The proposed AI for Chemistry course is designed to enable postgraduate students to deeply understand the integration of artificial intelligence technologies with chemical research and applications. The course covers fundamental concepts and working principles of AI methods such as machine learning, deep learning, and neural networks, and their applications in diverse chemical disciplines, including drug discovery, materials science, computational chemistry, and analytical sciences. Through critical review and discussion of recent literature, students will explore the latest AI-driven advancements in areas like molecular modeling, reaction prediction, and spectroscopic analysis, evaluating their advantages, limitations, and challenges for chemical R&D. Individual literature reviews will prompt students to identify current chemical problems and propose innovative AI-based approaches to derive chemical insights. Upon completion, students will be capable of designing AI-empowered experimental strategies or computational workflows, combining appropriate AI tools to address complex problems in chemistry.