides a new perspective for theoretical research, but also provides useful insights and tools for practitioners.
Keywords: Deep learning, career planning, college student entrepreneurship
