Curious about studying Computational Linguistics - BSc (Hons)at University of Essex? We've gathered all the key details—entry requirements, modules, fees, and more. Hear from real students by checking out reviews, or take the next step by booking an open day to explore it for yourself.
Bachelor of Science (with Honours) - BSc (Hons)
Colchester Campus
Full Time
Oct 2026
3 Year
An understanding of language enhances our self-awareness, inspiring us to address fundamental questions about our communication as human beings. Linguistics is an increasingly important subject, impacting on areas in psychology, philosophy, education and artificial intelligence. It has real-world applications in such diverse fields as human rights, computer-assisted language learning, and the study of institutional language in settings like doctor-patient interactions, interviewer-interviewee dialogues, and courtroom exchanges. This course will give you the unique skillset of using data science to tackle these topics by engaging with tools such as analysing large corpora of texts, conducting experiments, statistical analysis, and machine learning. It will allow you to develop your research and IT skills by collecting and analysing linguistic data using state-of-the-art technology, and a combination of team-work and independent projects will enhance your communication, problem-solving, and management skills. At Essex, you will acquire a broad foundation in the study of language. Our diverse research looks at this uniquely human phenomenon from several angles: the structures that exist in the world’s languages, the variation in how people speak them, how humans process and understand language, and how languages are learned and best taught. If you have a global outlook, are interested in human interaction and want real-world practical skills, welcome home.
This module introduces you to the production of language sounds and their distribution in words, in particular, but not exclusively, in English. You will study the basic principles of phonology and develop the knowledge required to understand and begin to analyse sound systems. You will also discuss phonological processes and investigate the context and motivation of occurrence.
Discover how to describe and analyse the structure of words, phrases, and sentences in this introductory half module. With topics including the English parts of speech, word structure and the distinction between inflection, derivation and compounding, and the identification of phrases, you will gain a solid grasp of the foundational material for the study of English linguistics, whilst developing useful analytical skills.
The aim of this module is to provide an introduction to the fundamental concepts of computer programming. After completing this module, students will be expected to be able to demonstrate an understanding of the basic principles and concepts that underlie the procedural programming model, explain and make use of high-level programming language features that support control, data and procedural abstraction. Also, they will be able to analyse and explain the behaviour of simple programs that incorporate standard control structures, parameterised functions, arrays, structures and I/O.
What are your skills? And how do they fit in with your career plans? Build your employability skills through this non-credit bearing but obligatory module. Attend workshops and events, engage in activities to raise your employability and build your knowledge of the graduate job market.
How do we receive and recognise speech? How are words and concepts stored in our mind? Building on your knowledge of Psycholinguistics gained in earlier modules, the focus of this module is on language processing. You will study how humans learn, represent, comprehend, and produce language. Topics covered include visual and auditory recognition of words, sentence comprehension, sentence production, language acquisition, and the neural representation of language. You will also have the opportunity to gain some practical experience with the elaboration of a research poster.
Relational databases and SQL are fundamental tools for applications in many different disciplines including humanities, life sciences, linguistics, marketing and social science. They are essential in almost all modern organisations for efficient information management in IT systems and commercial applications. The purpose of this module is to provide you with an introduction to the underlying principles of and practical experience in designing and implementing relational databases. It will cover data modelling and SQL, database analysis, design and management, and advanced topics including big data, security and privacy issues of modern databases.
This module covers the principles of linear modelling for analysing experimental and observational data. You will first study the assumptions of the general linear model, including collinearity, influential data, assessing fitted models and model selection techniques. You will then encounter statistical methods for efficient analysis of experiments with normally distributed data, such as one-way ANOVA, and extend the methodology to logistic regression and analysis of contingency tables with categorical variables of interest. Finally, you will study multivariate methods for the analysis of large, high-dimensional data sets.
What are your skills? And how do they fit in with your career plans? Build your employability skills through this non-credit bearing but obligatory module. Attend workshops and events, engage in activities to raise your employability and build your knowledge of the graduate job market.
What fascinates you about linguistics? Work independently on an extended project of your choosing within linguistics, with supervision from our expert staff. Build your subject knowledge, as well as your research skills and project management abilities.
In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience. For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.
This module introduces Artificial Intelligence (AI), the science of making computers and machines display intelligent behaviour. This multidisciplinary activity draws from computer sciences, mathematics and statistics, and also elements of philosophy, logic and even psychology. Today, AI is ubiquitous in society, from self-driving cars to spam filters and finance trading to video games. The increasing dependence on AI will reshape society and economy. Understanding AI principles, applications, and limitations is important for all students, regardless of their background, and this module assumes no prior knowledge. This module provides both theoretical and practical techniques, covering AI theory and fundamentals of machine learning models, as well as their implementation and applications.
What are your skills? And how do they fit in with your career plans? Build your employability skills through this non-credit bearing but obligatory module. Attend workshops and events, engage in activities to raise your employability and build your knowledge of the graduate job market.
4.3
