面向大数据人才培养的算法实践能力提升改革——以《机器学习基础实践》为例

Reform for Improving Algorithmic Practice Capabilities in Big Data Talent Training—Taking “Basic Practice of Machine Learning” as an Example

摘要: 机器学习基础实践课程在大数据人才培养过程中发挥着不可替代的重要作用，因此探究该课程的教育教学改革具有重要的意义。文章针对课程教学中存在的问题，提出了面向大数据人才培养的算法实践能力提升改革方案。方案通过优化教学内容，完善课程资源，丰富教学手段以及提升考评机制等举措不断强化学生的实践创新能力。通过本文的研究，有望构建全方位多维度的机器学习实践课程体系，收获更好的教学效果，为大数据及其他新兴学科的实践教学提供有价值的参考，对提高人才培养质量具有积极作用。

Abstract: The foundational practical course of machine learning plays an irreplaceable and significant role in the cultivation of talents in big data. Therefore, investigating the educational and teaching reforms of this course holds important significance. This article puts forward a reform scheme for enhancing algorithmic practical abilities aimed at cultivating talents in big data. The scheme continuously strengthens students’ practical innovation capabilities by optimizing the teaching content, improving course resources, enriching teaching methods, and enhancing the evaluation mechanism, addressing the problems existing in the course’s teaching. Through this research, it is anticipated to construct a comprehensive and multi-dimensional system for the practice of machine learning courses, achieving better teaching outcomes. This will provide valuable references for the practical teaching of big data and other emerging disciplines, and play a positive role in improving the quality of talent cultivation.