Reform and Innovation of Python Language Course Teaching System in the Era of Big Data

在人工智能与大数据技术快速发展的背景下，Python语言作为核心工具，其教学体系亟需改革以适应行业需求。本文聚焦高校大数据专业的Python课程，系统分析了当前存在的五大问题：课程内容滞后、实践环节薄弱、与行业需求脱节、专业同质化严重、师资专业性不足。针对这些问题，提出创新性改革策略，包括构建动态化课程更新机制追踪前沿技术、重构三层实践教学体系强化工程能力、设计差异化课程突出大数据特色、深化产教融合引入企业资源，以及通过师资培训提升教师实践水平。实践表明，改革后的课程实现了每学期20%案例更新，学生实践能力显著增强，产教合作成果丰硕，并培养出多领域竞赛获奖人才。该研究为培养具备数据思维与工程能力的复合型人才提供了可借鉴的路径，对推动教育数字化与行业需求对接具有重要参考价值。Against the backdrop of the rapid development of artificial intelligence and big data technology, the teaching system of Python language, as a core tool, urgently needs reform to meet the demands of the industry. This paper focuses on the Python courses in the big data major of universities, systematically analyzing the five major existing problems: outdated course content, weak practical links, disconnection from industry demands, severe homogenization of majors, and insufficient professional competence of teachers. In response to these issues, innovative reform strategies are proposed, including establishing a dynamic course update mechanism to track cutting-edge technologies, reconstructing a three-tier practical teaching system to enhance engineering capabilities, designing differentiated courses to highlight the characteristics of big data, deepening industry-education integration to introduce enterprise resources, and improving teachers’ practical skills through training. Practice shows that the reformed courses have achieved a 20% case update every semester, significantly enhanced students’ practical abilities, yielded rich industry-education cooperation results, and cultivated talents who have won awards in multiple fields. This research provides a referenceable path for cultivating compound talents with data thinking and engineering capabilities, and has important reference value for promoting the alignment of educational digitalization with industry demands.