Instructional Model for Building Effective Big Data Curricula for Online and Campus Education

Y. Demchenko, Emanuel Gruengard, S. Klous
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引用次数: 32

Abstract

This paper presents current results and ongoing work to develop effective educational courses on the Big Data (BD) and Data Intensive Science and Technologies (DIST) that is been done at the University of Amsterdam in cooperation with KPMG and by the Laureate Online Education (online partner of the University of Liverpool). The paper introduces the main Big Data concepts: multicomponent Big Data definition and Big Data Architecture Framework that provide the basis for defining the course structure and Common Body of Knowledge for Data Science and Big Data technology domains. The paper presents details on approach, learning model, and course content for two courses at the Laureate Online Education/University of Liverpool and at the University of Amsterdam. The paper also provides background information about existing initiatives and activities related to information exchange and coordination on developing educational materials and programs on Big Data, Data Science, and Research Data Management.
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构建有效的网络与校园大数据课程的教学模式
本文介绍了目前的成果和正在进行的工作,以开发有效的大数据(BD)和数据密集型科学与技术(DIST)的教育课程,这是由阿姆斯特丹大学与毕马威和桂冠在线教育(利物浦大学的在线合作伙伴)合作完成的。本文介绍了大数据的主要概念:多组件大数据定义和大数据架构框架,为定义数据科学和大数据技术领域的课程结构和共同知识体系提供了基础。本文详细介绍了劳瑞德在线教育/利物浦大学和阿姆斯特丹大学的两门课程的方法、学习模式和课程内容。本文还提供了与信息交流和协调有关的现有倡议和活动的背景信息,以开发大数据、数据科学和研究数据管理的教育材料和计划。
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