Computational Linguistics

MA Full-time 12 months, Part-time 2 years

Institute Code W75
UCAS Code
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Start Date(s) 21 September 2020
Award MA
Study Mode Full-time, Part-time
Course Length Full-time (12 months), Part-time (2 years)
Campus Location Wolverhampton City Campus
School School of Humanities

Why choose this course?

Are you interested in working with cutting-edge technology at the forefront of language processing?

MA Computational Linguistics is a course run by a leading research group at the University of Wolverhampton. As a Masters student on this course, you will be part of our Research Institute of Information and Language Processing (RIILP), an independent, research-driven University unit specialising in Linguistics and Natural Language Processing.

As the name suggests, Computational Linguistics (sometimes called Natural Language Processing) is the use of computers to study language. On the course, you will be able to study:
•   How to use Python and the well-established NLTK library to process natural language texts;
•   How to analyse real language usage;
•   How to automatically translate text using computer programs;
•   The use of computers to study features of language;
•   Translation tools such as translation memory systems;
•   Computer techniques for automatically classifying natural language texts;
•   Understand how Siri, Amazon Echo and Google Home etc. work;
•   How to design an experiment that will thoroughly test your research questions.

You will be mentored through this programme by experienced and leading academics from the field. Join our research group today to become part of this team of leading researchers and academics and create your path to a career in computers and language!

What happens on the course?

MA Computational Linguistics, when studied full-time, comprises of three semesters worth 60 credits each. Three modules will be studied in both Semester One and Semester Two. During the third semester, students will undertake their research project and complete a 15,000 word dissertation on any aspect of Computational Linguistics.

The course covers all aspects of Computational Linguistics in-line with current and leading work in research and industry, and is divided into the following taught modules:
1. Computer programming in Python
The students will be taught the Python computer programming language, which is specially designed for dealing with natural language texts.
2. Corpus Linguistics in R
Corpus Linguistics involves storing large amounts of text on the computer for linguistic analysis. R is a programming language used to study the statistics of language.
3. Machine translation and other natural language processing applications
The automatic translation of text using statistics. The members of the Research Group will each speak on their own research areas throughout the module.
4. Computational Linguistics
The use of computers to study language at all levels, such as relations between words, part of speech tagging, syntactic parsing and anaphora resolution.
5. Translation tools for professional translators
Using computer tools to speed up many aspects of translation, such as product manuals, film scripts, medical texts, video games and simultaneous interpreting.
6. Machine learning for language processing
Computer techniques for automatically classifying natural language texts, for NLP tasks such as making summaries of text automatically.
7. Research methods and professional skills
You will learn how to design an experiment to thoroughly test your research questions.

Translation Tools for Professional Translators is an elective module that may be chosen in the Second Semester to replace another taught module for those students who are interested in pursuing careers in Translation.

You will be expected to dedicate 9 hours per week to lectures and a proportionate amount of time to self-study and tutorials with your supervisor.

Opportunities:
- You will be taught by leading researchers in the field: our teaching staff at the Research Institute of Information and Language Processing (RIILP) are engaged in high-quality research, as evidenced by the latest RAE 2008 and REF 2014 results.
- We offer an exciting programme of invited lectures and research seminars, attended by both students and staff;
- The institute has a wide network of contacts in academia and in the industry from which you will be able to benefit.

The knowledge and skills developed in the course will be assessed in a variety of ways. Assessments will include writing assignments on given topics, reports on practical work carried out in the class, portfolios, projects, oral presentations, and tests.

The culmination of the study programme will be your 15,000-word dissertation, which will allow you to carry out an in-depth study of a chosen topic within the areas of corpus linguistics, language teaching, lexicography, or translation.

Course Modules

Module: 7LN004

Credits: 20

Period: 1

Type: Core