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Study on the Innovation and Reform of Public Security Big Data Course Teaching Empowered by Artificial Intelligence

Ying Yuan, Xun Wang, Feng Wang

Abstract


Against the background of the rapid development of the public security big data strategy and artificial intelligence technology, the
course "Big Data Technology and Application" for non-computer majors is facing three core dilemmas: backward technology, weak practice,
and disconnection from business. Based on the construction concept of "New Public Security Disciplines", this study breaks through the
limitations of traditional teaching and constructs a new AI-empowered integrated teaching paradigm with "intelligent collection-interactive
analysis-multidimensional presentation" as the main line. Practice shows that this reform can effectively lower the learning threshold for noncomputer major students, significantly improve their abilities in data acquisition, interactive analysis, and intelligence presentation in real
police scenarios, thereby systematically solving the teaching problems of "being unable to learn, connect, and apply" for non-computer major
students, and truly realizing the practical training of "business + technology" compound public security talents.

Keywords


Artificial Intelligence; Big Data Course; New Public Security Disciplines; Teaching Reform; Practical Teaching

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References


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DOI: http://dx.doi.org/10.70711/aitr.v4i1.9646

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