This course provides an in-depth treatment of advanced topics in Artificial Intelligence (AI), with a focus on perception and representation learning in visual and language-based modalities. The course covers areas such as computer vision and natural language processing, while maintaining a common conceptual foundation in modern machine learning and deep learning. You will gain a strong understanding of the theoretical principles and practical techniques underlying contemporary AI systems, including data representation, feature learning, probabilistic modelling, structured prediction, and optimisation. Core topics span both classical and modern approaches, covering domain-specific foundations (e.g.,image formation and geometry in vision;linguistic structure and semantics in language) as well as state-of-the-art neural architectures such as convolutional, recurrent, attention-based, and transformer models.