Developing a Data Science Course to Support Software Engineering Students

R. Acuña
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Abstract

Introducing software engineering students to data science provides an opportunity to reinforce foundational topics while also introducing students to emerging technologies. This paper discusses the experience of developing an undergraduate course that introduces data science. In addition to coverage of techniques in data management, data exploration, and machine learning, the course has a focus on scientific thinking along with the application of tools from software engineering. In contrast to the more common machine-learning first approach of applying algorithms and justifying them in terms of a numerical accuracy measure, we emphasize understanding data and drawing conclusions in an explainable way. In this work, we show how several foundational topics as defined by the Software Engineering Body of Knowledge (SWEBOK) map to topics in our data science course. We also discuss the design of a semester-long project that is used to elicit various data science skills.
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开发数据科学课程以支持软件工程专业的学生
向软件工程专业的学生介绍数据科学提供了一个加强基础主题的机会,同时也向学生介绍了新兴技术。本文讨论了开发一门介绍数据科学的本科课程的经验。除了涵盖数据管理、数据探索和机器学习技术外,本课程还侧重于科学思维以及软件工程工具的应用。与更常见的机器学习首先应用算法并根据数值精度测量来证明它们的方法相反,我们强调以可解释的方式理解数据并得出结论。在这项工作中,我们展示了软件工程知识体系(SWEBOK)定义的几个基础主题如何映射到我们的数据科学课程中的主题。我们还讨论了一个学期项目的设计,该项目用于引出各种数据科学技能。
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