Masters Degrees (Natural Language Processing)

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

This course is run by a leading research group at the University of Wolverhampton. As a Master's student, you will be part of our Research Institute of Information and Language Processing (RIILP) (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/), an independent, research-driven University unit specialising in Linguistics and Natural Language Processing.

What will I learn?

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 (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/) to become part of this team of leading researchers and academics and create your path to a career in computers and language!

What modules will I study?

When studied full-time, this course comprises of three semesters worth 60 credits each. Three modules will be studied in semesters one and 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
2. Corpus Linguistics in R
3. Machine translation and other natural language processing applications
4. Computational Linguistics
5. Translation tools for professional translators
6. Machine learning for language processing
7. Research methods and professional skills

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.

Opportunities

- You will be taught by leading researchers in the field: our teaching staff at the Research Institute of Information and Language Processing (RIILP) (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/) 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;
- 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/.

How will I be assessed?

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.

What skills will I 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 transferable 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.

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.

Student comments

"This course allowed me to see all the potential of Natural Language Processing - my favourite topic was Corpus Linguistics."

"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."

"I would recommend this course to the individuals who seek to increase their knowledge of Machine Learning and Natural Language Processing. People who want to understand how, say, SIRI works, should join 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 have several opportunities for a PhD in the US. I also learnt how to use a few programming languages, which is of great importance nowadays if one wants to find a job."

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Research profile

Data science is the study of the computational principles and systems for extracting knowledge from data, for maintaining data, and for ensuring its quality. Large data sets are now generated by almost every activity in science, society and commerce.

This EPSRC-sponsored programme tackles the question: how can we efficiently find patterns in these vast streams of data?

Many research areas in informatics are converging on the problem of data science. Those represented in the School include machine learning, databases, data management, optimization and cluster computing; and also the unstructured data issues generated in areas such as natural language processing and computer vision.

Our programme will allow you to specialise and perform advanced research in one of these areas, while gaining breadth and practical experience throughout data science.

A short sample of our research interests includes:

• machine learning applied to problems in biology, astronomy, computer science, engineering, health care, and e-commerce
• database theory and technology for managing unstructured data and for maintaining trust in data
• big data and management of streaming data
• management of unstructured data, including natural language processing, speech processing, and computer vision

Many more topics can be found by exploring the Centre’s web pages, particularly the personal web pages of the Centre supervisors:

• EPSRC Centre for Doctoral Training in Data Science

You will be supervised by one of our 45 world-renowned faculty. You will also benefit from interacting with a group of 35 leading industrial partners, including Amazon, Apple, Google, IBM, and Microsoft.

This will ensure your research is informed by real world case studies and will provide a source of diverse internship opportunities. Moreover we believe that key research insights can be gained by working across the boundaries of conventional groupings.

Training and support

The MScR is the first part of a longer 1+3 (MSc by Research + PhD) programme offered by the School through the EPSRC.

Our four-year PhD programme combines masters level coursework and project work with independent PhD-level research.

In the first year, you will undertake six masters level courses, spread throughout machine learning, databases, statistics, optimization, natural language processing, and related areas. You will also undertake a significant introductory research project. (Students with previous masters-level work in these areas may request to take three courses and a larger project, instead of six courses.)

At the end of the first year, successful students will be awarded an MSc by Research. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors.

You will have opportunities for three to six month internships with leading companies in your area, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies.

Throughout your studies, you will participate in our regular programmes of seminars, short talks and brainstorming sessions, and benefit from our pastoral mentoring schemes.

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.

• Athena SWAN

Facilities

Our research groups contain a diverse range of compute clusters for compute and data-intensive work, including a large cluster hosted by the Edinburgh Compute and Data Facility.

More broadly, 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

We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way in data science. This vision is shared by our industrial supporters, whose support for our internship programme indicates their strong desire to find highly qualified new employees.

You will be part of a new generation of data scientists, with the technical skills and interdisciplinary awareness to become R&D leaders in this emerging area.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.

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Programme description

Cognitive Science is a discipline in growing demand, and Edinburgh is a widely recognised leader in this area, with particular strengths in natural language, speech technology, robotics and learning, neural computation and philosophy of the mind.

You will gain a thorough grounding in neural computation, formal logic, computational and theoretical linguistics, cognitive psychology and natural language processing, and through a vast range of optional courses you will develop your own interests in this fascinating field.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a ‘specialist area’ within the programme, which will determine the choice of your optional courses. The specialist areas are:

• Cognitive Science
• Natural Language Processing
• Neural Computation and Neuroinformatics

Compulsory courses:

• Informatics Research Review
• Informatics Research Proposal
• Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
• Dissertation

There are several optional courses to choose from, such as:

• Accelerated Natural Language Processing
• Automated Reasoning
• Computational Cognitive Neuroscience
• Human-Computer Interaction
• Machine Learning and Pattern Recognition
• Natural Language Understanding
• Neural Computation
• Text Technologies for Data Science
• Bioinformatics
• Topics in Cognitive Modelling

Career opportunities

This programme will give you a deep understanding of the expanding domain of cognitive science through formal study and experiments. It is perfect preparation for a rewarding academic or professional career. The quality and reputation of the University, the School of Informatics and this programme will enhance your standing with many types of employer.

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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:

• Advanced Natural Language Processing
• Computer Programming for Speech and Language Processing
• Introduction to Phonology and Phonetics
• Speech Processing

Option courses may include:

• Advanced Topics in Phonetics: Speech Production and Perception
• Automatic Speech Recognition
• Introduction to Statistics and Experimental Design
• Machine Learning and Pattern Recognition
• Machine Translation
• Natural Language Generation
• Natural Language Understanding
• Prosody
• Simulating Language
• Speech Synthesis
• Univariate Statistics and Methodology using R

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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The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and makes them well equipped to proceed to become the ideal choice for the best employers in internet-related industries and the areas requiring big data analytical skills.

Degree information

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 five core modules (75 credits), three option modules (45 credits) and the research dissertation (60 credits).

Core modules
-Information Retrieval and Data Mining
-Statistical Natural Language Processing
-Complex Networks and Web
-Web Economics

Optional modules - students can choose three of the following:
-Cloud Computing
-Computer Graphics
-Entrepreneurship: Theory and Practice
-Interaction Design
-Applied Machine Learning
-Machine Vision
-Supervised Learning
-Understanding Usability and Use
-Distributed Systems and Security

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 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.

Employability
The skill set obtained from our MSc makes our students the ideal choice for the best employers in internet-related industries and sectors requiring big data analytics. 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, and was one of the top-rated departments in the country according to the UK government's recent Research Excellence Framework.

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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About the Course

1. Big Challenges being addressed by this programme – motivation

• Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills.
• Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future.
• The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone.
• CNN has listed jobs in this area in their Top 10 best new jobs in America.

2. Programme objectives & purpose

This is an advanced programme that provides Computing graduates with advanced knowledge and skills in the emerging growth area of Data Analytics. It includes advanced topics such as Large-Scale Data Analytics, Information Retrieval, Advanced Topics in Machine Learning and Data Mining, Natural Language Processing, Data Visualisation and Web-Mining. It also includes foundational modules in topics such as Statistics, Regression Analysis and Programming for Data Analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner.

Graduates will be excellently qualified to pursue careers in national and multinational industries in a wide range of areas. Our graduates currently work for companies as diverse as IBM, SAP, Cisco, Avaya, Google, Fujitsu and Merck Pharmaceuticals as well as many specialised companies and startups. Opportunities will be found in:
• Multinational companies, in Ireland and elsewhere, that provide services and solutions for analytics and big data or whose business depend on analytics and big data technologies;
• Innovative small to medium-sized companies and leading-edge start-ups who provide analytics solutions, services and products or use data analytics to develop competitive advantage
• Companies looking to extend their research and development units with highly trained data analytic specialists
• PhD-level research in NUI Galway, elsewhere in Ireland, or abroad

3. What’s special about CoEI/NUIG in this area:

• The MSc in Computer Science (Data Analytics) is being delivered by the Discipline of Information Technology in collaboration with the Insight Centre for Data Analytics (http://insight-centre.org) and with input from the School of Mathematics, Statistics and Applied Mathematics in NUI Galway
• The Discipline of Information Technology at NUI Galway has 25-year track record of education, academic research, and industry collaboration in the field of Computer Science
• The Insight centre at NUI Galway is Europe’s largest research centre for Data Analytics

4. Programme Structure – ECTS weights and split over semester; core/elective, etc.:

• 90ECTS programme
• one full year in duration, beginning September and finishing August
• comprises:
- Foundational taught modules (20 ECTS)
- Advanced taught modules (40 ECTS)
- Research/Industry Project (30 ECTS).

5. Programme Content – module names

Sample Foundational Modules:

• Tools and Techniques for Large Scale Data Analytics
• Programming for Data Analytics
• Machine Learning and Data Mining
• Modern Information Management
• Probability and Statistics
• Discrete Mathematics
• Applied Regression Models
• Digital Signal Processing

Sample Advanced Modules:

• Advanced Topics in Machine Learning and Information Retrieval
• Web Mining and Analytics
• Systems Modelling and Simulation
• Natural Language Processing
• Data Visualisation
• Linked Data Analytics
• Case Studies in Data Analytics
• Embedded Signal Analysis and Processing

6. Testimonials

Ms. Gofran Shukair, MSc, Research Engineer at ZenDesk, Ireland

After graduating with an MSc at NUI Galway, Gofran worked with Fujitsu’s Irish Research Lab as a research engineer before moving to a software engineering position at Zendesk, Ireland.

“The mix of technical and soft skills I gained through my Masters studies at NUI Galway is invaluable. I had the chance to work with great people and to apply my work on real world problems. With the data management and analysis skills I gained, I am currently pursuing my research in an international research project with one of the leading IT companies. I will be always thankful for studying at NUI Galway, a great historic place based in a culturally-rich vibrant city with an international mix of young and ambitious students that made me eager to learn and contribute back the moment I graduated.”

For further details

visit http://www.nuigalway.ie/courses/taught-postgraduate-courses/msc-in-computer-science-data-analytics.html

How to Apply:

Applications are made online via the Postgraduate Applications Centre (PAC) https://www.pac.ie
Please use the following PAC application code for your programme:

M.Sc. Computer Science – Data Analytics - PAC code GYE06

Scholarships :

Please visit our website for more information on scholarships: http://www.nuigalway.ie/engineering-informatics/internationalpostgraduatestudents/feesandscholarships/

Visit the M.Sc. Computer Science – Data Analytics page on the National University of Ireland, Galway web site for more details!

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Course description

This Master's 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.

For further information, please download our flyer here: http://rgcl.wlv.ac.uk/wp-content/uploads/2017/01/MA-Practical-Corpus-Linguistics-for-ELT-Lexicography-and-Translation.pdf

Why choose 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 – 98% of our postgraduate students are in work or further training six months after graduation!

What will I learn?

This course will introduce you to the use of corpora – large electronic collections of written and/or spoken text that serve as a reliable source of evidence in linguistic analysis. (‘Corpora’ is the plural of ‘corpus’.) You will learn how to design, analyse, and exploit corpora in language teaching, dictionary writing, and translation for English or any other language.

You will be given freedom and flexibility to tailor the course content to your needs and research interests as we offer a unique selection of general and specialized elective modules from which to choose. Our teaching staff will provide you with support and guidance in selecting the most suitable combination for your research topic.

Semester I will focus on developing general linguistic knowledge and research skills, which you will be able to apply to your chosen area of expertise in Semester II. You will learn about words, meanings, and linguistic creativity, broaden your knowledge of grammar, and acquire basic research and professional skills. You will also have an opportunity to learn the essentials of computer programming by attending our elective module in Python.

Semester II will introduce you to corpus linguistic methods and their application to three areas of research: language teaching, lexicography, and translation. You will start planning your dissertation and engage in one-on-one consultations with your supervisor.
For further information on modules and assessments, please visit our website: http://rgcl.wlv.ac.uk/macorling

Opportunities

As a Master's 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.
• You will be taught by leading researchers in the field: http://rgcl.wlv.ac.uk/macorling/who-will-teach-you-on-this-course/; our teaching staff at 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 which you will be able to benefit from;
• You will also have an opportunity to travel the world – Malaga, Valencia, Besançon, Naples, Alicante, and Plovdiv are just a few of the many possible destinations covered by our institute’s Erasmus agreements.

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.

Contact us

• Dr Sara Moze (course leader): [email protected]
• April Harper (admin office): [email protected]
• Research Group website: http://rgcl.wlv.ac.uk/
• Twitter: @RGCL_WLV


*Subject to approval

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USF’s one-year Master of Science in Analytics (MSAN) program delivers a rigorous curriculum focused on mathematical and computational techniques in the emerging field of data science. The curriculum emphasizes the careful formulation of business problems, selecting effective analytical techniques to address those problems and communicating solutions in a clear and creative fashion.

98% of MSAN students are employed within three months of graduation at companies such as Google, Williams-Sonoma, Amazon, Capital One Labs, Eventbrite, and Mozilla.

A Technically Challenging Curriculum

The program's challenging curriculum features seven-week courses designed specifically for MSAN students — they're not offered in other programs or departments. Students master subjects from computer science, statistics, and management such as regression, web scraping, SQL and NoSQL database management, natural language processing, business communications, machine learning, cluster analysis, application development, and interviewing skills. Students primarily use programming languages like R and Python in their classes and learn how to effectively use distributed computing technology such as MapReduce, Hadoop, and Spark, and become intimately familiar with cloud technology such as Amazon Web Services.

Practicum Program

Practicum projects allow students to work an average of 15 hours per week for nine months tackling data science and analytics problems at companies around the San Francisco Bay Area and beyond. Past and current partners include Uber, Airbnb, Eventbrite, Google, Capital One Labs, AT&T Big Data, Zephyr Health, and the Houston Astros. Groups of two to four students - supervised by MSAN faculty - work on a data-driven business problem and produce a defined set of deliverables.

Faculty

Our faculty represent the fundamental multidisciplinary nature of the big data industry. They’re traditional academics and data scientists actively working in the field, using real industry experience to inspire their instruction. Their areas of expertise include deep learning, natural language processing, databases, statistical modeling, network analytics, algorithms, unsupervised learning, machine learning, optimization, health analytics and signal processing.

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Learning how to build the intelligence used to power the future of the Web.
The Web has provided us with novel ways to maintain our social networks, rapidly search for information, and make purchases from the comfort of our own home. Most of us take these technologies for granted. However, for the Web to function as it does numerous problems had to be solved: which pages should surface given your search query? Which status updates will you enjoy most? Or, how do we make sure you find the products that you where looking for?
These questions are solved using a combination of machine learning, and an understanding of users. As our use of the Web steadily grows, new questions are continuously emerging. Smarter and faster solutions to empower an intelligent Web are needed. In the Master’s specialisation in Web and Language Interaction you’ll learn the building blocks you’ll need to answer resolve future problems that arise on the Web. In this you’ll learn to understand the psychological, technical and statistical aspect of data science and other Web issues.
The key course in this specialisation is the new AI at the Webscale course, in which AI techniques are studied in the context of streaming and massive data. This course is complemented by the App-Lab course, aimed at understanding how Apps are set-up, built and evaluated. Covering human cognition, a choice of courses in psycho-linguistics is offered in line with the broad expertise within the Donders Institute.

See the website http://www.ru.nl/masters/ai/web

Why study Web and Language Interaction at Radboud University?

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Data Science. This will take three instead of two years.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to debate and develop their projects. Every student also receives personal guidance and supervision from a member of our expert staff.

Our approach to this field

Language Information and Communication Technology lies at the basis of innumerable innovations in our society and has provided remarkable new services (like social media) and new products (like smart phones and tablets). Traditionally, applications of Artificial Intelligence used to be limited to micro worlds and toy systems. The horizon has now been widely extended to distribute mass applications of AI techniques. These developments are supported by a general availability of computation power and connectivity in the form of the web, social media, big data, wireless, and mobile platforms with input and output in many modalities.

Human-human and human-computer communication can be found in natural language applications like in the speech driven free-text systems such as Watson, and Siri, in brand sentiment detection and epidemic monitoring from tweets. But communication is also crucial for web applications and Apps that personalise information and make it accessible with other means. Examples thereof are voter guides, recommendation systems, click stream analysis, crowd sourcing and demand aggregation, e-therapy, e-inclusion, avatars with speech synthesis and recognition, gesture and emotion. Technical issues are e.g. map/ reduce architecture for massive data processing and emerging technologies like the semantic web.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Booking.com, Webpower, Google, Facebook, Philips, Booking.com, Philips, Rabobank. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Web and Language Interaction could get:
- PhD researcher, for example, on enhancing speech recognition using semantic knowledge or in user interaction design for patient doctor communication in a virtual hospital
- Data Scientist in a web start-up
- Developer for Computer Aided Language Learning
- EU R&D programme leader on machine translation of natural language
- Developer of intelligent software for music studios

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/web

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Content

The increasing demand for raw materials, their price volatility, the production concentration and the market distortions imposed by some countries, confront Europe and other world regions with a number of challenges along the entire value chain. To tackle this supply risk challenge and to deal with environmental problems arising from too large emissions of waste (such as CO2), technological innovation is required with respect to exploration of new resources and sustainable primary mining, sustainable use of resources in specific products and production processes (e.g. substitution of critical metals in materials), prevention of waste generation, valorisation of secondary (alternative) resources and recovery/recycling of resources from end-of-life products.

The International Master of Science in Sustainable and Innovative Natural Resource Management (SINReM) aims at educating a new range of professionals with a holistic overview on resource management and up-to-date processing technologies, who are familiar with sustainability concepts and possess an innovative mind-set to boost the economic importance of this sector.

Students will be acquainted with the different (technological) options for optimizing flows of natural resources in the different parts of the chain, ranging from resource exploration over sustainable materials use and use of resources in production processes to recovery/recycling of resources from end-of-life products. The focus is on developing ground-breaking technologies, engineering and re-inventing the value chain to make it more sustainable. Students will get a broad view on the entire value chain in its different aspects.

Networking and exchange of knowledge and experience between different nationalities, between academic and non-academic partners and between scholars and students will be promoted.

SINReM is offered by a consortium consisting of 3 Institutes of Higher Education:

Universiteit Gent / Ghent University (UGent, Gent, Belgium);
Uppsala University (UU, Uppsala, Sweden);
TU Bergakademie Freiberg (TUFreiberg, Freiberg, Germany).

The SINReM programme is (co)financed by the European Institute of Innovation and Technology within the EIT Raw Materials programme and aims at achieving an EIT label. EIT-labelled educational programmes foster students to become more creative, innovative and entrepreneurs.

Career Perspectives

Graduates are qualified for a professional career in the private (supporting companies in making processes, products and services more sustainable), research (applied research at universities, research institutes or companies) or public sector (consulting in local, regional and (inter)national administrations, defining and implementing sustainable development policies).
Graduates have an entrepreneurial mindset, a multidisciplinary view and creative innovative problem-based technology development skills

Structure

This 2-year programme contains 120 ECTS credit units and leads to the joint diploma of International Master of Science in Sustainable and Innovative Natural Resource Management.

In order to expose all students to different institutional settings, student mobility within Europe is an integral part of the programme.

General Entrance Module - Semester I 30 ECTS - Ghent University
Advanced Module - Semester II 30 ECTS - Uppsala University
Field trip - Summer School - University of Freiburg
Advanced Module II - Semester III 60 ECTS - choose a one of the following majors containing (elective) courses in combination with master dissertation research:
geo-resource exploration (Uppsala)
sustainable processes (Freiberg)
sustainable materials and resource recovery (Ghent)

All students will be moving as a cohort to Gent, Freiberg and Uppsala in the first year, which approach has significant networking and social cohesion advantages.

During this first year, students are introduced to the value chain, management of natural resources, the circular economy, its economic, policy and legal aspects, inventory techniques, the clean technology concept and life cycle assessment tools to assess sustainability of products, services and processes. Moreover, students are exposed to a basic training in the different technological tools that can be used to intervene in different parts of the value chain (geo-resource exploration, sustainable (chemical) extraction processes, sustainable materials and resource recovery technology).

In the second year students have the option to further specialize by selecting a major and conducting thesis research. They interact with the professional sector through cooperation in thesis research, internships, lectures and seminars.

Admission Requirements

To be admitted, candidates must have at least a bachelor degree (minimum 180 ECTS credits) in engineering or science (physics, chemistry, biology, mathematics, earth science, materials science) including 15 ECTS in mathematics and/or physics and 10 ECTS pure or applied chemistry or an equivalent level from a recognised university or Engineering College.

In terms of language requirements the following is currently applied in or acceptable by the partner institutes. Changes to these requirements are however admissible (upon approval by the MB).

Nationals of Australia, Botswana, Canada, Eritrea, Gambia, Ghana, Guyana, India, Ireland, Kenya, Liberia, Malawi, Namibia, New Zealand, Nigeria, Philippines, Sierra Leone, South Africa, Sri Lanka, Trinidad and Tobago, Uganda, UK, USA, Zambia, and Zimbabwe, need to send proof of at least one year - 60 ECTS (finished successfully) - of comprehensive English-based instruction at a HEI do not need to present a language certificate but a mode of instruction.

Candidates from any other nationality need to present test results of one of the following tests (validity of 5 years; TOEFL/IELTS predictive tests and TOEIC will not be accepted):

TOEFL IBT 86
TOEFL PBT 570
ACADEMIC IELTS 6,5 overall score with a min. of 6 for writing

Candidates apply online through a standard online application form. All candidates fulfilling the above-mentioned minimum admission requirements receive and an official letter of admission signed by the legal representative of Ghent University (the Rector), in name of the consortium. Any applicant will need to be granted academic admission by Ghent University, advised by the SINReM Management Board, before starting the program. To this aim, candidates have to prove through their application file that they meet the admission requirements.

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Students who graduate from the Master’s programme in geography have strong theoretical and practical skills. The education in geography offers a broad understanding in current social and environmental issues. Our students can work as experts in their field, both independently and as members of multi-professional teams.

The teaching within the programme is connected with the work of the geography research groups. It is often possible to write the final thesis as part of work in a research group or a research institute in a related field.

The Master’s programme in geography is divided into three sub-programmes (described in section 4). Our students have been very successful in the job market after completing our programme.

The strengths of students who have completed our Master’s programme when it comes to research and expertise are:
-Their ability to apply theoretical knowledge.
-A broad understanding of multi-layered regional issues.
-Strong interaction skills within multi-disciplinary groups of specialists.
-Their ability to communicate in writing, orally, and graphically about geographical phenomena and research findings.
-Their ability to utilise and interpret various kinds of research data.
-Their versatile knowledge of methodology in geography.
-Their ability to apply the newest methods in geoinformatics and cartography.
-Their embracing of responsible and ethical scientifc practices.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The first year of the advanced module of the Master’s programme contains the method courses of your chosen sub-programme, elective courses, and advanced literature. During this year you will start planning your Master’s thesis.

In the autumn of the second year, you will join a Master’s seminar and take exams on literature related to the MSc thesis. In the spring, you should be ready to present your finished MSc thesis (Pro gradu). In addition, you can take optional courses in both years that support your sub-programme. If you are studying to be a teacher, you will take courses in pedagogy during your second year.

Studying takes many forms. A large part of the instruction is contact teaching. Method and specialisation courses are usually implemented in groups of 10-20 students, where it is easy to discuss professional issues and gain deeper insights. Independent study is supported through workshops supervised by older students, and reading circles. The Master’s programme also includes extensive exams on literature in the field.

Selection of the Major

The Master’s programme in geography is divided into sub-programmes. The sub-programmes offer students the opportunity to specialise in different areas of geography. The Master’s programme contains both general and sub-programme-specific courses. The teaching within the Master’s programme in geography is seamlessly connected with the Master’s programme in urban studies and planning, which is jointly implemented with Aalto University.

The sub-programmes in the Master’s programme for geography are:
-Physical Geography
-Human Geography and Spatial Planning
-Geoinformatics

Physical Geography
Physical geography is an area of geography that studies natural systems and the regional interaction between nature and humans. The main parts of physical geography are geomorphology, climatology, hydrogeography, biogeography, and research into global change.

The Master’s courses in physical geography work towards deeper regional syntheses, explain the physical surroundings and their changes as a part of the function of regional systems, and analyse and model the relationships between different sectors. Focus areas in the Master’s programme in physical geography are the effect of global change on natural systems, watershed research, and the regional modelling of geomorphological processes and local climates. A considerable part of the Master’s programme in physical geography consists of work in small groups or in the field, where you will learn to implement theories in practice.

Having completed the Master’s programme in physical geography, you will be able to analyse and model regional systems of nature, as well as the interaction between nature and humans. In addition, the programme teaches you to analyse sustainable use of natural resources, and evaluate environmental impact. You will learn to implement theoretical knowledge and regional methods in planning a scientific thesis, implementing it in practice, and presenting your results orally and in writing. Further, the courses will train you to take specimens independently, analyse them, and interpret them. The teaching at the Master’s stage is closely connected with research on physical geography: theses are done in collaboration with a research group or research institute.

Human Geography and Spatial Planning
Human geography and spatial planning is a sub-programme, where regional structures and related planning is studied. Urban structures, regional social structures, statewide regional structures, the regional development in the European Union, and globalisation are studied. At the core of the sub-programme is the spatial transformation of society. The Master’s programme studies such phenomena as the divergence of regional and urban structures, urban culture, as well as the political-geographical dynamics of regions. In addition, sustainability, multiculturalism, segregation, housing, and migration are at the core of the sub-programme. Relevant themes for the sub-programme are also regional and urban planning, the political ecology of use of natural resources and land, and gobal development issues. These geographical phenomena and themes are studied through both theoretical and empirical questions, which can be analysed with different qualitative and quantitative methods.

The programme goes into how theories on cities and regional systems can be transformed into empirical research questions. After completing their Master’s theses, students can independently gather empirical data on the main dimensions of regional and urban structures and regional development, they can analyse these data with both qualitative and quantitative methods, and they can evaluate the planning practices connected with regional and social structures. After graduating from the Master’s programme, students will be able to communicate about phenomena and research findings in regional and urban structures, both orally and in writing.

Geoinformatics
Geoinformatics is an effective approach to the study and understanding of complex regional issues. Geoinformatics studies and develops computational methods for gaining, processing, analysing, and presenting positioning data. As a part of geography, geoinformatics is a research method on the one hand, to be used in the study of complex regional issues from urban environments to natural ones, from studying local environments to issues of sustainability in developing countries. On the other hand, the methods are the object of research. In urban environments, the methods of geoinformatics can be used to study accessibility and mobility, for example, or to plan a good park network. In the context of developing countries, the research into climate change, land use, or interaction between humans and environment with the help of quantitative, qualitative, and involving methods rises into the front. Students in geography reach a basic understanding of geoinformatics methods in the study of geographical issues, the sources and use of different sets of data (remote sensing, global and national databases, geographical Big Data), analysis methods, and effective visualisation of results.

At the Master’s level, as a student specialising in geoinformatics you will advance your skills both theoretically and technically, developing your methodological expertise from data acquisition to data refinement and visualisation with the help of geoinformatics methods. The instruction is directly connected with the work of research groups and theses are often written as a part of research work. After graduating, you will be able to utilise versatile approaches in geoinformatics in research into geographical questions. You will be able to follow the rapid development of the subject independently, and participate on your own.

Programme Structure

The Master’s programme in geography comprises 120 credits (ECTS) and you should graduate as a Master of Science in two academic years. The following courses are included in the degree:
-60 credits of shared advanced courses or according to sub-programme (including MSc thesis 30 credits).
-60 credits of other courses from your own or other programmes.
-60 credits of courses in pedagogy for teaching students.
-The other studies may include working-life or periods of international work or study.
-Working-life orientation and career planning.
-Personal study plan.

Career Prospects

The Master’s programme in geography provides you with excellent abilities to work in research or as specialists. Our graduates have found good employment in the public and private sectors, in Finland and abroad. Their postings include:
-Evaluation of environmental effects and environment consultation.
-Positioning and remote-sensing work.
-Regional and urban planning.
-Governmental community and regional administration.
-Governmental posts in ministries.
-Organisational posts.
-Development cooperation projects.
-Communication and publishing work.
-Teaching.

Internationalization

The Master’s programme in geography offers many opportunities for international work:
-Student exchange in one of the exchange locations of the faculty or university.
-Traineeship abroad.
-Participation in international projects and expeditions (e.g. to the Taita research station in Kenya).
-Participation in international research groups (writing your thesis).
-Participation in language courses at the University of Helsinki (a wide range of languages, including rare ones).

Research Focus

In physical geography:
-Research into global change, especially the environmental effects of climate change.
-Watershed research, the physical-chemical quality and ecological status of water systems.
-Natural systems, their function and change.
-Regional analytics and modelling in research into natural systems.
-Positioning and remote-sensing methods and their application when studying the status and changes in natural environments.
-‘Big data,’ analysis of regional and temporal data.
-The Arctic areas: status, change and vulnerability.

In human geography and spatial planning:
-Transformation and segregation in the social and physical urban environment.
-The changing rationalities and concepts of regional and urban planning.
-Regional policy and geopolitics.
-Urbanisation and changing relationships between state and cities.
-Internationalisation of cities and states.
-The spatial planning system of the European Union.
-Regional policy of data-intensive economics.
-The political ecology and management of natural resources and land use.
-Globalisation.

In geoinformatics:
-Spatial data analysis, new information sources.
-Development of remote-sensing methods for environmental study, especially hyper-spectral remote-sensing data and drone applications.
-Application of geoinformatics methods to environmental and urban research.

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Overview

The aim of this advanced course is to provide a natural follow-up to typical undergraduate courses in electrical and electronic engineering, concentrating on the commercially important and rapidly expanding area of embedded digital systems for communication and control. It offers a range of options of immediate relevance to industry at large, and is excellent preparation for those wishing to engage in research. The topics covered include embedded system design, software engineering, data communications, signal and image processing and embedded control systems. The course concludes with a major project and dissertation. See website http://www.postgraduate.hw.ac.uk/prog/msc-embedded-systems/

Programme content

CORE MODULES
- Embedded Systems
- Digital Design
- Research Methods Critical Analysis and Project Planning
- Embedded Systems Design Project
- Project Phase 1
- Embedded Software
- MSc Project

OPTIONAL MODULES
- Software Engineering 1
- Digital Signal Processing
- Software Engineering 2
- Image Processing
- Advanced Digital Electronics

English language requirements

If your first language is not English, or your first degree was not taught in English, we’ll need to see evidence of your English language ability. The minimum requirement for English language is IELTS 6.5 or equivalent. We offer a range of English language courses (See http://www.hw.ac.uk/study/english.htm ) to help you meet the English language requirement prior to starting your masters programme:
- 14 weeks English (for IELTS of 5.5 with no more than one skill at 4.5);
- 10 weeks English (for IELTS of 5.5 with minimum of 5.0 in all skills);
- 6 weeks English (for IELTS 5.5 with minimum of 5.5 in reading & writing and minimum of 5.0 in speaking & listening)

Find information on Fees and Scholarships here http://www.postgraduate.hw.ac.uk/prog/msc-embedded-systems/

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You will take eight Assessed Modules plus an Individual Project carried out in the department. Six of the modules cover core Software Engineering methods, practices and tools, and are compulsory. For the remaining two modules, you will be able to choose from Natural Language Processing, Topics in Privacy & Security, Evolutionary Computation, Concurrent & Real-Time Programming, and Functional Programming Technology.

Software Engineering has become a crucial discipline in the functioning of the modern world. Information systems, communications, transport, manufacturing and services all require well-engineered and reliable software. The focus of our MSc in Software Engineering is automated and large-scale software engineering, so the course will equip you to deal with the types of systems widely found in industry.

The MSc is a full-time, one-year course for those with some experience or background in Software Engineering. You will learn up-to-date theory and practice in the core areas of Software Engineering, and the main methods and tools used in industry. The course also covers model-driven engineering, service-oriented architectures, software architectures and user-centred design. You will gain a thorough understanding of techniques and practices of software management, including measurement and testing. This in-depth understanding of the role of software in commercial organisations will enable you to develop and maintain large-scale software systems.

You will gain a thorough understanding of techniques and practices of software management, including measurement and testing. These techniques will allow you to understand the role of software in commercial organisations and you will be able to develop and maintain these large scale systems.

Course Aims
When you graduate, you will be able to apply advanced Software Engineering techniques to analyse systems and design solutions, particularly in a commercial context. You will have experience of using state-of-the-art Software Engineering tool suites (e.g., Eclipse and Epsilon). You will also understand the human factors in Software Engineering, and will be able to design systems taking into account the needs of users.

Your individual project gives you the chance to specialise in a specific area of Software Engineering, as you will undertake independent research and apply your results to develop a real solution – an application, tool or technique.

On graduation, you will be equipped to design and maintain large systems in a wide range of industries, or to pursue an academic research career in Software Engineering.

Learning Outcomes
A thorough grounding and practical experience in the use of state-of-the-art techniques for developing software-based systems.
An in-depth understanding of the principles underpinning these techniques, so as to make sound judgements throughout the systems and software engineering life cycle.

Project

Team Project
You are taught a broad range of project management skills, which you will directly apply to a medium-sized software project that is conducted in small student teams.

Individual Project
The course concludes with your individual project. You may choose a topic among the many offered by the academic staff, or you may propose your own topic. Some recent topics were:
-Air Traffic Control application using PostgreSQL
-Automated Development of Graphical Editors built atop Graphiti
-Multi-Agent Reinforcement Learning: Conquest of Mars
-Natural Disaster Planning - A System of Systems Analysis
-Reinforcement Learning for Mobile Cognitive Radio Agents
-Simulation-based Hazard Analysis for Autonomous Robots
-Study of Business Processes in a Complex Enterprise System
-Using heuristics for Monte Carlo Tree Search

Careers

Here at York, we're really proud of the fact that more than 97% of our postgraduate students go on to employment or further study within six months of graduating from York. We think the reason for this is that our courses prepare our students for life in the workplace through our collaboration with industry to ensure that what we are teaching is useful for employers.

Our postgraduate taught courses are specifically designed to meet the needs of industry, and the thorough grounding we provide, alongside the skills you learn from undertaking a Masters degree, will stand you in good stead in the workplace.

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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. 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

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

Examples of optional modules

Object-Oriented Programming and Software Design; Modelling and Simulation of Natural Systems; Theory of Distributed Systems; 3D Computer Graphics; Computer Security and Forensics; Testing and Verification in Safety-critical Systems; Intelligent Web; Software and Hardware Verification; Software Development for Mobile Devices; Virtual Environments and Computer Games Technology; Java E-Commerce; Network Performance Analysis.

Teaching and assessment

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

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About the course

Accredited by the British Computer Society

Turn your fascination with how things work into a successful career in business or industry. We’ll give you an advanced education in the most up-to-date aspects of computer science and software engineering, informed by our wide-ranging research interests. Innovative project work will teach you how to apply your knowledge in the real world.

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

Object-Oriented Programming and Software Design; Research Methods and Professional Issues; Dissertation Project.

Examples of optional modules

Text Processing; Modelling and Simulation of Natural Systems; Speech Processing; Theory of Distributed Systems; 3D Computer Graphics; Computer Security and Forensics; Testing and Verification in Safety-critical Systems; Intelligent Web; Machine Learning and Adaptive Intelligence; Software and Hardware Verification; Software Development for Mobile Devices; Speech Technology; Virtual Environments and Computer Games Technology; Natural Language Processing; Java E-Commerce; Network Performance Analysis.

Teaching and assessment

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

Read less