The motivation, philosophy, and organization of a course on artificial intelligence in chemical engineering is presented. The purpose is to teach undergraduate and graduate students how to build AI-based models that incorporate a first principles-based understanding of our products, processes, and systems. This is achieved by combining "symbolic" AI with data-driven "numeric" AI. In this respect, this course is different from the standard machine learning course, which typically does not address the symbolic AI component.