Through predictive text, translation tools, and smart devices natural language processing (NLP) is increasingly a part of our day-to-day lives, and in large language models like Chat-GPT we see the enormous future potential of this exciting area of research. This advanced course examines the theoretical concepts of NLP and its current and potential future application in diverse domains.
The course begins with an introduction to attention mechanisms, examining self-attention, transformers, and byte pair encoding, before turning to large language models (LLMs) and natural language generation, exploring how they use prompting and reinforcement learning with human feedback. You will look closely at the varied applications of NLP and LLMs in particular, such as question answering, translation, and code generation. In the final part of the course you will discover how language and vision can interact in applications such as video captioning or text to image generation, before looking to the future of NLP research and considering the limitations, biases, ethical concerns, and potential misuses of NLP.
This intensive course offers students theoretical understanding and practical experience in a range of natural language processing concepts and techniques, offering career skills as well as excellent foundations for future research.
