Software engineers have significant expertise to offer when building intelligent systems, drawing on decades of experience and methods for building systems that scale and are responsive and robust, even when built on unreliable components. Systems with artificial-intelligence or machine-learning components raise new challenges and require careful engineering. We designed a new course to teach software-engineering skills to students with a background in machine learning. We specifically go beyond traditional machine-learning courses that teach modeling techniques under artifical conditions and focus, in lecture and assignments, on realism with large and changing datasets, robust and evolvable infrastructure, and purposeful requirements engineering that considers also ethics and fairness. We describe the course and our infrastructure and share experience and all material from teaching the course for the first time.