This course aims to provide students with an in-depth critical understanding of Computer Vision's principles, concepts, and advanced techniques. The main objective of this course is to develop students with the fundamental knowledge of how machines understand and process data in the visual world. The outline of this course includes the topics of computer vision from the perspectives of low-level image processing (e.g., image mathematical and physical modelling, image enhancement, image coding, and filtering, edge and contour detection, image statistics analysis) and high-level visual semantic understanding (e.g., image recognition, image segmentation, motion analysis), along with different real-world applications where computer vision techniques have been applied. This course will also provide students with the understanding of cutting-edge technologies, such as foundation model and out-of-distribution generalization.