[目的/意义] 调查数据科学课程群建设现状，聚焦数据科学人才培养方案，为我国高校信息学院数据科学教学实践提供参考和借鉴。[方法/过程] 基于UIUC （美国伊利诺伊大学香槟分校）信息科学学院的数据科学课程实践，首先调研该院数据科学相关课程的名称、简介、学制学时、授课形式、授课教师及授课对象，然后从培养对象类型、授课形式、授课合作程度和课程内容4个方面对课程群进行系统分类和比较分析，最后对我国高校数据科学课程建设提出若干建议。[结果/结论] UIUC数据科学课程群可分为六大类别，面向本硕博各阶段学生，采用线上线下相结合的混合式教学方式，通过教师合作开展授课，教学内容紧密跟随数据科学岗位市场需求。因此，我国高校在数据科学领域应强化培育连续性、丰富教学创新性、加强教师授课合作性、增强研究方向完备性。
[Purpose/significance] This paper studied the current construction of data science curriculum groups, focuses on the training program of data science talents and provides references and advice for the data science practice of information colleges in China.[Method/process] Based on the data science curriculum practice of UIUC iSchool, this paper first investigated the name and introductions of the data science-related courses in detail, academic hours, teaching forms, the teachers and the subjects, then systematically classified the course groups and made a detailed comparative analysis from the 4 aspects:training object type, teaching forms, teaching cooperation degree, and the course content. Finally, this paper summarized the enlightenments and suggestions for the development of data science education in China in light of the current domestic situation.[Result/conclusion] In UIUC iSchool Data science courses can be divided into 6 categories, which are suitable for students at all stages. A mixed teaching method combining online and offline is adopted. Teachers cooperate with each other and the contents closely follow the data science job market requirements. Finally, the authors suggest that we should strengthen the continuity of cultivation, innovate teaching methods, improve teaching cooperation, and enrich research directions in the field of data science in China.
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