Jennifer Foster

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In this major, we cover the primary topics of Natural Language Processing, which encompass both language generation (automatically generating language or text) and language understanding (automatically analysing and making sense of language or text). This includes Natural Language Processing tasks such as question answering, machine translation, syntactic and semantic parsing, opinion mining and sentiment analysis, summarisation and language proofing. We cover a variety of fascinating approaches including rule-based and machine-learning-based methods, as well as the very latest methods grounded in neural language models. 

We explore key methods to evaluate and explain the output of Natural Language Processing systems, and of course, we also explore the ethical implications of developing these systems. Students on the course gain hands-on experience in developing, evaluating and interpreting NLP systems in tasks such as machine translation, sentiment analysis and question answering. In addition to their module assignments, they carry out a significant practical project on an NLP topic of their choosing, supervised by an expert in the area.

A student should study NLP because it’s a fascinating and exciting subject at the forefront of Artificial Intelligence. It brings together aspects of both computer science and language (or linguistics). It’s a very practical area with a wide range of applications across any domain you can think of including medicine, law, education, media, finance and marketing. It’s a rapidly growing area given the recent advances in Transformer language models such as GPT.

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