Exploration of Practical Teaching of Big Data Technology for Engineering Applications
In response to the problem of overly theoretical teaching in traditional big data courses,practical teaching methods are explored for engineering applications.Through the introduction of the practical case of the engineering project"Shear wave Velocity Structure Instant-imaging System for Microtremor Survey Based on Edge Computing",we guide students to participate in the key links such as load big data acquisition and pre-processing,load dynamic change law discussion,load prediction and calculation resource allocation,and cultivate their engineering application ability.Emphasizing teamwork and practical ability cultivation,the role of teachers is shifted from being knowledge imparters to learning guides,and the quality of education is improved by the support of information technology.The research results indicate that the teaching reform of big data courses driven by engineering projects can cultivate professional talents who meet the needs of engineering applications,effectively improving students'practical and problem-solving abilities.
big data technologyengineering applicationsmicrotremor surveyload forecastingpractice teaching
NETL
NSTL
万方数据
维普
