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.

翻译：建造和维护生产级ML驱动组件是一项复杂的工作,超出了目前学术教育方法的范围,重点是优化实验室的ML模型性能,在这份文件中,我们介绍了以项目为基础的学习方法来教授MLOPs,重点是示范和新出现做法和工具的经验,以将ML驱动组件的建造自动化,我们审查了以这一方法为基础的课程设计,包括涵盖从建模到生产部署的终端至终端ML组件生命周期的实验室会议。此外,我们报告了该课程第一版的初步结果。今年,同一课程的更新版本将在两所独立的大学提供;将评估相关的学习结果,以分析这一特定主题基于项目学习的有效性。