The rapid evolution of Artificial Intelligence (AI) presents both challenges and opportunities for programming education. Traditional teaching modes in Python courses often struggle to keep pace with industrial demands and technological advancements

leading to a gap between acquired skills and practical application. This paper analyzes the prevalent issues in current Python teaching

including disconnection from AI frontiers

monotonous pedagogy

insufficient resources

a single evaluation system

and lack of deep industry-academia collaboration. In response

we propose a systematic reform plan centered on a "Three Integrations

Three Innovations

and Three Links" framework. This model emphasizes the deep integration of artificial intelligence tools

such as DeepSeek and intelligent code analysis tools

a blended dual-mentor teaching approach

and the construction of a multidimensional evaluation system. By restructuring course content

innovating practice models

and forging a seamless cultivation loop

the reform aims to enhance students' practical and innovative abilities. The paper also discusses potential challenges in implementation and corresponding strategies. This model provides a replicable and scalable reference for the reform of programming courses in the context of "New Engineering Education" in universities.