产教融合视角下人工智能专业教学改革创新探索——以数据挖掘与机器学习课程为例
DOI:
https://doi.org/10.6938/iie.060707Keywords:
产教融合, 人工智能专业, 数据挖掘与机器学习Abstract
在人工智能专业的教育体系中,课程教学的有效性对于人才培养至关重要。随着产教融合成为教育改革的重要趋势,如何在专业核心课程中有效落实这一理念已成为研究的重点。作为人工智能专业的核心课程,数据挖掘与机器学习旨在培养学生掌握相关原理和处理方法。该课程主要面向应用型本科大二学生,注重理论与实践相结合,并特别关注行业前沿技术的引入。通过学情分析发现,学生在学习中普遍存在理论知识薄弱、难以触及技术前沿以及行业对接不易等问题。针对这些问题,课程提出了“理论深化、前沿探索、应用实践、行业对接、思政融通”的教学理念,构建“产学研用”四位一体的课程体系,实施“项目驱动式”实践教学模式,并引入行业导师制等创新举措。自实施以来,这些产教融合的改革措施已取得显著成效,为人才培养和行业发展提供了有力支持。
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