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Masters Degrees (Information Retrieval)

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

Research profile

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

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

Our primary areas of research are:

natural language processing and computational linguistics
spoken language processing
dialogue and multimodal interaction
information extraction, retrieval, and presentation
computational theories of human cognition
educational and assistive technology
Much of our research is applied to software development, in areas as diverse as social media, assisted living, gaming and education.

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

Many of our researchers are involved in two cross-disciplinary research centres:

Centre for Speech Technology Research (CSTR)

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

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

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

Human Communication Research Centre

The Human Communication Research Centre (HCRC) is an interdisciplinary research centre at the Universities of Edinburgh and Glasgow that brings together theories and methods from several formal and experimental disciplines to understand better how this happens.

We focus on spoken and written language; we also study communication in other visual, graphical and computer-based media.

Training and support

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

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

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

Facilities

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

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

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

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

Career opportunities

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

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Organisations operate within increasingly unpredictable, competitive, constrained and demanding environments. Information is crucial to their success as it is required for decision making at all levels. Read more

Course Description

Organisations operate within increasingly unpredictable, competitive, constrained and demanding environments. Information is crucial to their success as it is required for decision making at all levels. Consequently there is a need to understand the strategic importance of information and develop agile, effective and secure ways to exploit it to its full potential. To do this, effective information capability management must be developed throughout the organisation so that the right information is available to the right people at the right time in an effective, efficient and secure manner.

An appropriate infrastructure is required to enable effective information capability management to address strategic business needs. This is dependent on joined-up systems of processes, technology and appropriately skilled, competent and motivated people focused on delivering clearly understood business benefit. The Information Capability Management (ICM) MSc has been developed to address these important issues.

Overview

Skilled professionals are needed to enable organisations to realise the strategic benefits that successfully exploiting information can provide. Success in business of all types and in all sectors, both public and private, is dependant on:

•Understanding the value of information as a strategic asset
•Developing agile, effective and efficient systems that make this information available.
•Countering cyber threats with appropriate cyber security.

The internationally recognised Information Capability Management course successfully supports the development of these professionals. Students from Government departments, industry and other organisations within the UK and internationally come together to study and discuss issues and develop skills that will enable solutions now and in the future.

Key goals of the course are to provide students with postgraduate level education in order to:

•Develop in individuals an awareness of the management, user and supplier communities
•Recognise the stakeholder roles, needs and expectations within these communities
•Enable effective communication and a shared understanding between these stakeholders in order to meet capability objectives
•Master the principles and practice that underlie the delivery of effective, efficient and secure systems in various business spaces that exploit information in order to provide strategic benefit

Start date: Full Time: September / Part Time: January

Duration: Full-time MSc - one year, Part-time MSc - up to three years, Full-time PgCert - one year, Part-time PgCert - two years, Full-time PgDip - one year, Part-time PgDip - two years

Course overview

MSc students must complete a taught phase consisting of twelve modules, followed by an individual dissertation in a relevant topic.

PgDip students are required to undertake the same taught phase as the MSc, but without the individual dissertation.

PgCert students must complete the core module (Foundations of Information Systems) together with five other modules.

Modules

Qualifications achieved by completing:
PgCert: Foundations of Information Systems and any five other modules
PgDip: All modules
MSc: All modules and the dissertation.

Core:
- Cyber Security and Information Assurance
- Dissertation
- Emerging Technology Monitoring
- Foundations of Information Systems
- Information Storage and Retrieval
- Methods and Tools for Information Systems Development
- Organisation Development
- Professional Issues
- Programme and Project Management for Information Systems
- Software Engineering (IS)
- Strategic Application of Information Systems
- Systems Architecture
- Data-led Decision Support
- Data Modelling, Storage and Management

Individual Project

The Individual Project is the opportunity for a student to utilise and demonstrate their understanding of the taught phase of the course by applying their learning to a real world problem. It is also an opportunity to develop skills and achieve a greater level of understanding in a specific area or areas of relevance to the course. Students are allocated a supervisor and have access to subject matter experts to support them in the project phase.

Assessment

Spread throughout the programme and includes coursework, group presentations and examinations during the taught phase and for the MSc a research based dissertation.

Career opportunities

Takes you on to further senior career opportunities and to become one of the next generation of senior professionals delivering business benefit through exploitation of information with skills in appropriate areas including business analysis, strategy development and implementation, information assurance, cyber security, organisational development and strategic application of information systems.

For further information

On this course, please visit our course webpage http://www.cranfield.ac.uk/Courses/Masters/Information-Capability-Management

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The Masters in Data Science provides you with a thorough grounding in the analysis and use of large data sets, together with experience of conducting a development project, preparing you for responsible positions in the Big Data and IT industries. Read more
The Masters in Data Science provides you with a thorough grounding in the analysis and use of large data sets, together with experience of conducting a development project, preparing you for responsible positions in the Big Data and IT industries. As well as studying a range of taught courses reflecting the state-of-the-art and the expertise of our internationally respected academic staff, you will undertake a significant programming team project, and develop your own skills in conducting a data science project.

Why this programme

◾The School of Computing Science is consistently highly ranked achieving 2nd in Scotland and 10th in the UK (Complete University Guide 2017)
◾The School is a member of the Scottish Informatics and Computer Science Alliance: SICSA. This collaboration of Scottish universities aims to develop Scotland's place as a world leader in Informatics and Computer Science research and education.
◾We currently have 15 funded places to offer to home and EU students.
◾You will have opportunities to meet employers who come to make recruitment presentations, and often seek to recruit our graduates during the programme.
◾You will benefit from having 24-hour access to a computer laboratory equipped with state-of-the-art hardware and software.

Programme structure

Modes of delivery of the MSc in Data Science include lectures, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses

◾Big data
◾Data fundementals
◾Information retrieval
◾Machine learning
◾Research methods and techniques
◾Text as data
◾Web science
◾Masters team project.

Optional courses

◾Advanced networking and communications
◾Advanced operating systems
◾Algorithmics
◾Artificial intelligence
◾Big data: systems, programming and management
◾Computer architecture
◾Computer vision methods and applications
◾Cryptography and secure development
◾Cyber security forensics
◾Cyber security fundamentals
◾Distributed algorithms and systems
◾Enterprise cyber security
◾Functional programming
◾Human computer interaction
◾Human computer interaction: design and evaluation
◾Human-centred security
◾Information retrieval
◾Internet technology
◾IT architecture
◾Machine learning
◾Mobile human computer interaction
◾Modelling reactive systems
◾Safety critical systems.
◾Software project management
◾Theory of Computation

Depending on staff availability, the optional courses listed here may change.

If you wish to engage in part-time study, please be aware that dependent upon your optional taught courses, you may still be expected to be on campus on most week days.

Industry links and employability

◾The advent of Big Data tools in recent years has facilitated the large-scale mining of voluminous data, to allow actionable knowledge and understanding, known as Data Science. For instance, search engines can gain insights into how ambiguous a query is according to the querying and clicking patterns of different users. Data Science combines a thorough background in Big Data processing techniques, combined with techniques from information retrieval and machine learning, to permit coherent and principled solutions allowing real insights and predictions to be obtained from data.
◾The programme includes a thorough grounding in professional software development, together with experience of conducting a development project. The programme will prepare you for a responsible position in the IT industry.
◾The School of Computing Science has extensive contacts with industrial partners who contribute to several of their taught courses, through active teaching, curriculum development, and panel discussion. Recent contributors include representatives from IBM, J.P. Morgan, Amazon, Adobe, Red Hat and Bing.
◾During the programme students have an opportunity to develop and practice relevant professional and transferrable skills, and to meet and learn from employers about working in the IT industry.

The Data Lab

We work closely with The Data Lab, an internationally leading research and innovation centre in data science. Established with an £11.3 million grant from the Scottish Funding Council, The Data Lab will enable industry, public sector and world-class university researchers to innovate and develop new data science capabilities in a collaborative environment. Its core mission is to generate significant economic, social and scientific value from data. Our students will benefit from a wide range of learning and networking events that connect leading organisations seeking business analytics skills with students looking for exciting opportunities in this field.

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The Library and Information Studies MA provides the ideal foundation for career progression in library or information work. Read more
The Library and Information Studies MA provides the ideal foundation for career progression in library or information work. The one-year programme is accredited by the professional association Chartered Institute of Library and Information Professionals (CILIP), and offers students a wide range of up-to-date learning opportunities while helping to develop strong networks designed to enhance their employability.

Degree information

The programme prepares students for professional practice in the field of library and information studies. It equips them with the practical skills required for the identification, location, management and organisation of information and information stores, and fosters an understanding of the processes by which information is produced, disseminated, controlled and recorded.

Students undertake modules to the value of 180 credits. The programme consists of six core modules (90 credits), two optional modules (30 credits) and a research dissertation (60 credits). A Postgraduate Diploma, six core modules (90 credits), two optional modules (30 credits), full-time nine months or flexible study 2-5 years, is offered.

Core modules
-Cataloguing and Classification 1
-Collection Management and Preservation
-Information Sources and Retrieval
-Introduction to Management
-Principles of Computing and Information Technology
-Professional Awareness

Optional modules - students choose two of the following:
-Advanced Preservation
-Cataloguing and Classification 2
-Digital Resources in the Humanities
-Electronic Publishing
-Historical Bibliography
-Individual Approved Study
-Information Governance
-Knowledge Representation and Semantic Technologies
-Manuscript Studies
-Publishing Today
-Records Management
-Web Publishing
-Information Literacy
-Academic and Journals Publishing

Dissertation/report
All MA students undertake an independent research project which culminates in a dissertation of 10,000–12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, computer laboratory and classroom practicals, with a strong emphasis on active learning and the acquisition of practical skills. Assessment is through a mixture of essays, reports, examination and practical assignments such as website design and the creation of indexing tools.

Placement
The work placement is only open to full-time students and forms part of the G030 Professional Awareness module. The work placement gives students experience of how the techniques they have learned may be applied in practice. Placements last for two weeks, and are undertaken at the beginning of the third term. We arrange placements individually for each student and do our best to match the placement with their interests and experience.

Careers

The programme aims to be broad-based: we are not trying to produce graduates who can work in only one kind of library or information service. The skills we try to impart are, therefore intended to apply in a wide range of different jobs.

Top career destinations for this degree:
-Information Officer, Trowers and Hamlins
-News Reference Specialist, British Library
-Cataloguer, Eton College
-Librarian, BSix
-Knowledge and Information Specialist, CRU Group

Employability
As a vocational Master's, this programme prepares students for employment in the sector, and, in most cases, for promotion from their pre-library school role as a library assistant to a qualified librarian role, such as senior library assistant, assistant librarian, librarian and library manager. Students occasionally choose careers in information provision, such as taxonomists and web designers. There are specialist employment agencies that place students in both short-term and permanent positions, so if students do not find their ideal post straight away, they usually find suitable employment while continuing to seek their ideal post.

Why study this degree at UCL?

This well-established programme is accredited by CILIP (to 2019). It attracts an outstanding team of researchers, teachers, students, practitioners and information industry leaders. It combines an appreciation of the traditional library with the latest developments in internet and digital technologies to develop an understanding of the ever-evolving information environment.

Networking opportunities include a two-week work placement, regular journal club and speaker events, guest lectures by professionals and career seminars sponsored by industry professionals.

Students benefit from UCL's proximity to major libraries and repositories, including the British Library and the Senate House LIbrary of the University of London.

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This MRes is aimed at those wishing to broaden or deepen understanding of aspects of the information world at postgraduate level, or to prepare for doctoral studies. Read more
This MRes is aimed at those wishing to broaden or deepen understanding of aspects of the information world at postgraduate level, or to prepare for doctoral studies. It is also aimed at mid-career information and cultural professionals who wish to develop their leadership, management and professional skill.

Degree information

This is a flexible programme of study combining information disciplines, information technology, leadership, management and professional skills. The programme is tailored to individual needs, closely related to students' current or future employment or research goals. Through research skills classes and a substantial research project, students develop skills for further study and career development.

Students undertake modules to the value of 180 credits. The programme consists of four optional modules (60 credits) and a research dissertation (120 credits). There are no core modules for this programme.

Optional modules - students select in conjunction with their Director of Studies, four modules from the range of postgraduate programmes offered by the Department of Information Studies. Typically, the selection is made across the following areas:
-Management of Services, Resources or Systems
-Information and Communication Systems and Technologies
-Adult Learning and Professional Development
-Archives and Records Management
-Digital Humanities
-Information Services for Specialist Media or Users
-Information Sources, Organisation and Retrieval
-Publishing
-Cultural Heritage

The full range of postgraduate modules is available on the UCL Information Studies website. On occasion it may be appropriate for students to take modules offered by another UCL department also.

Dissertation/report
All students undertake an independent research project in an applied or theoretical area of information work, which culminates in a dissertation of 25,000 words.

Teaching and learning
Taught modules are delivered through lectures, seminars, groupwork and practicals. Research skills are developed through classes within the department and students are encouraged to take courses run by UCL Doctoral School. Assessment is through a mixture of essays, reports, examination and practical assignments and by the dissertation and viva voce.

Careers

The programme provides an ideal foundation for further doctoral research, as a preparation for an MPhil or PhD, and enables career development of information professionals into senior and managerial roles.

Places of employment or further study of recent students include:
-Staffordshire County Council
-National Library of Portugal
-University of Botswana
-UCL

Why study this degree at UCL?

UCL Information Studies is unique in the UK with programmes spanning archives, records management, information studies and systems, digital humanities and publishing. Students have unparalleled opportunities for cross-domain engagement and the opportunity to work with other departments at UCL.

Students benefit from UCL's central London location, and many premier information and cultural institutions are within easy reach. Staff are experts in their field and closely involved with the professional bodies and companies, supporting students in building contacts and widening experience.

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Qatar has a bold vision to become a knowledge society. It is also committed to developing a world-class Qatar National Library (QNL) which will ‘bridge with knowledge Qatar’s heritage and future’. Read more
Qatar has a bold vision to become a knowledge society. It is also committed to developing a world-class Qatar National Library (QNL) which will ‘bridge with knowledge Qatar’s heritage and future’. This ground-breaking MA aims to nurture a world-class cadre of library professionals and train the future leaders of the sector.

Degree information

The programme provides students with an awareness of current issues and trends in library and information work. It fosters understanding of the processes by which information is produced, disseminated, controlled and recorded, and equips students with practical skills for the identification, location, management and organisation of information.

Students undertake modules to the value of 180 credits. The programme consists of six core modules (90 credits), two optional modules (30 credits), and a dissertation (60 credits). The programme consists of six core modules (90 credits), two optional modules (30 credits), and a dissertation (60 credits). A Postgraduate Diploma (120 credits, full-time nine months) is also offered. Students complete all modules except the dissertation.

Core modules
-Knowledge Organsiation and Access
-Collection Management
-Information Sources and Retrieval
-Introduction to Management
-Principles of Computing and Information Technology
-Professional Awareness
-Dissertation

Optional modules
-The Book in the World
-Digital Resources in the Humanities
-Information Literacy
-Interdisciplinary Methods for the Study of Cultural Heritage
-Introduction to Archives and Preservation
-Islamic Manuscripts
-Library Systems and Data Management
-Services to Children and Young People

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, private reading, seminars, practical classes, small group work, group project work, computer laboratory sessions, essay writing, and independent research. Except for short courses, all programmes are delivered in afternoon sessions. Students can access and use the virtual learning environment (Moodle) at UCL, which provides the opportunity to benefit from the expertise of UCL staff both in London and Qatar. Intensive short courses will also be delivered by visiting staff from UCL Information Studies (London). Assessment takes a variety of forms including: essays, portfolios, prepared practical work, individual and group project work, report writing, policy writing, presentations, peer assessment and the dissertation. There is also a written examination, attached to the professional awareness module, and accounting for 50% of the marks.

Careers

Graduates will be able to work in a wide network of settings including school libraries, libraries based in government ministries, and many more libraries in institutions such as museums and societies, and countless business libraries and archives.

Why study this degree at UCL?

The MA in Library and Information Studies at UCL Qatar has become the first degree programme of its kind in the region to be formally accredited by CILIP: the Chartered Institute of Library and Information Professionals. The MA in Library and Information Studies is identical to the programme offered at UCL’s Department of Information Studies in London – the UK’s premier facility for the teaching of library and information studies.

Students have the opportunity to network with leading library professionals from Qatar and the region and will undertake a placement in a local or international library.

Qatar is investing heavily in libraries, infrastructure and capacity building. This is an exceptionally exciting period for students and professionals who are looking to develop their career in the region.

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The Master's of Research in Historical Research is a one-year course that is research-oriented and allows specialisation in particular research areas. Read more

Introduction

The Master's of Research in Historical Research is a one-year course that is research-oriented and allows specialisation in particular research areas. Students are allocated an individual supervisor to direct their independent study and plan the curriculum to reflect their interests and needs. Students should maintain regular contact with supervisors through email and an agreed schedule of meetings to discuss their work and review draft submissions.

The Master's of Research (MRes) is designed
- to enable students to become well-trained historians
and
- to demonstrate their fitness to undertake research to doctoral level at Stirling or other universities in Britain and overseas. Both are achieved through the completion of independent study modules, field seminars and skills training, under supervision.

There are four variants of the MRes in Historical Research:
- MRes in Historical Research: The American Revolutionary Era
- MRes in Historial Research: Medieval Scottish History
- MRes in Historical Research: Environmental History
- MRes in HIstorical Research: Modern European History and Politics

Students are allocated an individual supervisor to direct their independent study and plan the curriculum to reflect their interests and needs.

Accreditation

The MRes programme and all constituent modules are constructed in line with the University's academic procedures and are fully assessed and externally examined. The programme is recognised by both the Arts and Humanities Research Council and the Economic and Social Research Council both of whom have given PhD awards to outstanding Stirling graduates of the MRes.

Key information

- Degree type: MRes
- Study methods: Part-time, Full-time
- Duration: Full-time: 12 months Part-time: 24 months
- Start date: September
- Course Director: Dr Jim Smyth

Course objectives

This programme prepares you for further research:
- to co-ordinate the provision of additional or external skills training and to develop the application of research skills
- students will obtain practical experience of devising and applying a research method to interrogate primary sources
- qualitative and quantitative analyses
- the application of IT in information retrieval, especially bibliographical database software,
- communication skills, written and oral
- project design involving the conceptualisation of research questions and the presentation of data and data analysis

English language requirements

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.5 with 6.0 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade B
- Pearson Test of English (Academic): 60 with 56 in each component
- IBT TOEFL: 90 with no subtest less than 20

For more information go to English language requirements https://www.stir.ac.uk/study-in-the-uk/entry-requirements/english/

If you don’t meet the required score you may be able to register for one of our pre-sessional English courses. To register you must hold a conditional offer for your course and have an IELTS score 0.5 or 1.0 below the required standard. View the range of pre-sessional courses http://www.intohigher.com/uk/en-gb/our-centres/into-university-of-stirling/studying/our-courses/course-list/pre-sessional-english.aspx .

Career opportunities

The MRes has been designed with three career destinations in mind:
- to prepare graduate students for further research at doctoral level
- as a route to an academic career
- as a higher degree in its own right

The MRes will also enhance continuing professional development, particularly in teaching, journalism, marketing, and heritage management through in-depth study of particular fields; by aiming to develop critical analytical skills and research techniques, the programme provides preparation for a wide variety of research-based careers in the public and private sectors.
Most of our graduates go on to study for a PhD either by continuing at Stirling or at another University in the UK, Europe or North America. Recent graduates have secured posts in firms and institutions as varied as Historic Scotland, Sea World, and the Defence Science and Technology Laboratory (Dstl).

Chances to expand your horizons
There is a lively series of guest lectures which students can attend on this programme.

Where are our graduates now?
The MRes has been designed with three career destinations in mind:
- to prepare graduate students for further research at doctoral level and as a route to an academic career
- as a higher degree in its own right
- to enhance continuing professional development, particularly in teaching, journalism, marketing, and heritage management through in-depth study of particular fields; by aiming to develop critical analytical skills and research techniques, the programme provides preparation for a wide variety of research-based careers in the public and private sectors

Employability

Skills you can develop through this programme
- command of a substantial body of historical knowledge
- understand how people have existed, acted and thought in the context of the past
- read and use texts and other source materials critically and empathetically
- appreciate the complexity and diversity of situations, events and past mentalities
- recognise there are ways of testing statements and that there are rules of evidence which require integrity and maturity
- reflect critically on the nature and theoretical underpinnings of the discipline
- marshall an argument, be self-disciplined and independent intellectually
- express themselves orally and in writing with coherence, clarity and fluency
- gather, organise and deploy evidence, data and information
- analyse and solve problems
- use effectively ICT, information retrieval and presentation skills
- exercise self-discipline, self-direction and initiative
- work with others and have respect for others’ reasoned views
- show empathy and imaginative insight
- prepare for further academic research such as a Phd

In addition, our students have the opportunity to further develop their transferable skills through voluntary internships working on collections of material held within the Division (The Scottish Political Archive and the University's own archive (e.g. UNESCO recognised Royal Scottish National Institution for mentally disabled children).

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This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

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

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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The MRes 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. Read more
The MRes 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 the fundamental principles and technological components of the World Wide Web, learning not only the latest web search and information retrieval technologies and their underlying computational and statistical methods, but also studying essential large-scale data analytics to extract insights and patterns from vast amounts of unstructured data.

Students undertake modules to the value of 180 credits.

The programme consists of two core modules (30 credits), four option modules (60 credits), and the research dissertation (90 credits).

Core modules
-Investigating Research
-Researcher Professional Development

Optional modules
-Complex Networks and Web
-Web Economics
-Information Retrieval and Data Mining
-Distributed Systems and Security
-Multimedia Systems
-Or an elective module from other Computer Science programmes

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. For the research project, each student is liaised with their academic or industrial supervisor to choose a study area of mutual interest. Student performance is assessed by unseen written examinations, coursework and the research 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 MRes makes our students the ideal choice for the best employers in internet-related industries and sectors requiring big data analytics. The MRes 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, their 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 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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Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights. Read more
Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights.

Who is it for?

This programme is for students who have a numerate first degree or can demonstrate numerate skills. Students are often at the early stages of their careers in diverse professions including economics, statistics and computer science.

Students will have a curiosity about data, and will want to learn new techniques to boost their career and be part of exciting current industry developments. The MSc in Data Science includes some complex programming tasks because of the applied nature of the course, so many students have a mathematics or statistics background and enjoy working with algorithms.

Objectives

The demand for data scientists in the UK has grown more than ten-fold in the past five years *. The amount of data in the world is growing exponentially. From analysing tyre performance to detecting problem gamblers, wherever data exists, there are opportunities to apply it.

City’s MSc Data Science programme covers the intersection of computer science and statistics, machine learning and practical applications. We explore areas such as visualisation because we believe that data science is about generating insight into data as well as its communication in practice.

The programme focuses on machine learning as the most exciting technology for data and we have learned from our own graduates that this is of high value when it comes to employment within the field. At City, we have excellent expertise in machine learning and the facilities students need to learn the technical aspects of data analysis. We also have a world-leading centre for data visualisation, where students get exposed to the latest developments on presenting and communicating their results – a highly sought after skill.

Placements

There is the opportunity to do an internship as part of the programme. The final project, which is normally three months for a full-time student, can be extended to six months if you want to study within a specific organisation. When it comes to the big data and data science area, we have established relationships with organisations including the BBC, Microsoft and The British Library so you can be confident that with City, your access to professional experience is unparalleled. One recent student undertook an internship with Google and has since secured a job within the company.

Academic facilities

The School's computer science laboratories are equipped with the latest up-to-date hardware and software. From Oracle’s leading commercial object-relational database server to PCs with state-of-the-art NVidia GPUs for computer graphics, you will have access to an array of tools to support your learning.

The MSc Data Science programme offers two (three by mid 2016) dedicated computer servers for the Big Data module, which you can also use for your final project to analyse large data sets. We give you the opportunity to undertake training in MATLAB, the most popular numerical and technical programming environment, while you study.

Scholarships

A scholarship for the full fees of the MSc will be offered to an outstanding applicant. The scholarship is available to UK/EU and overseas students, studying full-time. To be considered for the scholarship, please include with your full application a one-page essay with your answer to the question:

'What are the challenges that Data Science faces and how would you address those challenges?'

The submission deadline for anyone wishing to be considered for the scholarship is: 1 MAY 2017

Teaching and learning

The teaching and learning methods we use mean that students’ specialist knowledge and autonomy increase as they progress through each module. Active researchers guide your progress in the areas of machine learning, data visualization, and high-performance computing, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.

Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:
-Present and exemplify the concepts underpinning a particular subject.
-Highlight the most significant aspects of the syllabus.
-Indicate additional topics and resources for private study.

Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.

Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.

In addition to lectures, laboratory sessions and tutorial support, you also have access to a personal tutor. This is an academic member of staff from whom you can gain learning support throughout your degree. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.

We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Each module is assessed through a combination of written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply data science methods and techniques.

The individual project is a substantial task. It is your opportunity to develop a research-related topic under the supervision of an academic member of staff. This is the moment when you can apply what you have learnt to solve a real-world problem using large datasets from industry, academia or government and use your knowledge of collecting and processing real data, designing and implementing big data methods and applying and evaluating data analysis, visualisation and prediction techniques. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.

Course content

Data science is the area of study concerned with the extraction of insight from large collections of data.

The course covers the study, integration and application of advanced methods and techniques from:
-Data analysis and machine learning
-Data visualisation and visual analytics
-High-performance, parallel and distributed computing
-Knowledge representation and reasoning
-Neural computation
-Signal processing
-Data management and information retrieval.

It gives you the opportunity to specialise so, once you graduate, you can apply data science to any sector from health to retail. By engaging with researchers and industrial partners during the programme, you can develop your knowledge and skills within a real-world context in each of the above areas.

Core modules
-Principles of data science (15 credits)
-Machine learning (15 credits)
-Big Data (15 credits)
-Neural computing (15 credits)
-Visual analytics (15 credits)
-Research methods and professional issues (15 credits)

Elective modules
-Advanced programming: concurrency (15 credits)
-Readings in computer science (15 credits)
-Advanced databases (15 credits)
-Information retrieval (15 credits)
-Data visualisation (15 credits)
-Digital signal processing and audio programming (15 credits)
-Cloud computing (15 credits)
-Computer vision (15 credits)
-Software agents (15 credits)

Individual project - (60 credits)

Career prospects

From health to retail, and from the IT industry to government, the Data Science MSc will prepare you for a successful career as a data scientist. You will graduate with specialist skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction and explanation, which are in high demand.

City's unique internships, our emphasis on machine learning and visual analytics, together with our links with the industry and Tech City, should help you gain employment as a specialist in data analysis and visualization. Graduates starting a new business can benefit from City's London City Incubator and City's links with Tech City, providing support for start-up businesses.

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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 turn real-world data sets into tools and useful insights, with the help of software and algorithms. Data plays a role in almost every scientific discipline, business industry or social organisation. Read more
Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms.

Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. There is therefore an urgent need for data scientists in whole array of fields. In the Master’s specialisation in Data Science you’ll learn how to turn data into knowledge with the help of computers and how to translate that knowledge into solutions.

Although this Master’s is an excellent stepping-stone for students with ambitions in research, most of our graduates work as data consultants and data analysts for commercial companies and governmental organisations.

Why study Data Science at Radboud University?

- This specialisation builds on the strong international reputation of the Institute for Computing and Information Sciences (iCIS) in areas such as machine learning, probabilistic modelling, and information retrieval.
- We’re leading in research on legal and privacy aspects of data science and on the impact of data science on society and policy.
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- Because of its relevance to all kinds of different disciplines, we offer our students the chance to take related courses at other departments like at language studies (information retrieval and natural language processing), artificial intelligence (machine learning for cognitive neuroscience), chemistry (pattern recognition and chemometrics) and biophysics (machine learning and optimal control).
- The job opportunities are excellent: some of our students get offered jobs before they’ve even graduated and almost all of our graduates have positions within six months after graduating.
- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

See the website http://www.ru.nl/masters/datascience

Admission requirements for international students

- A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of >550 (paper based) or >213 (computer based) or >80 (internet based)
- IELTS score of >6.0
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data:
- To come up with a creative and useful solution.
- To find or program the right tool to turn the data into knowledge.
- To communicate the obtained findings to others.

By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

The job perspective for our graduates is excellent. Industry desperately needs data science specialists at an academic level, and thus our graduates have no difficulty in find an interesting and challenging job. A few of our graduates decide to go for a PhD and stay at the university, but most of our students go for a career in industry. They then typically either find a job at a larger company as consultant or data analysis, or start up their own company in data analytics.

Examples of companies where our graduates end up include SMEs like Orikami, Media11 and FlexOne, and multinationals like ING Bank, Philips, ASML, Capgemini, Booking.com and perhaps even Google.

Our approach to this field

Data nowadays plays a role in almost every scientific discipline as well as industry and is rapidly becoming a key driver of scientific discoveries, business innovation, and solutions for societal challenges such as better healthcare. Medical scientists are sequencing and analysing human genomes to uncover clues to infections, cancer, and other diseases. With huge telescopes, astronomers generate terabytes of data per hour to study the formation of galaxies and the evolution of quasars. Businesses like Google and Amazon are sifting social networking and user preference data to fulfill desires we don't even know we have. Police employing seismology-like data models can predict where crimes will occur and prevent them from happening.

It is then with good reason that data science has been called the sexiest job of the 21st century. Many companies complain about the difficulty to find skilled data scientists and predict this to be even harder in the future. A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data, to come up with a creative and useful solution, to find or program the right tool to turn the data into knowledge, and to communicate the obtained findings to others. By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

See the website http://www.ru.nl/masters/datascience

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The programme aims at preparing engineers to develop and use information technology tools so as to satisfy the widest variety of applications. Read more

Mission and Goals

The programme aims at preparing engineers to develop and use information technology tools so as to satisfy the widest variety of applications. Compared to the Bachelor of Science, Master of Science students acquire greater ability to model and solve complex problems, integrating different advanced skills and technologies. The programme comprises three tracks: Communication and Society Engineering, Sound and Music Engineering, Data Engineering.

The teaching language is English.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/computer-science-and-engineering/computer-science-and-engineering-track-como/

Career Opportunities

The information technology engineer operates mainly in companies manufacturing and distributing information technology and robotics equipment and systems, companies providing products and services with a high information technology content, private organisations and public administration using information technology to plan, design, manage, decide, produce and administrate.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Computer_science_and_engineering_CO_01.pdf
The Master of Science programme in Computer Science and Engineering aims at training engineers able to develop and use information technology tools so as to satisfy the widest variety of applications. Four tracks are available, corresponding to four main cultural areas. The “Communication and Society Engineering” track focuses on the integration of computer science and communication skills, for designing, implementing, presenting and evaluating innovative multimedia applications. The methodologies for the management of data, such as data mining, pattern recognition, information retrieval, constitute the core of the “Data Engineering” track. The “ICT Engineering, Business and Innovation” track aims at building professional profiles that combine a solid computer science background with managerial capabilities, through a selection of computer science and management courses, integrated with a broad cross-disciplinary project, carried out in collaboration with companies and Management Engineering students and professors. Finally, the “Sound and Music Engineering” track (in collaboration with the “Giuseppe Verdi” Music Conservatory of Como) focuses on the concepts and processes that are behind generation, analysis, manipulation/ processing, transport, access, coding and rendering of audio and musical signals. The programme is taught in English.

Subjects

Key subjects available:
Multimedia Interactive Applications for Web and Mobile Devices, Computer Graphics and Applications, Advanced Software Engineering, Advanced Computer Architectures, Performance Evaluation of Computer Systems, Multimedia Information Retrieval, Multimedia Signal Processing, Sound Analysis, Synthesis and Processing, Electronics and Electroacoustic.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/computer-science-and-engineering/computer-science-and-engineering-track-como/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/computer-science-and-engineering/computer-science-and-engineering-track-como/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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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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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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