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Masters Degrees (Natural Language)

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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. Read more
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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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 the philosophy of the mind. Read more

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 the 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 option 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 Project 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
  • Computational Cognitive Neuroscience
  • Human-Computer Interaction
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Neural Computation
  • Text Technologies for Data Science
  • Bioinformatics

Career opportunities

This programme will give you a deep understanding of the expanding domain of cognitive science through formal study and experiments. It is excellent 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. Recent graduates are now working as software engineers, analysts and language scientists for companies such as British Telecom and Intel.



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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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Data science is the study of the computational principles and systems for extracting knowledge from data, for maintaining data, and for ensuring its quality. Read more

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, artificial intelligence, 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:

You will be supervised by one of our 58 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.

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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Your programme of study. If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. Read more

Your programme of study

If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.

Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies. It is also said that artificial intelligence has the potential to change how we research and act to provide immediate solutions to energy, travel, and gridlock before it happens by setting up more alerts and warnings to us. We now already have the capabilities in smart technology to alert us on maps, apps, weather stations, lighting, sensors and other electronic and wired machine to machine devices to provide instant relevant information.

You are also advised to visit the organisation websites via the link below to find out about the innovations which may be influenced by AI:

Scottish Innovation Centres -

Courses listed for the programme

SEMESTER 1

Compulsory Courses

  • Foundations in AI
  • Machine Learning
  • Evaluation Systems of AI Systems
  • Engineering of AI Systems

SEMESTER 2

Compulsory Courses

  • Data Mining and Visualisation
  • Natural Language Generation
  • Software Agents and Multi-Agent Systems
  • Knowledge Representation and Reasoning

SEMESTER 3

You can broaden and deepen your skills with industry client opportunities where possible

Find out more detail by visiting the programme web page

Why study at Aberdeen?

  • AI or Artificial Intelligence is part of a major industrial revolution globally, linking to the Internet of Things
  • Aberdeen gives you a strong worldwide reputation for teaching in computing science, data science and natural language generation
  • You can be involved in cutting edge innovations which will shape our world in the future

Where you study

  • University of Aberdeen
  • 12 Months Full Time
  • September start

International Student Fees 2017/2018

Find out about fees:

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page and the latest postgraduate opportunities

Living in Aberdeen

Find out more about:

  • Your Accommodation
  • Campus Facilities
  • Aberdeen City
  • Student Support
  • Clubs and Societies

Find out more about living in Aberdeen and living costs 

You may also be interested in:

Information Technology MSc - Campus or Online



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- Intercalating medical students, or students intending to pursue a medical degree. - Students with a degree in the social sciences or humanities wishing to acquire a broad understanding of medical anthropology with reference to Asia or Africa, but also including other parts of the world. Read more

Who is this programme for?:

- Intercalating medical students, or students intending to pursue a medical degree.

- Students with a degree in the social sciences or humanities wishing to acquire a broad understanding of medical anthropology with reference to Asia or Africa, but also including other parts of the world

- People with professional experience in medical practice who have an interest in cross-cultural understandings of health and illness.

- Students with a degree in social anthropology wishing to pursue more specialist topics in the anthropology of medicine.

- Students without a previous degree in Anthropology looking for an MA conversion degree to serve as a qualification for pursuing a further research degree in anthropology

- The two-year intensive language pathway is directed at students who want to engage with a country in a professional as well as academic way, as the intensive language courses will enable them to reach a near proficient knowledge of the language.

As one might expect of study at SOAS, our programme is unique in that we take a cultural and phenomenological approach to the anthropology of medicine. That is, we stress a truly cross-cultural method, one which unites all medical systems in a unified comparative perspective. This allows students to grasp the underlying principles and questions common to all therapeutic systems. Given the diversity of the School’s courses, students may choose options which strengthen either the humanities or the development studies aspects of their interests.

It can also be taken with an intensive language pathway over two years, therefore making this programme unique in Europe.

The Japanese pathway is available for students who have an intermediate level of Japanese. Students will be required to take a placement exam in the week before classes begin in order to determine if their level is suitable. Please contact Professor Drew Gerstle () for further information.

The Korean pathway is designed for beginner learners of Korean. Students with prior knowledge of Korean are advised to contact the programme convenor, Dr Anders Karlsson (). Students will take four course units in the Korean language, one of them at a Korean university during the summer after year 1.

The Arabic pathway is designed for beginner learners of Arabic. Students will take four units of Arabic, one of them at the Qasid Institute in Jordan or another partner institution during the summer after year 1. Programme convenor: Dr Mustafa Shah ()

Visit the website http://www.soas.ac.uk/anthropology/programmes/ma-medical-anthropology-and-intensive-language/

Structure

- Core course: Cultural Understandings of Health - 15PANC093 (1.0 unit).

- Dissertation in Anthropology and Sociology - 15PANC999 (1.0 unit). This is a 10,000 word dissertation on a topic agreed with the Programme Convenor of the MA Medical Anthropology and the candidate’s supervisor.

- In addition, all MA Anthropology students 'audit' the course Ethnographic Research Methods during term 1 - this will not count towards your 4 units.

- Students without previous experience of anthropology must take the foundation course, Theoretical Approaches to Social Anthropology - 15PANC008 (1.0 unit).

Option Courses - Group A and Group B:

Students then choose TWO 0.5 unit courses from the Group A and B lists.

- AT LEAST ONE of the two 0.5 unit courses normally must come from Group A
- Students not taking Theoretical Approaches to Social Anthropology may then select their fourth unit (either a single 1.0 unit course or two 0.5 unit courses) from the Option Courses list.
- Alternatively, one language course may be taken from the Faculty of Languages and Cultures
- In the two-year language pathway, students take 2 intensive language units and Cultural Understandings of Health (1 unit) in their first year. During the summer, they will participate in a summer school abroad (location dependant on language). Upon their return, they will take one intensive language unit in their second year and two optional anthropology units. In the intensive-language pathway, the same rules apply as for the usual MA.

Programme Specification

MA Medical Anthropology and Intensive Language Programme Specification (pdf; 230kb) - http://www.soas.ac.uk/anthropology/programmes/ma-medical-anthropology-and-intensive-language/file93566.pdf

Teaching & Learning

Aims and Outcomes:
- All students are introduced to the types of problem and areas of questioning which are fundamental to the anthropology of medicine.

- Students new to the discipline are given knowledge of the general principles of anthropological enquiry

- All students develop advanced knowledge and understanding of the theoretical approaches which help form an anthropological perspective.

- All students gain an understanding of the practical methods by which this perspective is applied in field research.
All students will be provided with a near proficient ability in a language.

Knowledge:

- Students will be familiar with the foundational literature on the basis of which medical anthropology is linked to and emerges from broader disciplinary concerns.

- Students will have knowledge of the intersections linking medical anthropology to related fields, such as social studies of science, studies in bioethics, and critical approaches to public health

- Students will be familiar with the numerous ethnographic studies of health and illness.

Intellectual (thinking) skills:

- Students will learn to deploy an ethnographic kind of questioning – one directed toward teasing out of complex situations the sets of particular norms or principles which condition or shape them.

- As anthropologists, they will be trained to look for the specifically social in everything (even & especially in the “natural”)

- Students will learn how to form an anthropological problem – that is to distinguish an anthropological problem from a mere topic or area of interest.

Subject-based practical skills:

- Personal drive: Students are expected to take responsibility for their own learning

- Students will develop research skills: including location and adjustment to differing types of library collection, as well as locating organizations and people who hold significant information

- Listening & understanding: Students will be able to assimilate complex arguments quickly on the basis of listening – and to discuss or disagree constructively with points made by others.

- Planning and problem solving: students will be able to set targets and achieve them, and will be able to work well to deadlines.

- Working in a group: students will learn to lead by contributing to the development of consensus.

- In the two year intensive language pathway, to acquire/develop skills in a language to Effective Operational Proficiency level, i.e., being able to communicate in written and spoken medium in a contemporary language.

Transferable skills:

- Students will develop an ability to begin from a general question or issue and develop an appropriate research model and method.
- Ability to clearly represent a concise understanding of a project/problem and its solution.
- An ability to recognize and appreciate for what it is an unconventional approach or an unfamiliar idea
- An ability creatively to resolve conflict while working in a team; being able to see the other person’s point of view
- An ability to work and feel at ease in multicultural or cross cultural environments.

Find out how to apply here - http://www.soas.ac.uk/admissions/pg/howtoapply/

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Global population, economic growth and on-going environmental deterioration are increasing the pressure on existing natural systems. Read more
Global population, economic growth and on-going environmental deterioration are increasing the pressure on existing natural systems. Their ability to provide natural resources such as food, water and energy is at risk and waning. Under conditions of globalization, these processes are most forceful in developing countries and emerging economies with high growth rates, low awareness, loss of existing traditional knowledge bases and weak governance structures. This calls for specialists and leadership in order to develop and employ managerial, economical, governance, and technical solutions – in short, professionals with lateral understanding and trans-disciplinary approaches for a sustainable development.

The objective of the program is to form such experts. Participants are provided with appropriate knowledge and skills to analyze current problems related to the usage and management of natural resources.

Target groups of the program are recently graduated professionals with working experience in public or private institutions, authorities and enterprises of the natural resources sector. The applicants should be active in or dealing with natural resources management and have an interest in learning and working in an intercultural and multidisciplinary environment.

The master program “Natural Resources Management & Development” (NRM) provides a practice oriented and skills-based learning experience in which students develop their capacity for critical thinking, and creative problem solving. It addresses bachelor’s degree holders principally of Engineering, Natural Sciences and Social Sciences, who aim to deepen their knowledge in Natural Resources Management and wish to acquire management and leadership skills as well as regional and intercultural competences. These experts ought to be able to assess natural resources and develop appropriate solutions considering the complex linkages with economic, social and ecological aspects.

Contents

The program consists of basic modules, including “Management of Natural Resources Systems”, “Natural Resources Economics and Governance”, ”International Cooperation and Development” and “Project and Business Management” with the aim of providing an overview on natural resources management, economics, project management and the regional and institutional context. In addition, the participants select 10 specialized electives related to topics of natural resources management emphasizing the particular situation.

The fourth semester will focus on the preparation of the master thesis. Internships and research stays if possible together with a local institution or company guarantee the practical orientation of the master research. Tutors pay particular attention that the knowledge acquired in the first three semesters is applied in the individual projects.

Tuition

Semester contribution fees, additional fees for field trips, conference participation and course materials. For more information on the semester contribution fees: https://www.th-koeln.de/en/academics/fees_5908.php

Funding

Applicants may receive one of the limited numbers of scholarships. Available are full time scholarships from the DAAD EPOS Program for applicants from DAC-list countries.

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Global population, economic growth and on-going environmental deterioration are increasing the pressure. on existing natural systems. Read more
Global population, economic growth and on-going environmental deterioration are increasing the pressure
on existing natural systems. Their ability to provide natural resources such as food, water and energy is at risk and waning. Under conditions of globalization, these processes are most forceful in developing countries and emerging economies with high growth rates, low awareness, loss of existing traditional knowledge bases and weak governance structures. This calls for specialists and leadership in order to develop and employ managerial, economical, governance, and technical solutions. Next to technical and managerial knowledge, they should also be familiar with the practices of projects between Europe and Vietnam and well trained in intercultural communication, language, culture and politics.

The objective of the program is to form such experts in the field of NRM and related concepts and methods within the context of European-Vietnamese cooperation. Participants are provided with appropriate knowledge and skills to analyze current problems related to the usage and management of natural resources. The program targets graduated professionals with working experience in public or private institutions, authorities and enterprises of the natural resources sector. The applicants should have an interest in learning and working in an intercultural and multidisciplinary environment.

The master program “Natural Resources Management & Development - South East Asia” (NRM SEA) provides a practice oriented and skills-based learning experience in which students develop their capacity for critical thinking, and creative problem solving. It addresses bachelor’s degree holders principally of Engineering, Natural Sciences and Social Sciences, who aim to deepen their knowledge in Natural Resources Management and wish to acquire management and leadership skills as well as regional and intercultural competences. These experts ought to be able to assess natural resources and develop appropriate solutions considering the complex linkages with economic, social and ecological aspects. The consolidation of different disciplines has not only a methodological dimension but a cultural and a human one, because interdisciplinary team work requires knowledge sharing and effective communication.

Contents

The program consists of basic modules, like “Management of Natural Resources Systems”, “Natural Resources Economics and Governance”, ”International Cooperation and Development” and “Project and Business Management” with the aim of providing an overview on natural resources management, economics, project management and the regional and institutional context. In addition, the participants select 10 specialized electives related to topics of natural resources management and tools emphasizing the particular situation. The first and second semester will be conducted in Hanoi at the Vietnam Academy for Water Resources while in the third semester the student will study at TH Köln, Germany.

The fourth semester will focus on the preparation of the master thesis. Internships and research stays if possible together with a local institution or company guarantee the practical orientation of the master research. Tutors pay particular attention that the knowledge acquired in the first three semesters is applied in the individual projects.

Tuition

Tuition fees in Vietnam, basic course fees for field trips, conference participation and course material

Funding

Applicants may receive one of the limited numbers of scholarships. Available are full time scholarships from the DAAD “Sur-Place” Program for Vietnamese and foreign applicants.

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This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world. Read more

This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world.

Our research draws on neuroscience, cognitive science, linguistics, computer science, mathematics, statistics and psychology to span knowledge representation and reasoning, the study of brain processes and artificial learning systems, computer vision, mobile and assembly robotics, music perception and visualisation. We aim to give you practical knowledge in the design and construction of intelligent systems so you can apply your skills in a variety of career settings.

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.

Compulsory courses:

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

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses:

  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Processing

You can choose from a variety of optional courses including:

  • Advanced Vision
  • Algorithmic Game Theory and Its Applications
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Robotics: Science and Systems
  • Human-Computer Interaction
  • Software Architecture, Process and Management
  • Text Technologies for Data Science
  • Computational Cognitive Neuroscience

Career opportunities

Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to spacecraft control.

Recent graduates are now working as software developers and engineers, programmers and data analysts for companies such as HarperCollins, J.P. Morgan, Nokia, IBM, Amazon, Soundcloud and the Bank of England.



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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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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. Read more

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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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. Read more

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

Radboud University Master's Open Day 10 March 2018



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Data Science brings together computational and statistical skills for data-driven problem solving. Read more
Data Science brings together computational and statistical skills for data-driven problem solving. This rapidly expanding area includes machine learning, 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.

Degree information

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 wide range of industry partners.

Students undertake modules to the value of 180 credits.

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

Core modules
-Applied Machine Learning
-Introduction to Supervised Learning
-Introduction to Statistical Data Science

Optional modules - students choose a minimum of 30 credits and a maximum of 60 credits from the following optional modules:
-Cloud Computing (Birkbeck)
-Machine Vision
-Information Retrieval & Data Mining
-Statistical Natural Language Processing
-Web Economics

Students choose a minimum of 0 credits and a maximum of 30 credits from these optional Statistics modules:
-Statistical Design of Investigations
-Applied Bayesian Methods
-Decision & Risk

Students choose a minimum of 15 credits and a maximum of 15 credits from these elective modules:
-Supervised Learning
-Graphical Models
-Bioinformatics
-Affective Computing and Human-Robot Interaction
-Computational Modelling for Biomedical Imaging
-Stochastic Systems
-Forecasting

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.

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. A thorough understanding of the fundamentals required from the best practitioners, and this programme's broad base, assists data scientists to adapt to rapidly evolving goals. This is a 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
-Last.fm
-Cisco
-Deutsche Bank
-IBM
-Morgan Stanley

Why study this degree at UCL?

The 2014 Research Excellence Framework ranked UCL first in the UK for computer science. 61% of its research work is rated as world-leading and 96% as internationally excellent.

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; and 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.

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The UCL School of Pharmacy has an international reputation in natural drug discovery and the evaluation of drug leads from natural sources. Read more

The UCL School of Pharmacy has an international reputation in natural drug discovery and the evaluation of drug leads from natural sources. This MSc has been designed in response to ever-increasing interest in the development and use of medicines derived from natural products.

About this degree

This programme aims to train students in the methods used to analyse and characterise medicinal natural products, to examine the safety and efficacy of currently used herbal medicines, analytical and bioassay methods, and the ethnopharmaceutical uses of plants from traditional systems of medicines.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (120 credits), and a research dissertation (60 credits).

Core modules

  • Analytical Techniques in Phytochemistry
  • Biodiversity and Medicines
  • Medicinal Natural Products
  • Natural Products Discovery
  • Formulation of Natural Products and Cosmeceuticals

Optional modules

  • There are no optional modules for this programme.

Dissertation/report

All students undertake a four-month research project in the third term which culminates in a dissertation. Topics range from natural product isolation and characterisation, synthesis, analysis, and a survey of medicinal products used in the community.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, tutorials and laboratory-based practical classes. Assessment is through a combination of written examinations, coursework and practical assignments, and the research project and oral presentation.

Further information on modules and degree structure is available on the department website: Medicinal Natural Products and Phytochemistry MSc

Careers

Recent graduates of this programme have progressed to careers in herbal, phytopharmaceutical or health food sectors. Some are involved in drug discovery while others pursue a PhD in the UK or overseas.

Why study this degree at UCL?

The programme provides a broad overview of natural product science, the impact of natural products as medicines, their analysis and their place in various societies.

Specifically the programme covers herbal medicines in healthcare and their safety and efficacy, with examples of natural products as medicines. There will also be lectures on the analysis of natural products and their place in the drug discovery process.

A visit to an industrial manufacturer of herbal medicinal products will take place.

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: School of Pharmacy

87% 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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Our modern world is witnessing a growth of online data in a variety of forms, including web documents, blogs, social networks, digital libraries and medical records. Read more
Our modern world is witnessing a growth of online data in a variety of forms, including web documents, blogs, social networks, digital libraries and medical records. Much of this data contains valuable information, such as emerging opinions in social networks, search trends from search engines, consumer purchase behaviour, and patterns that emerge from these huge data sources.

The sheer volume of this information means that traditional stand-alone applications are no longer suitable to process and analyse this data. Our course equips you with the knowledge to contribute to this rapidly emerging area.

We give you hands-on experience with various types of large-scale data and information handling, and start by providing you with a solid understanding of the underlying technologies, in particular cloud computing and high-performance computing. You explore areas including:
-Mobile and social application programming
-Human-computer interaction
-Computer vision
-Computer networking
-Computer security

You also obtain practical knowledge of processing textual data on a large scale in order to turn this data into meaningful information, and have the chance to work on projects that are derived from actual industry needs proposed by our industrial partners.

We are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent (REF 2014).

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

Today’s computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our staff are driven by creativity and imagination as well as technical excellence. We are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist staff working on data analytics include:
-Dr Luca Citi – machine learning, learning from biological signals and data (EEG, etc)
-Dr Adrian Clark – automatic construction of vision systems using machine learning and evaluation of algorithms, data visualisation and augmented reality
-Professor Maria Fasli – analysis of structured/unstructured data, machine learning, adaptation, semantic information extraction, ontologies, data exploration, recommendation technologies
-Professor John Gan – machine learning for data modelling and analysis, dimensionality reduction and feature selection in high-dimensional data space
-Dr Udo Kruschwitz – natural language processing, analysis textual/unstructured data, information retrieval
-Professor Massimo Poesio – cognitive science of language, text mining, computational linguistics
-Professor Edward Tsang – applied AI, constraint satisfaction, computational finance and economics, agent-based simulations

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

Demand for skilled graduates in the areas of big data and data science is growing rapidly in both the public and private sector, and there is a predicted shortage of data scientists with the skills to understand and make commercial decisions based on the analysis of big data.

Our recent graduates have progressed to a variety of senior positions in industry and academia. Some of the companies and organisations where our former graduates are now employed include:
-Electronic Data Systems
-Pfizer Pharmaceuticals
-Bank of Mexico
-Visa International
-Hyperknowledge (Cambridge)
-Hellenic Air Force
-ICSS (Beijing)
-United Microelectronic Corporation (Taiwan)

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.

Big Data and Text Analytics - MSc
-MSc Project and Dissertation
-Information Retrieval
-Cloud Technologies and Systems (optional)
-Group Project
-High Performance Computing
-Machine Learning and Data Mining
-Natural Language Engineering
-Professional Practice and Research Methodology
-Text Analytics
-Advanced Web Technologies (optional)
-Data Science and Decision Making (optional)
-Big-Data for Computational Finance (optional)
-Computer Security (optional)
-Computer Vision (optional)
-Creating and Growing a New Business Venture (optional)
-Mobile & Social Application Programming (optional)

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