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Masters Degrees (Natural Language Processing ()

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Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, text analytics, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing (NLP)) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, digital humanities, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

 

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

Students can expect to learn more about:

  • Language Technology
  • Natural Language Processing (NLP)
  • Computational Linguistics
  • Text Analytics
  • Digital Humanities

 

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

 

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

 

Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php

Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 



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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. Read more

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.

Career path

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.

What skills will you gain?

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.



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This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Read more

This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Drawing from our cutting-edge research, the programme’s content covers all areas of speech and language processing, from phonetics, speech synthesis and speech recognition to natural language generation and machine translation.

This flexible programme provides research or vocational training and can be either freestanding or lead to PhD study. The modular nature of the programme allows you to tailor it to your own interests.

Taught by leading researchers from Linguistics & English Language, the Centre for Speech Technology Research and the School of Informatics, this programme combines elements of linguistics, computer science, engineering and psychology.

You will develop up-to-date knowledge of a broad range of areas in speech and language processing and gain the technical expertise and hands-on skills required to carry out research and development in this challenging interdisciplinary area.

Programme structure

You study two semesters of taught courses, followed by a dissertation.

Most core compulsory courses have both computational and mathematical content. A few optional courses need a stronger mathematical background. Courses in the second semester can be tailored to your own interests and abilities.

Compulsory courses:

  • Accelerated Natural Language Processing
  • Computer Programming for Speech and Language Processing
  • Speech Processing
  • Univariate Statistics and Methodology Using R

Option courses may include:

  • Introduction to Phonology and Phonetics
  • Automatic Speech Recognition
  • Machine Learning and Pattern Recognition
  • Machine Translation
  • Natural Language Understanding
  • Simulating Language
  • Speech Synthesis

Learning outcomes

This programme aims to equip you with the technical knowledge and practical skills required to carry out research and development in the challenging interdisciplinary arena of speech and language technology.

You will learn about state-of-the-art techniques in speech synthesis, speech recognition, natural language processing, dialogue, language generation and machine translation.

You will also learn the theory behind such technologies and gain the practical experience of working with and developing real systems based on these technologies. This programme is ideal preparation for a PhD or working in industry.

Career opportunities

This programme will provide you with the specialised skills you need to perform research or develop technology in speech and language processing. It will also serve as a solid basis for doctoral study.



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Goal of the pro­gramme. Read more

Goal of the pro­gramme

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:

  • gain an in-depth understanding of the basic structure of language, its subsystems (phonology, morphology, syntax, semantics, pragmatics) and their mutual relationships
  • learn the fundamentals of linguistic analysis and language description
  • familiarize yourself with linguistic concepts, theories, descriptive models and the associated research methods
  • learn how language is related to cognition, speech and interaction as well as to social structures, culture and society
  • learn to use various methods and technical tools in order to manage and analyze language data.
  • gain a good understanding of linguistic variation and diversity: what is common to the world's languages and how they differ, how language changes through time, how languages influence one another, how individuals cope with multilingual situations and how communities speaking endangered languages can be supported.

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.

Pro­gramme con­tents

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. 



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Strongly interdisciplinary in nature, the Institute for Language, Cognition and Communication (ILCC) is dedicated to both basic and applied research in the computational study of language, communication, and cognition, in both humans and machines. Read more

Strongly interdisciplinary in nature, the Institute for Language, Cognition and Communication (ILCC) is dedicated to both basic and applied research in the computational study of language, communication, and cognition, in both humans and machines.

As technology focuses increasingly on language-based communication tools, research into the automation of language processing has become vital. ILCC offers you the broadest research scope in the UK, and a strong computational focus.

Our primary areas of research are:

  • natural language processing and computational linguistics
  • spoken language processing
  • dialogue and multimodal interaction
  • information extraction, retrieval, and presentation
  • computational theories of human cognition
  • educational and assistive technology
  • visualisation

Much of our research is applied to software development, in areas as diverse as social media, assisted living, gaming and education.

You may find yourself working closely with other departments of the University, particularly the School of Philosophy, Psychology & Language Sciences.

Many of our researchers are involved in cross-disciplinary research centres; for instance:

Centre for Speech Technology Research (CSTR)

The Centre for Speech Technology Research (CSTR) is an interdisciplinary research centre linking Informatics and Linguistics. Founded in 1984, it is now one of the world's largest concentrations of researchers working in the field of language and speech processing.

CSTR is concerned with research in all areas of speech technology including speech recognition, synthesis, signal processing, acoustic phonetics, information access, multi-modal interaction and dialogue systems.

The Centre is home to state-of-the-art research facilities including specialised speech and language-orientated computer labs, a digital recording studio, perception labs and a meeting room instrumented with multiple synchronised video cameras and microphones. There is also access to high-performance computer clusters, the University storage area network, a specialist library, and many speech and language databases

Centre for Design Informatics

Data driven innovation is transforming society and the economy. In the Centre for Design Informatics, we design systems for better human data interaction, in diverse settings such as health, culture, mobility and finance. We explore design from, with, and by data: the central concern is the design of flows of data which sustain and enhance human values. Relevant technologies range from the internet of things, through blockchains, to robotics, speech recognition, data visualisation, interaction design, and social computing.

Data Science EPSRC Centre for Doctoral Training

The EPSRC Centre for Doctoral Training (CDT) in Data Science, based at the University of Edinburgh, is training a new generation of data scientists, comprising 50 PhDs over five intake years, with the technical skills and interdisciplinary awareness necessary to become R&D leaders in this emerging area.

Training and support

You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.

A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.

It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.

Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.

Among our entrepreneurial initiatives is Informatics Ventures, set up to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

While many of our graduates pursue an academic career, others find their skills are highly sought after in the technology industry. A number of our students serve internships with large UK and international software developers, while others take up positions with major social media companies.



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About the course. Accredited by the British Computer Society. Speech and language technology graduates are in demand, in areas like machine translation, document indexing and retrieval, and speech recognition. Read more

About the course

Accredited by the British Computer Society

Speech and language technology graduates are in demand, in areas like machine translation, document indexing and retrieval, and speech recognition. Our world-leading language and speech research staff will help you to develop the skills you need.

Prepare for your career

Our courses give you experience of how real-world projects work. We consult with big employers to ensure that you develop the skills and the personal qualities they’re looking for.

You’ll learn about the issues that matter in global business and industry. Our graduates go into academic and industrial research, the software industry, banking and finance. They work for companies such as Logica, IBM, Hewlett Packard, PWC, Vodafone, the BBC and HSBC.

About us

Our challenge is to use computation to understand all kinds of systems: computer systems, living systems and cognitive systems. Our research areas include robotics, machine learning, speech and language processing, virtual reality, computational systems biology and software verification and testing. It’s work that makes a difference to people’s lives.

Network and hardware

We have our own high-performance network so you can access our advanced computing facilities. There are labs for teaching smaller groups, wi-fi coverage throughout the department, and you can connect your own laptop to the network. Mobile devices and tablets are available for you to borrow for project work.

We also use specialised equipment: an immersive virtual reality facility, robotics hardware and an acoustic booth for speech processing research.

Core modules

  • Text Processing
  • Speech Processing
  • Speech Technology
  • Machine Learning and Adaptive Intelligence
  • Natural Language Processing
  • Research Methods and Professional Issues
  • Dissertation Project

Examples of optional modules

  • Parallel Computing with Graphical Processing Units (GPUs)
  • Cloud Computing
  • Modelling and Simulation of Natural Systems
  • Software Development for Mobile Devices
  • The Intelligent Web

Teaching and assessment

We use lectures, tutorials and group work. Assessment is by formal examinations, coursework assignments and a dissertation.



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This Masters course will give you a completely new insight into how language really works and the way people use words to create meaning. Read more

This Masters course will give you a completely new insight into how language really works and the way people use words to create meaning.

If you would like to learn how to explore language using innovative techniques and computer tools, then our course will offer you cutting-edge, research-led training of the highest quality, taught by leading researchers in the fields of linguistics and computer science.

You will have options enabling you to study:

- How people use words to make meanings;

- How to analyse real language usage;

- The role of phraseology, metaphor, and idioms;

- Creative and poetic uses of language;

- New approaches to language teaching;

- Translation tools such as translation memory systems;

- Creating dictionaries using new kinds of evidence;

- Using computer tools for teaching and translation.

The course will enable you to develop interdisciplinary knowledge and practical, transferrable skills, enabling you to meet the most recent and relevant demands of the field.

If you are interested technological aspects of language study, you will also have an option to learn basic computer programming – a skill that is increasingly sought after by companies seeking to employ language professionals.

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 specializing in linguistics and natural language processing.

Join our team of international researchers and start exploring language now!

Why Wolverhampton?

MA Practical Corpus Linguistics for ELT, Lexicography and Translation is an innovative, unique, and up-to-date course based on high-quality interdisciplinary research, with a selection of modules that is unparalleled both on a national and international level. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. As a result, the knowledge and practical skills developed on the course will allow you to meet the most recent and relevant demands of the industry.

You will become proficient in the use of sophisticated corpus tools such as the Sketch Engine (https://www.sketchengine.co.uk), as well as state-of-the-art specialist software for professional translators and lexicographers. You will also be given an option to learn basic computer programming in Python, which is one of the most robust, popular, and widely used programming languages in the field. By the end of the course, you will have developed a unique set of transferrable skills that will make you highly competitive in the marketplace and allow you to find employment as a language professional in industry or in academia.

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 you to use for work or play;

- 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).

Career path

Graduates will be able to pursue a career path in language teaching, translation, lexicography, editing, and human language technology, working either as freelancers or in a variety of industry locations, including publishing houses, translation agencies and IT companies that specialize in the development of language resources and tools (e.g. language learning applications, CAT tools). English language teachers will benefit greatly from the course, as they will develop knowledge and practical skills in using modern lexical resources, corpus data and tools in the preparation of teaching material and in the classroom, which will significantly improve their chances of securing a job in the ELT sector.

The course will also provide a sound intellectual platform for students to progress onto doctorate level study and a career in higher education. As the teaching on the course is based on research carried out within the Research Institute of Information and Language Processing (RIILP), graduates will be well-placed to continue their academic careers by applying for PhD positions within our institute or at other leading centres specializing in Corpus Linguistics, ELT/TESOL, Lexicography, Translation Studies, or Natural Language Processing.



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Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php


Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 

Visit the European Masters Program Language & Communication Technologies page on the University of Malta website for more details!



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Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

 

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

 

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

 Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php

Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 

 

Visit the European Masters Program Language & Communication Technologies page on the University of Malta website for more details!



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Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

 

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

 

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

 

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

 Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php

Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 

 

Visit the European Masters Program Language & Communication Technologies page on the University of Malta website for more details!



Read less
Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

 

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

 

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

 

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

 

Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php

Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 

Visit the European Masters Program Language & Communication Technologies page on the University of Malta website for more details!


Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php



Read less
Program Brief. The LCT program is an international distributed Master program. Read more

Program Brief

The LCT program is an international distributed Master program. It is designed to meet the demands of industry and research in the rapidly growing field of Language Technology. Research and innovation in Language Technology is vital for many of the smart applications that are pervasive in modern daily life, such as virtual assistants, automatic translation services, search engines, voice-driven technology, social media analytics etc. Language Technology (also known as Computational Linguistics or Natural Language Processing) is an interdisciplinary field at the intersection of Linguistics, Computer Science and Mathematics (logic, probability theory, formal language theory, statistics). Hence, students in this program choose appropriate combinations of modules in Language Technology, Computational and Theoretical Linguistics, and Computer Science. Moreover, the students are able to acquire practice-oriented knowledge through our strong and continuous links with industry through internships, joint industry-academia supervisions, and the like.

Mobility

The program involves studying one year each at two different European partner universities. Optionally, a stay at one of the non-european partners for some months is possible, as well as an internship at any of our industrial partners. After completing all study requirements, the students obtain two Master degrees: one from each of the two European universities where they studied.

 

Study program

The course consists of compulsory core modules, as well as elective advanced modules in Language Technology and Computer Science, possibly complemented by an internship project, and completed by a Master Thesis.

 

History

The LCT Masters program has been successfully implemented since 2006, being funding by the Erasmus Mundus Programme from 2007 to 2011 and from 2013 to 2017. In 2012 the LCT Program operated as an Erasmus Mundus Brand Name. Intake 2018: the program commits to respecting the Erasmus Mundus requirements and to maintain the high quality of the implementation during the years of funding.

Key facts:

+ duration 2 years (120 ECTS credits)

+ in-depth theoretical and hands-on instruction in computational linguistics methods and technologies

+ study one year each at two different partner universities in Europe

+ double degree

+ possibility to visit one of two non-European partners for a part of the study

+ language of instruction and academic and administrative support is English

European partners:

1. Saarland University in Saarbruecken, Germany (coordinator)

2. University of Trento, Trento, Italy

3. University of Malta, Malta

4. University of Lorraine, Nancy, France

5. Charles University, Prague, Czech Republic

6. Rijksuniversiteit Groningen, The Netherlands

7. The University of the Basque Country / Euskal Herriko University, San Sebastian, Spain

 

Non-European partners:

8. Shanghai Jiao Tong University, China

9. The University of Melbourne, Australia

 

Frequently Asked Questions

You can find answers to our Frequently asked questions here: https://lct-master.org/contents_2014/faq.php

Careers

The LCT program offers education and training opportunities for the next generation of leaders in research and innovation in artificial intelligence as well as language and speech technologies. Examples of jobs held by the LCT alumni include: PhD student; university professor; company founder, data scientist, software engineer, IT consultant, senior analyst, researcher, senior linguist, information extraction engineer, project leader, computational linguist, assistant professor, post-doctoral researcher. 

Visit the European Masters Program Language & Communication Technologies page on the University of Malta website for more details!



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This MSc will prepare students for highly skilled, multidisciplinary managerial roles in the natural resources sector across the globe. Read more

This MSc will prepare students for highly skilled, multidisciplinary managerial roles in the natural resources sector across the globe. The programme is transcontinental (offered by UCL and the University of South Australia (UniSA)), is delivered by UCL Chemical Engineering, UCL Earth Sciences, UCL School of Management, and the Future Industries Institute at UniSA, and designed with significant input from industry.

About this degree

Students develop knowledge of geology, geosciences, geochemistry and the chemical processes used to transform raw materials into commmodities; managerial skills; and an understanding of the relationship between limited natural resources, economic forces, and the implications for society. The first two terms are spent at UCL in London and the third term and summer at UniSA in Adelaide.

Students undertake modules to the value of 180 credits.

The programme consists of eight core modules (120 credits) and a dissertation (60 credits).

Core modules

  • Business Sustainability
  • Decision and Risk Analysis
  • Earth Resources and Sustainability
  • Geology for Global Managers and Engineers
  • Minerals Usage, Extraction and Processing
  • Natural Gas Processing
  • Prevention and Remediation of Environmental Contamination
  • Social Licensing

Optional modules

There are no optional modules for this programme.

Dissertation/report

All students undertake a dissertation of 6,000 words based on an individual research project, field trip and executive summary. They must also complete an oral examination of 20 minutes maximum.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, site visits, independent reading and research as well as online material. Some of the modules taught in London will be co-taught by experts at UniSA via remote teaching methods. Assessment is by examination, coursework, process design, oral presentation, online quizzing, reports and writing executive summaries, with some components involving group work.

Further information on modules and degree structure is available on the department website: Global Management of Natural Resources MSc

Careers

The Global Management of Natural Resources MSc will prepare graduates for highly skilled, multidisciplinary managerial jobs in the natural resources sector. Recent university graduates who apply will gain a global perspective on the natural resources sector. Mid-career professionals already employed will expand their range of expertise. 

Our graduates will also be equipped for further postgraduate research in relevant disciplines.

Employability

Successful graduates will have wide knowledge of the energy and natural resources industries, have strong managerial and communication skills, be aware and respectful of social responsibilities, and operate within national and international constraints.

Why study this degree at UCL?

UCL is consistently placed in the global top 20 in a wide range of world rankings and in the latest Research Excellence Framework (REF 2014) UCL was the top-rated UK university for research strength. This MSc has developed from the European-funded research project ShaleXenvironmenT (in which UCL was an academic partner) and anticipates increasing demand for managerial professionals in existing and developing natural resources fields. UniSA is one of Australia’s leading universities for interdisciplinary research.

Our programme aims to produce global citizens and offers networking opportunities in London and Adelaide. We offer career advice throughout the programme and foster transferable skills through our multidisciplinary environment.

The programme includes a field trip to explore sedimentary formations similar to shale plays in either Spain or the UK. There is another field trip to a copper, gold or uranium mine in South Australia.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Chemical Engineering

90% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best internet-related industries and areas requiring big data analytical skills. Read more

The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best internet-related industries and areas requiring big data analytical skills.

About this degree

Students will gain a detailed knowledge and understanding of web-related technologies and big data analytics, ranging from information search and retrieval, natural language processing, data mining and knowledge acquisition, large-scale distributed data analytics and cloud computing to e-commerce and their business economic models and the latest concepts of social networks.

MSc students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), five optional modules (75 credits), and the research dissertation (60 credits).

Core modules

  • Complex Networks and Web (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Web Economics (15 credits)

Optional modules

Students must choose a minimum of 45 and a maximum of 75 credits of optional modules. Up to two electives (30 credits) may also be chosen instead of two of the optional modules.

  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Birkbeck College: Cloud Computing (15 credits)
  • Computer Graphics (15 credits)
  • Entrepreneurship: Theory and Practice (15 credits)
  • Graphical Models (15 credits)
  • Interaction Design (15 credits)
  • Machine Vision (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Supervised Learning (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent research project which culminates in a substantial dissertation.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and the dissertation.

Careers

Graduates from UCL are keenly sought after by the world's leading organisations, and many progress in their careers to secure senior and influential positions. Graduates of our Web Science and Big Data Analytics programmes are expected to develop careers in scientific research, the internet-based industry and other professional areas that require big data analytics skills.

Recent career destinations for this degree

  • CEO (Chief Executive Officer), Hoxton Analytics
  • Software Engineer, China Mobile
  • Computer Science Lecturer, Singapore Polytechnic
  • Software Developer, Barclays
  • Software Engineer, UCL

Employability

The MSc has a unique industry connection as almost all our lecturers have industry experience. Through long-term collaborations with big players in the field such as Google, Microsoft and BT, research is driven by the fundamental technical challenges faced by the industry. Throughout the degree, our students have the chance to interact with our industry collaborators and previous students, and have placement opportunities to address the specific technical problems faced by the industry.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research.

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.



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Data Science brings together computational and statistical skills and machine learning for data-driven problem solving. Read more

Data Science brings together computational and statistical skills and machine learning for data-driven problem solving. This rapidly expanding area includes deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.

About this degree

The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a range of industry partners.

Students undertake modules to the value of 180 credits.

The programme consists of three compulsory modules (45 credits), four optional modules (75 credits) and a dissertation/report (60 credits).

Core modules

  • Applied Machine Learning (15 credits)
  • Introduction to Machine Learning (15 credits)
  • Introduction to Statistical Data Science (15 credits)

Optional modules

Students must choose 30 credits from Group One options. For the remaining 45 credits, students may choose up to 30 credits from Group Two options or up to 45 credits from Electives.

Group One Options (30 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Birkbeck College: Cloud Computing (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Web Economics (15 credits)

Group Two Options (up to 30 credits)

  • Applied Bayesian Methods (15 credits)
  • Decision and Risk (15 credits)
  • Forecasting (15 credits)
  • Statistical Design of Investigations (15 credits)

Electives (up to 45 credits)

  • Affective Computing and Human-Robot Interaction (15 credits)
  • Bioinformatics (15 credits)
  • Computational Modelling for Biomedical Imaging (15 credits)
  • Graphical Models (15 credits)
  • Stochastic Systems (15 credits)
  • Supervised Learning (15 credits)

Please note: the availability and delivery of modules may vary, based on your selected options.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning

The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further information on modules and degree structure is available on the department website: Data Science and Machine Learning MSc

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. This is a very new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including:

  • Google Deepmind
  • Microsoft Research
  • Dunnhumby
  • Index Ventures
  • Cisco
  • Deutsche Bank
  • IBM
  • Morgan Stanley

Employability

Students gain a thorough understanding of the fundamentals required from the best practitioners, and the programme's broad base enables data scientists to adapt to rapidly evolving goals.

Why study this degree at UCL?

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.

The department also enjoys strong collaborative relationships across UCL; exposure to interdisciplinary research spanning UCL Computer Science and UCL Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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