Course summary

Artificial intelligence and computational linguistics are transforming industries, from social media to marketing, by applying AI to language data. This programme offers a foundation in these techniques, perfect if you are looking to pursue a career in AI without a technical background. It’s led by our renowned Department of Linguistics. This programme will build your digital AI knowledge and skills and provide a solid foundation in AI methods applied to language data. You will understand how to apply your knowledge to real-world large datasets. You will develop the skills to understand, organise, clean, process, and analyse a range of data types. You will use the software R to develop skills at statistical computing and data visualisation. You will gain an understanding of how the various linguistic properties of text (word structure, sentence structure, word and sentence meaning, and discourse structure) are important in the computational processing of text, and how current computational models apply to extract information relevant to these properties. You will understand how machine learning systems work in this domain, what their advantages and limitations are both as theories and as tools, and where the field is currently heading. You will learn advanced concepts and algorithms in computational linguistics underlying contemporary generative AI models, for language. It covers core computational architectures (Hidden Markov Models, Recurrent Neural Networks, Long-Short Term Memory networks, Transformer architectures for LLMs), advanced linguistic concepts (constituency, ambiguity, dependency, semantic roles, affect, anaphora, and discourse cohesion) and how computational approaches, both symbolic and neural, can be applied to these. You will understand how different computational models are applied to different aspects of language structure and will develop their ability to use these tools to large language data sets You will get an introduction to computer programming and computational modelling for language as it is applied in various settings. You will learn how to write basic programmes in Python, understand their use in AI applications, and develop their ability to use these tools with large language data sets. You will learn the use of Python for data acquisition, cleaning, and analysis, particularly with datasets that relate to the Humanities and Social Sciences. You will learn how to write code in a widely used programming language (Python), understand the role of other languages (e.g. Java), and gain experience in using tools that are suited to solving a range of computational problems in linguistics using machine learning approaches. The Linguistics Department has strengths in statistical data processing of language, computational and experimental techniques relevant to language analysis, ethical, philosophical and computational theories, and core areas of linguistics (phonology, syntax, sociolinguistics, semantics, discourse).