Why do languages change? Why does your mobile device suggest funny completions for words you are typing? How did it happen that Finnish is spoken mostly in Finland, but its linguistic relatives are scattered over a larger area? How can you study a language that does not have a standard orthography? Why can you sometimes tell where other people come from just by their accent? Why do some people stick to their dialect, but others give it up when they move to the city? Should you try to support language diversity? Can we save languages that are spoken by a very small number of people? How can computer-synthesised speech be made to sound more human? Why do some languages seem so much more difficult to learn - are they inherently more complex?
This Master's programme will provide you with an understanding of the nature and diversity of human language and with the theoretical tools for working with language material. If you are interested in languages but are unable to decide which of them you want to study, this Master's programme offers several fields of specialisation. One of them might be just perfect for you.
During your studies, you will:
After completing your studies, you will be able to work independently in various fields that require multidisciplinary expertise in linguistic sciences. You will have the theoretical knowledge and skills that are required for postgraduate studies in the doctoral programme in language studies.
Further information about the studies on the Master's programme website.
Linguistic Diversity in the Digital Age is an integrated international programme that offers you a comprehensive view of all subfields of the science of language. As a student in the programme you will be able to choose among four specialist options: (1) General Linguistics, (2) Phonetics, (3) Language Technology, and (4) Diversity Linguistics.
General Linguistics gives you comprehensive in-depth training in a wide range of theoretical and methodological approaches to language structure and language in use. Special emphasis is put on language typology in a global perspective as well as the documentation and description of endangered and previously undocumented and under-documented forms of speech.
Phonetics will introduce you to the tools for working with the articulatory, acoustic and perceptional aspects of human speech from a multidisciplinary perspective. At the more advanced level, you will become acquainted with the methods of experimental phonetics.
Language Technology combines linguistics with digital technology in an interdisciplinary approach with close links to computer science. The focus areas include natural language processing (NLP) for morphologically rich languages, cross-lingual NLP and language technology in the humanities.
Diversity Linguistics encompasses all aspects of linguistic diversity in time and space, including historical linguistics as well as the extralinguistic context of languages: ethnicities, cultures and environments. The areal foci in Diversity Linguistics are Eurasia and Africa.
These four specialist options interact at all levels. There is a study module common to all students in the programme regardless of the specialist option they choose. The integration of these four perspectives into one programme is unique - no similar programme exists anywhere else.
In the context of “Humanities”, the programme has the closest relationship to natural sciences, and many subfields of the programme involve methods directly linked to laboratory sciences, including digital technology and neurosciences.
The teaching in the programme includes lectures and seminars, practical exercise sessions, reading circles, fieldwork excursions, as well as work practice (internship). The broad spectrum of teaching methods guarantees optimal support for your learning processes.
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.
- 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.
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.
IMF Business School, in collaboration with the Camilo José Cela University, launches the Master in Business Analytics and Big Data. This program aims to provide students with a global view of Big Data technologies and their use, as well as applied and practical training in Business Analytics. IMF is a member of the Association of Computer Technicians (ATI).
This Master's degree is aimed at both new graduates and experienced professionals who wish to focus on the new professions related to data analysis (Data Analyst, Data Scientists, Chief Data Officer, Data Engineer ...). The recommended access profiles are those related to ICTs, careers with a high qualitative component, and careers in business and economics.
The Master's Degree in Big Data of IMF, of an academic year of duration, is taught in online mode supported by an advanced technological platform that allows the student to access the study, regardless of geographical location or time availability.
With the IMF Student Centered methodology, the student is placed at the center of all training services and guides the institution towards academic and professional success. The student will be able to know his progress at all times, be attended when he needs to, access to all resources with total freedom and have a coaching service, headhunting and job placement.
All students who successfully complete this program will obtain a double Master's degree from the University Camilo José Cela and Master by MFI Business School. They will have at their disposal all the advantages of MFI:
The M.A. program in Linguistics offers either a Thesis (research) track or a non-thesis (general) track. Both tracks have three objectives: (1) to expose students to current research topics in the field (2) to engage students in scientific discourse, research methodologies, and critical reasoning; (3) to train students in academic writing and the use of professional literature. The goal of the thesis track, in addition, is for students to conduct original research that contributes to the field.
Both tracks are two-year programs.
Students can choose from among the various courses offered. However, all students in this track must take the Methodology course in their first year. In addition, the courses chosen must include at least one course in syntax and at least one course in semantics. All M.A. courses are run as seminars and require a final paper.
Overall, students in the thesis track take 24 points (6 courses of 4 points each), comprising 50% of the final grade. They also write a research thesis (12 points), comprising 50% of the final grade. Students are also required to attend the departmental seminar throughout their two years of study.
All research students are encouraged to choose an advisor and begin working on their thesis proposal (3 pages plus bibliography) before the end of their first year.
Excellent students can choose a special track in Computational Linguistics, with the approval of the Computational Linguistics advisor, Prof. Ariel Cohen. This track includes the following three courses from Computer Science: Introduction to Computer Science, Data Structure, and a course in Natural Language Processing, with no need for additional prerequisites. The courses in Data Structure and NLP count as 8 points toward the MA degree.
Students can choose from among the various courses offered. Students in this track take 36 points (9 courses of 4 points each), comprising 80% of the final grade, plus a final take-home exam (comprising 20% of the final grade). The exam integrates materials from the courses which the students have studied in the M.A. program.
The department also offers a combined track of literature and linguistics. In this track, the students take 36 points (9 courses of 4 points each) in which both linguistics and literature courses are represented (a minimum of 8 points for each field, a maximum of 24 points). Up to 8 points are designated courses for this track. This track combines advanced courses in Literature and Linguistics and is particularly suitable for English teachers whose BA studies covered both areas and who are interested in both fields. Students write a final take-home
the exam is by the end of their second year in the program.