Materials informatics integrates materials science and engineering with artificial intelligence (AI), machine learning (ML), and database to accelerate the innovation in the whole materials development continuum and to speed up the process from data to material knowledge. The 2024 physics and chemistry Nobel Prizes on AI are greatly promoting and accelerating the development of materials informatics. This is a continued course in materials informatics to introduce advanced AI and ML algorithms with more focus on global Bayesian optimization, transfer learning, transformer, and graph neural networks. The course will be lectured through vivid and practical examples from materials science and engineering. Notably, this course is designed for students whose majors are in broader fields of sciences and engineering, but not in AI and computer sciences and engineering. This course will empower those with limited knowledge of AI and ML to learn Materials Informatics without too much difficulty.