Knowledge-driven Practice for the Capstone Project Course of Data Science

摘要：

　　The rapid development of data applications poses severe challenges as well as significant opportunities for data science talent cultivation.On the demand for data analysis specialty,in this poster the authors report on some preliminary results of a knowledge-driven practice for the capstone project course of data science.The practice consists of the tier of knowledge generalization and specialization and the tier of data science practice.Three kinds of knowledge,including general knowledge from the perspectives of data science,domain knowledge from real-world applications,and engineering expertise knowledge for conducting data analysis process,are refined to implement data science practice to achieve solutions effectively and efficiently for real-world applications.Preliminary results indicate that knowledge-driven practice promotes students to improve the ability of data analysis efficiently,and students attending the course win world-class data analysis competitions,such as KDD (Knowledge Discovery and Data Mining) Cup and Kaggle.

关键词： Data Science capstone project course knowledge-driven practice domain knowledge general knowledge engineering expertise knowledge generalization and specialization data science practice

作者: Liang Bai Yanli Hu

作者单位: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,Changsha, Hunan, P.R.China, 410073

会议类型: 国际会议

会议名称: 2018中国图灵大会(ACM Turing Celebration conference-China 2018)

会议地点: 上海

会议语种:英文

页码: 125-126

在线出版日期: 2018-05-19（万方平台首次上网日期，不代表论文的发表时间）