Generative artificial intelligence

This unit covers the theoretical and practical foundations of Generative Artificial Intelligence (GenAI), building on prior knowledge of deep learning. The unit begins with essential Natural Language Processing (NLP) concepts that underpin modern generative systems, such as text representation, contextual embeddings, and sequence modelling. You then progress to large language models (LLMs), advanced generative techniques including variational autoencoders (VAEs), generative adversarial networks (GANs), and diffusion models, as well as their integration into real-world applications such as conversational systems, summarisation, translation, and multimodal AI.

Throughout the unit, you will critically evaluate the architectures and training strategies that power generative systems, with strong emphasis on ethical, societal, and regulatory considerations. By the end of the unit, you will be able to design, apply, and evaluate generative AI solutions responsibly across various complex domains.