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An Application Driven Big Data/Machine Learning Education program for Engineering Professionals — Methods and Examples

机译:应用驱动的面向工程专业人士的大数据/机器学习教育计划—方法和示例

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Complexity is the new normal. Thus the constantly evolving tools in the open-source R/Python programming domains are of outmost importance for the applications of big data/machine learning tools. This implies that an engineering professional, who was not originally exposed to these subjects, is complexity challenged during continuing education, as there is a need to apply still more advanced data analysis/machine learning methods for information acquisition, aggregation and finally decision support, within many different engineering disciplines based on an increasing amount of applied statistics, linear algebra and optimization. This paper presents an application driven education program addressing this challenge. Initially the paper presents the main challenges to the continuing education. They are divided into the two areas: the technology drivers and the prerequisites of the very diversified population of todays engineering professionals. This is followed by a proposed Four Phase education program with R/Python script snapshots presenting machine learning model examples and examples on application driven company relevant projects. Finally the paper presents suggestions for possible future road-maps for continued education. This paper is mainly targeted those who are in an initial process of establishing a program for continued education of non specialists within the community of engineering professionals. It proposes a selection of very practical tools and structures, which aim at supporting a fast hands-on introduction to two integrated development environments (IDE's) for the programming languages R and Python and their practical applications.
机译:复杂性是新常态。因此,在开源R / Python编程领域中不断发展的工具对于大数据/机器学习工具的应用至关重要。这意味着原本没有接触这些学科的工程专业人士在继续教育期间面临着复杂性挑战,因为有必要将更高级的数据分析/机器学习方法应用于信息获取,汇总和最终决策支持中。基于越来越多的应用统计,线性代数和优化的许多不同的工程学科。本文提出了一种应用程序驱动的教育计划,以应对这一挑战。最初,本文提出了继续教育的主要挑战。它们分为两个领域:技术驱动力和当今工程专业人才非常多样化的前提条件。接下来是拟议的带有R / Python脚本快照的“四阶段”教育程序,其中提供了机器学习模型示例以及有关应用程序驱动的公司相关项目的示例。最后,本文提出了可能的未来继续教育路线图的建议。本文主要针对那些正处于初始阶段的人员,这些人员正在制定计划,以继续进行工程专业人员社区中的非专业人员的继续教育。它提出了一些非常实用的工具和结构的选择,旨在支持针对R和Python编程语言及其实际应用的两个集成开发环境(IDE)的快速动手介绍。

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