论文标题
为AI支持系统的教学软件工程
Teaching Software Engineering for AI-Enabled Systems
论文作者
论文摘要
软件工程师在构建智能系统时可以提供大量的专业知识，即即使建立在不可靠的组件上时，也可以利用可扩展，响应良好和健壮的数十年的经验和方法。具有人工智能或机器学习（ML）组件的系统提出了新的挑战，需要仔细的工程。我们设计了一门新课程，以向具有ML背景的学生讲授软件工程技能。我们特别超越了传统的ML课程，这些课程在人造条件下教授建模技术，并在讲座和作业中，在讲座和作业中，具有较大且不断变化的数据集，可靠和可发展的基础架构以及有目的的要求工程，并考虑道德和公平性。我们描述了课程，基础设施，共享经验以及第一次教学课程的所有材料。
Software engineers have significant expertise to offer when building intelligent systems, drawing on decades of experience and methods for building systems that are scalable, responsive and robust, even when built on unreliable components. Systems with artificial-intelligence or machine-learning (ML) components raise new challenges and require careful engineering. We designed a new course to teach software-engineering skills to students with a background in ML. We specifically go beyond traditional ML courses that teach modeling techniques under artificial conditions and focus, in lecture and assignments, on realism with large and changing datasets, robust and evolvable infrastructure, and purposeful requirements engineering that considers ethics and fairness as well. We describe the course and our infrastructure and share experience and all material from teaching the course for the first time.
