Teaching MLOps in Higher Education through Project-Based Learning

F. Lanubile, Silverio Mart'inez-Fern'andez, L. Quaranta
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引用次数: 2

Abstract

Building and maintaining production-grade ML-enabled components is a complex endeavor that goes beyond the current approach of academic education, focused on the optimization of ML model performance in the lab. In this paper, we present a project-based learning approach to teaching MLOps, focused on the demonstration and experience with emerging practices and tools to automatize the construction of ML-enabled components. We examine the design of a course based on this approach, including laboratory sessions that cover the end-to-end ML component life cycle, from model building to production deployment. Moreover, we report on preliminary results from the first edition of the course. During the present year, an updated version of the same course is being delivered in two independent universities; the related learning outcomes will be evaluated to analyze the effectiveness of project-based learning for this specific subject.
基于项目学习的高等教育MLOps教学
构建和维护生产级支持ML的组件是一项复杂的工作,它超越了当前的学术教育方法,专注于实验室中ML模型性能的优化。在本文中,我们提出了一种基于项目的学习方法来教授MLOps,重点关注新兴实践和工具的演示和经验,以自动化构建支持ml的组件。我们研究了基于这种方法的课程设计,包括涵盖端到端ML组件生命周期的实验室课程,从模型构建到生产部署。此外,我们还报告了课程第一版的初步结果。今年,两所独立的大学正在提供同一课程的最新版本;将评估相关的学习成果,以分析基于项目的学习对该特定主题的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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