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!
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.
Figures speak louder than words: the University of Wolverhampton boasts an outstanding graduate employability rate – 96% of students are in work or further training six months after graduation!
Facilities
The course will be run on the City Campus, which is situated in the heart of the city centre, only a seven-minute walk from both the train station and St Georges Metro terminus, and a five-minute walk from the main bus station.
The newly renovated City Campus features:
- The Harrison Learning Centre, which has four floors of electronic, online, hardcopy and audio-visual materials;
- The Technology Centre, which has 500 PCs available for your personal use;
- A 'Social Learning Space', which incorporates a coffee and sandwich bar with islands of PCs and comfortable seating;
- On-campus food court, shops, and outlets such as Starbucks;
- Sports facilities including a gym and a sports hall;
- Three Halls of Residence for 1,000 students, located only a short walk from the campus and next to a 24-hour supermarket;
- City centre location, close to all amenities (post office, restaurants, shopping centres, art gallery, theatre etc.);
- Excellent train connections to all major cities (Birmingham: 20 minutes, London: 1 hour 50 minutes).
The researchers leading the course are international experts in their fields.
Dr. Michael Oakes
Course Leader and Reader in Computational Linguistics
Research Group in Computational Linguistics
Dr. Oakes is the author of the books “Statistics for Corpus Linguistics” and “Literary Detective Work on the Computer”.
Modules: Computational Linguistics, Corpus Linguistics with R.
Dr. Constantin Orasan
Reader in Computational Linguistics, Deputy Head of the Research Group
Research Group in Computational Linguistics
Dr. Orasan is the coordinator of the EU-funded EXPERT programme on Machine Translation which comprised of a consortium of 6 academic partners, 3 commercial partners and 2 associated partners.
Modules: Python Programming, Machine Learning.
Dr. Victoria Yaneva
Research Associate
Research Group in Computational Linguistics
Dr. Yaneva was recently featured on ITV news for her work on simplifying text for people with autism.
Modules: Research Methods and Professional Skills.
Guest lectures will be given by Prof. Patrick Hanks, a world authority in Lexicography, and Prof. Ruslan Mitkov, Director of the Research Institute of Information and Language Processing, Editor of the “Oxford Handbook of Natural Language Processing” and Executive Editor of the Cambridge Journal “Natural Language Engineering”.
Learn more about our Research Group through visiting our website. Find out about current members, recent news, projects and read past papers written. http://rgcl.wlv.ac.uk/
Follow us on Twitter to keep up to date with our latest news and developments at @RGCL_WLV.
Watch recently graduated PhD student and now Research Associate, Dr. Victoria Yaneva, share her research on ITV Central into innovative technology to assist people with Autistic Spectrum Disorder with their digital text comprehension. https://www.youtube.com/watch?v=9YbLfekcx8w&feature=youtu.be
Find out about Dr. Vinita Nahar’s (past group member) innovative research into technology to detect Cyberbullying online http://www.itv.com/news/central/topic/cyber-bulling/.
Graduates of this course will be well-placed to continue their academic/research careers by applying for PhD positions within RIILP or at other leading centres for language and information processing. This degree will also enable graduates to access research and development positions within the language processing and human language technology industries, as well as in related areas such as translation, software development and information and communication technologies, depending on their specific module choices and dissertation topic. It should be noted that computer programming is a skill that is increasingly sought after by many companies from technological backgrounds and skills gained from this course will place graduates in a good position to take up such posts. Past graduates from this course have also gone on to successful careers specifically within the computer programming industry.
The practical sessions include working with tools and software and developing programs based on the material taught in the lectures, allowing you to apply the technical skills you are learning. Some of the tasks are group based, feeding into the collaboration aspect of blended learning which enhances team-working skills, and some are done individually. Through portfolio building, you will be able to share your learning with other students. You will also be able to enhance your employability by sharing your online portfolio with prospective employers. Some assessments will require you to present your work to the rest of the class, enabling you to develop your presentation skills, which are useful in both academia and industry. Other transferrable skills are the abilities to structure your thoughts, present your ideas clearly in writing and prepare texts for a wider audience. You will acquire these skills through assessed report and essay writing, and most of all through writing your dissertation.
Feedback from Student A:
What I have enjoyed about this course?
I enjoyed being taught various topics. This course allowed me to see all the potential of Natural Language Processing--my favourite topic was Corpus Linguistics. I also enjoyed the projects that we carried out during this course.
Who would I recommend it to?
I would recommend this course to people interested in linguistics or languages in general to show them that linguistics can also be paired with Computer Science and to those interested in Computer Science, for it could show them a new application to Computer Science.
What I have gone on to do?
I am now looking for a graduate job that would allow me to use the skills I learnt during this course. Besides, I am writing a paper in natural language processing, which will probably be published in the International Journal of Corpus Linguistics.
How I have benefitted from this course?
Thanks to this course, I know what I want to do in the future; I want to be a Professor of Corpus Linguistics. I also have got several opportunities for a PhD in the US. Besides, I also learnt how to use a few programming languages, which is of great importance nowadays if one wants to find a job.
Feedback from Student B:
What I have enjoyed about the course?
I enjoyed Python. It helped me a lot to develop a good understanding of how a program works and get manipulated by users in order to achieve the results required. Even though I have finished the course, I am still developing my skills in Python to create a simple project based on deep learning in the future.
Who would I recommend it to?
I would recommend this course to the individuals who seek to increase their knowledge of Machine Learning and Natural Language Processing. These two fields are enjoyable and challenging at the same time to me. Therefore, the people who want to understand how, say, SIRI works, should join this course.
What I have gone on to do?
Hopefully, I will do my PhD in the future. I am planning to take my skills in programming further beyond what I have learnt from the course. Also, I will, hopefully, benefit my beloved Arabic language in the field of NLP.
Feedback from Student C:
What I have enjoyed about the course?
I particularly enjoyed the programming aspects of the course.
What I have gone on to do?
I am a DevOps engineer.
How I have benefitted from this course?
I used it as a conversion degree to get into computer science.
These modules are correct at the time of publication. Modules may change over time due to validation and continuous monitoring policies. Applicants will be notified in writing of any significant changes to their chosen course(s).
| Title | Credit | Type | Year | Location |
|---|
| Computational Linguistics | 20.00 | Core | 1 | Wolverhampton City Campus |
| Corpus Linguistics with R | 20.00 | Core | 1 | Wolverhampton City Campus |
| Dissertation | 60.00 | Core | 1 | Wolverhampton City Campus |
| Machine Learning for NLP | 20.00 | Core | 1 | Wolverhampton City Campus |
| Python Programming | 20.00 | Core | 1 | Wolverhampton City Campus |
| Research Methods | 20.00 | Core | 1 | Wolverhampton City Campus |
| Machine Translation | 20.00 | Optional | 1 | Wolverhampton City Campus |
| Translation Technology | 20.00 | Optional | 1 | Wolverhampton City Campus |
The entry requirement would normally be a 2:1 undergraduate degree in a computer science, linguistics, translation, languages or mathematics. Exceptionally, a 2:2 would be considered upon a successful interview. Students with a linguistics or language-related discipline but without a background in computer science would be appropriately advised by the course team and additional specialist technical support provided where necessary. We also require IELTS 6.5 or above.
These fees are applicable for new entrants in 2019/20. Fees are for the academic year only, any subsequent years may be subject to an annual increase, usually in line with inflation.
Postgraduate Loans: Are available for taught and research Masters courses for students resident in England. For more information on eligibility and how to apply online visit: www.gov.uk/postgraduate-loan
Professional and Career Development Loan: The University is a Professional and Career Development Loans (PCDL) registered Learning Provider, registration number [4413]. A PCDL is a commercial bank loan that you can use to help pay for work-related learning. For further information on financial assistance to support your learning, please visit the GOV.UK website or contact the National Careers Service on 0800 100 900.
Charitable Funding: You might also want to explore the possibility of funding from charitable trusts; please see the following websites www.acf.org.uk, www.dsc.org.uk/fundingwebsites or www.family-action.org.uk. Most charities and trust funds offer limited bursaries targeted to specific groups of students so you will need to research whether any of them are relevant to your situation.
University Postgraduate Loyalty Discount: The University also offers a postgraduate loyalty discount (http://www.wlv.ac.uk/study-here/money-matters/financial-support/postgraduate-study/postgraduate-loyalty-discount/): If you have completed an undergraduate degree at the University of Wolverhampton, you may be eligible for a 20% discount on the first year of a taught postgraduate programme.
Financial Hardship: Students can apply to the Dennis Turner Opportunity Fund (http://www.wlv.ac.uk/study-here/money-matters/financial-support/dennis-turner-opportunity-fund/) for help with course related costs however this cannot be used for fees or to cover general living costs.
If you are paying for the fees yourself then the fees can be paid in 3 instalments: November, January and April. More information can be found at www.wlv.ac.uk/howtopay
