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The data centre sector is growing and is central to our daily lives. But there’s a shortage of data centre managers who can address the rapid change and complexity faced by the industry. Read more

Course Overview

The data centre sector is growing and is central to our daily lives. But there’s a shortage of data centre managers who can address the rapid change and complexity faced by the industry. Our course will equip experienced professionals with the knowledge and capability to meet the demands of data centre leadership.

Data centres are fast-moving, complex businesses that need decisive, knowledgeable leaders. Our MA course aims to give practising data centre managers the opportunity to develop and advance their leadership abilities.

While our MA includes technical elements, it’s not designed to be a technical course. Rather, it takes broad-based contemporary business theory and applies it to data centre management to help you apply your learning effectively and immediately.

As all of our students continue to work while studying, you’ll have the opportunity to look at your current work and past professional experience to consider how you can apply what you’ve learnt in practice. Together we’ll analyse historical and contemporary management theory, giving you a firm understanding of how it’s evolved, while challenging current thought on business and leadership issues.

Consolidating the breadth of philosophical and theoretical concepts of leadership with the essential underpinning theories of change, risk management, finance, general management and human resources management, our MA programme offers you the opportunity to apply generic constructs to your own data centre workplace.

By the time you graduate, you’ll have the ability to consider, and then apply, leadership and management principles in a number of ways, in line with your organisation’s needs and external demands.

Our lecturers are experienced practitioners with strong professional links. What’s more, our modules are developed with input from industry specialists so you can be sure they’re current, authentic and challenging. Specialists also provide guest lectures, case study material and advice on current and emerging issues for use as ‘provocations’ on our course.

Lord Ashcroft International Business School is one of the largest business schools in the east of England. You'll benefit from state-of-the-art teaching and learning facilities, including our Virtual Learning Environment (VLE) through which you can access study resources and help.

See the website http://www.anglia.ac.uk/study/postgraduate-taught/data-centre-leadership-and-management

Year 1 – Postgraduate Certificate (PG Cert)

Data Centre Leadership
What are the challenges of leading in a complex and dynamic industry? This module sets the scene for the course by helping you develop the aptitude and knowledge needed to lead successful data centre teams, departments and companies. This module looks at topics such as strategic analysis, change management and organisational dynamics, as well as how to foster innovation within the business.

Finance for Non Financial Managers
Finance is a core element of any business activity and a key element of business decisions. Therefore, having a deeper understanding of financial management will enhance your contribution to the business and increase your influence within the company.

Sustainable Design for High Capacity Data Centres
The design of data centres can have a huge influence of their efficiency and sustainability. Leaders who can anticipate and manage future trends in design and sustainability will have an advantage in a fast moving industry. This module will bring you the most up to date thinking on data centre design, while also having a strong emphasis on management and monitoring to maximise efficiency and sustainability.

Year 2 - Postgraduate Diploma (PG Dip)

Data Centre Infrastructure Management, Security and Disaster Recovery
What are the issues when managing complex resources? What strategies can be used to ensure security, identify risk and vulnerability, and mitigate against these? How can you plan for disasters, and can you plans be built with future developments in mind? This module takes these questions and more, helping you to develop answers in the context of your own work.

HRM and Organisational Capability Development
This module looks at managing human resources from the leader’s perspective. You will look at how organisational structures influence behaviour, strategies for managing talented individuals, how to manage contingent labour and organisational performance in a dynamic environment.

Decision Making in Critical Services
Data centres are mission critical environments, experiencing high levels of complexity and change. Due to this, the data centre context is highly sensitive to the outcomes of decisions, and it is important that leaders have the knowledge and capacity to consider and implement complex decisions. This module will give you the opportunity to develop your decision making capabilities, particularly where decision outcomes may be disruptive, innovative or untested in current contexts.

Year 3 – Master of Arts Degree (MA)

Contemporary Issues in Leadership and Management
The data centre industry is a dynamic environment, with new issues emerging as technology develops, political influences change and the global economic situation evolves. These factors all impact on day-to-day leadership and management within the industry. This module will help you to build your own understanding of issues that influence the industry, develop your responses and grow as a thought leader.

Research Methods for Business and Management
Research skills are important in business as well as academia. Producing high quality research can drive innovation and enterprise and form a crucial part of the professional’s portfolio of capability. This module will enable you to develop the key project management and data analysis skills needed to deliver Masters Level research.

Post Graduate Major Project
This final module builds on the knowledge that you have developed through the course, giving you a chance to produce an in-depth academic study into a topic of your choice. Your project could address an issue in your workplace, or examine a theme in the wider industry. Under our supervision, you will further build your own specialist expertise and ultimately enhance your career development.

Assessment

You will complete an assessed piece of work at the end of each module, and a Postgraduate Major Project in your final year. Your assessed work will be relevant to your job and designed to help you develop your skills, knowledge and career.

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The data centre sector is growing and is central to our daily lives. But there’s a shortage of data centre managers who can address the rapid change and complexity faced by the industry. Read more
The data centre sector is growing and is central to our daily lives. But there’s a shortage of data centre managers who can address the rapid change and complexity faced by the industry. Our course will equip experienced professionals with the knowledge and capability to meet the demands of data centre leadership.

Data centres are fast-moving, complex businesses that need decisive, knowledgeable leaders. Our MA course aims to give practising data centre managers the opportunity to develop and advance their leadership abilities.

While our MA includes technical elements, it’s not designed to be a technical course. Rather, it takes broad-based contemporary business theory and applies it to data centre management to help you apply your learning effectively and immediately.

As all of our students continue to work while studying, you’ll have the opportunity to look at your current work and past professional experience to consider how you can apply what you’ve learnt in practice. Together we’ll analyse historical and contemporary management theory, giving you a firm understanding of how it’s evolved, while challenging current thought on business and leadership issues.

Consolidating the breadth of philosophical and theoretical concepts of leadership with the essential underpinning theories of change, risk management, finance, general management and human resources management, our MA programme offers you the opportunity to apply generic constructs to your own data centre workplace.

By the time you graduate, you’ll have the ability to consider, and then apply, leadership and management principles in a number of ways, in line with your organisation’s needs and external demands.

Our lecturers are experienced practitioners with strong professional links. What’s more, our modules are developed with input from industry specialists so you can be sure they’re current, authentic and challenging. Specialists also provide guest lectures, case study material and advice on current and emerging issues for use as ‘provocations’ on our course.

Lord Ashcroft International Business School is one of the largest business schools in the east of England. You'll benefit from state-of-the-art teaching and learning facilities, including our Virtual Learning Environment (VLE) through which you can access study resources and help.

See the website http://www.anglia.ac.uk/study/postgraduate/data-centre-leadership-and-management

Careers

Like many organisations, data centres are experiencing a shortage of senior staff with contemporary and robust skills in leadership and management.

Our MA programme aims to assist those who are already working in managerial roles to develop relevant capabilities to address the current skills gap, to engage with personal and continuing professional development, and to advance their knowledge and application of leadership and management abilities. Developing capability beyond a technical role is central to sound leadership and management in all businesses, and particularly so in this area.

Core modules

Data Centre Leadership
Finance for Non-Financial Managers
Sustainable Design for High Capacity Data Centres
Data Centre Infrastructure Management, Security and Disaster Recovery
HRM and Organisational Capability Development
Decision Making in Critical Services
Contemporary Issues in Leadership and Management
Research Methods for Business and Management
Postgraduate Major Project

Assessment

You’ll be assessed through a range of written assignments, portfolio assessments and report work. You’ll be encouraged to explore the application of theoretical constructs to your own workplace through the use of contextualised assessments, online discussions, and tutor-lead activities.

- This is a 3 year programme
Please note that modules are subject to change and availability.

Your faculty

The Lord Ashcroft International Business School is one of the largest business schools in the East of England, with nearly 100 full-time teaching staff and approximately 6,000 students from more than 100 countries.

Our striking and award-winning business school building in Chelmsford, as well as new buildings in Cambridge, offer the most advanced learning technologies. We’re well-recognised for our centres of excellence by students, employers and professional bodies alike.

What makes us stand out is that our courses don't just give you sound academic knowledge – they’re at the cutting edge of current business practice and highly relevant to employers. This is owing to the close links we have with the business community and the partnerships we've developed with a wide variety of businesses and public service organisations.

We're interested in people who are confident, ambitious and ready to take the challenge of making a difference in the world of business. If that's you, we'd love to hear from you.

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Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Read more
Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.

In the Data Science master’s programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master’s programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.

Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to:
-Understand the general computational and probabilistic principles underlying modern machine learning and data mining algorithms.
-Apply various computational and statistical methods to analyse scientific and business data.
-Assess the suitability of each method for the purpose of data collection and use.
-Implement state-of-the-art machine learning solutions efficiently using high-performance computing platforms.
-Undertake creative work, making systematic use of investigation or experimentation, to discover new knowledge.
-Report results in a clear and understandable manner.
-Analyse scientific and industrial data to devise new applications and support decision making.

The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.

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

Programme Contents

The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through minor studies in the MSc programme, or it might already be part of your bachelor-level degree.

Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.

Minor studies give you a wider perspective of Data Science. Your minor subject can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).

Selection of the Major

You can specialise either in the core areas of data science -- algorithms, infrastructure and statistics -- or in its applications. This means that you can focus on the development of new models and methods in data science, supported by the data science research carried out at the University of Helsinki; or you can become a data science specialist in an application field by incorporating studies in another subject. In addition to mainstream data science topics, the programme offers two largely unique opportunities for specialisation: the data science computing environment and infrastructure, and data science in natural sciences, especially physics.

Programme Structure

You should be able to complete the MSc Programme in Data Science of 120 credits (ECTS) in two years of full-time study. The programme consists of:
-Common core studies of basic data science courses.
-Several modules on specific topics within data science algorithms, data science infrastructures and statistical data science, and on data science tools.
-Seminars and colloquia.
-Courses on academic skills and tools.
-Possibly an internship in a research group or company.
-Studies in an application domain.
-Master’s thesis (30 credits).

Career Prospects

Industry and science are flooded with data and are struggling to make sense of it. There is urgent demand for individuals trained to analyse data, including massive and heterogeneous data. For this reason, the opportunities are expected to grow dramatically. The interdisciplinary Data Science MSc programme will train you to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.

If you are focusing on the core areas of data science, you will typically find employment as a researcher or consultant, sometimes after taking a PhD in Computer Science or Statistics to deepen your knowledge of the field and research methods. If your focus is on the use of data science for specific applications, you will typically find work in industry or in other fields of science such as physics, digital humanities, biology or medicine.

Internationalization

The Data Science MSc is an international programme, with students from around the world and an international research environment. All of the departments taking part in the programme are internationally recognised for their research and a significant fraction of the teaching and research staff come from abroad.

The departments participate in international student exchange programmes and offer you the chance to include international experience as part of your degree. Data Science itself is an international field, so once you graduate you can apply for jobs in any country.

In the programme, all courses are in English. Although the Helsinki area is quite cosmopolitan and English is widely spoken, you can also take courses to learn Finnish at the University of Helsinki Language Centre. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning other languages.

Research Focus

The MSc programme in Data Science is offered jointly by three departments and two research institutes. Their research covers a wide spectrum of the many aspects of data science. At a very general level, the focal areas are:
-Machine learning and data mining
-Distributed computation and computational infrastructures
-Statistical modelling and analysis
-Studies in the programme are tightly connected to research carried out in the participating departments and institutes.

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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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We offer a suite of Masters programmes at Stirling. This is a one year, full time taught MSc. designed to lead to a job in data science or analytics. Read more

Introduction

We offer a suite of Masters programmes at Stirling.
This is a one year, full time taught MSc. designed to lead to a job in data science or analytics.
Big Data skills are in high demand and they attract high salaries. The MSc Big Data at the University of Stirling is a taught advanced Master's degree covering the technology of Big Data and the science of data analytics.
The course is taught in the beautiful Stirling campus in the heart of Scotland with support from companies who recruit data scientists.
The course covers Big Data technology, advanced analytics and industrial and scientific applications. The syllabus includes:
- Mathematics for Big Data
- Python scripting
- Big Data theory and computing foundations
- Big databases and NoSQL
- Analytics, machine learning and data visualisation
- Optimisation and heuristics for big problems
- Hadoop and MapReduce
- Scientific and commercial applications
- Student projects

Key information

- Degree type: MSc
- Duration: One year
- Start date: September
- Course Director: Kevin Swingler

Course objectives

- An understanding of the issues of scalability of databases, data analysis, search and optimisation
- The ability to choose the right solution for a commercial task involving big data, including databases, architectures and cloud services
- An understanding of the analysis of big data including methods to visualise and automatically learn from vast quantities of data
- An appreciation of the size of search spaces in large problems and the ability to choose an appropriate heuristic to find a near optimal solution
- The programming skills to build simple solutions using big data technologies such as MapReduce and scripting for NoSQL, and the ability to write parallel algorithms for multi processor execution.

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: 6.0 with 5.5 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade C
- Pearson Test of English (Academic): 54 with 51 in each component
- IBT TOEFL: 80 with no subtest less than 17

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 .

Structure and content

Our Big Data MSc is a mix of practical technology such as Hadoop, NoSQL, and Map-Reduce, important maths and computing theory, and advanced computational techniques. The course will teach you what you need to know to collect, manage and analyse big, fast moving data for science or commerce

REF2014

In REF2014 Stirling was placed 6th in Scotland and 45th in the UK with almost three quarters of research activity rated either world-leading or internationally excellent.

Strengths

Stirling is a member of The Data Lab, which is an Innovation Centre with the aim of developing the data science talent and skills required by industry in Scotland. The data lab with facilitate industry involvement and collaboration and provide funding and resources for students.
The Stirling MSc in Big Data has been developed in partnership with global and local companies who employ data scientists. HSBC have a development centre in Stirling and have provided some very interesting Big Data projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh. The course features a long summer project, generally in partnership with a company or technology provider, that provides students with a showcase of their skills to take to employers or launch online.
We also have a programme of invited speakers from industry who give the students a chance to ask questions of people who are doing data science every day. Recent companies have included MongoDB, SkyScanner and HSBC.

Career opportunities

Demand for people with big data skills is projected to grow rapidly in the coming years. Average salaries are higher in Big Data jobs than the IT average and the skills shortage will make that gap bigger.
The Stirling Big Data MSc is run in partnership with industry and is designed to produce graduates with the skills that companies need.
e-Skills UK estimate that:
- The number of Big Data jobs in the UK rose by 41% from 2012 - 2013
- By 2020 there will be 56,000 Big Data jobs in the UK alone
- Big Data professionals earn on average 31% more than other IT professionals
- 77% of companies say it is difficult to recruit people with the Big Data skill they need

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Take advantage of one of our 100 Master’s Scholarships to study Health Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Health Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Healthcare, with an already established strong relationship with Information & Communication Technologies (ICT), is continuously expanding the knowledge forefront as new methods of acquiring data concerning the health of human beings are developed.

Processing this data to extract valuable information about a population (epidemiological applications) or the individual (personalised healthcare applications) is the work of health data scientists. Their work has the potential to improve quality of life on a large scale.

Swansea University is the first institution in the UK to offer this taught master's programme in Health Data Science designed to develop the essential skills and knowledge required of the Health Data Scientist.

Key Features of the Health Data Science Programme

- A one year full-time taught master's programme designed to develop the essential skills and knowledge required of the Health Data Scientist.
- The Health Data Science course is also available for three years part-time study.
- An integrated programme of studies tailored to the essential skill set required for Data Scientists operating within healthcare organisations covering key topics in computation, data modeling, visualisation, machine learning and key methodologies in the analysis of linked health data.
- Hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment.
- Strong collaboration links with colleagues from the Centre for Health Services Research of the University of Western Australia, a group of leading experts in the analysis of linked health data.
- The Health Data Science course is based within the award winning Centres for Excellence for Administrative Data and eHealth Research of Swansea University, awarded by the Economic and Social Research Council (ESRC) and Medical Research Council (MRC), enhancing the quality of the course.

Who should study MSc Health Data Science?

The Health Data Science course is suitable for those working in healthcare with roles involving the analysis of health data and also computer scientists with experience in working with data from the healthcare domain, as well as biomedical engineers and other similar professions.

Course Structure

Students must complete 6 modules of 20 credits each and produce a 60 credits dissertation on a Health Data Science project. Each module of the programme requires a short period of attendance that is augmented by preparatory and reflective material supplied via the course website before and after attendance.

Attendance Pattern

Health Data Science students are required to attend the University for 1 week (5 consecutive days) for each module in Part One. Attendance during Part Two is negotiated with the supervisor.

Modules

Modules on the Health Data Science programme typically include:

Scientific Computing and Health Care
Health Data Modelling
Introductory Analysis of Linked Health Data
Machine Learning in Healthcare
Health Data Visualisation
Advanced Analysis of Linked Health Data

Professional Development

The College of Medicine offers the modules on the Health Data Science course as standalone opportunities for prospective students to undertake continued professional development (CPD) in the area of Health Data Science.

You can enroll on the individual modules for the Health Data Science programme as either an Associate Student (who will be required to complete the module(s) assessments) or as a Non-Associate Student (who can attend all teaching sessions but will not be required to complete any assessments).

For information and advice on applying for any of the continuing education opportunities, please contact the College directly at .

Employability

Postgraduate study has many benefits, including enhanced employability, career progression, intellectual reward and the opportunity to change direction with a conversion course.

From the moment you arrive in Swansea, specialist staff in Careers and Employability will help you plan and prepare for your future. They will help you identify and develop skills that will enable you to make the most of your postgraduate degree and enhance your career options. The services they offer will ensure that you have the best possible chance of success in the job market.

The student experience at Swansea University offers a wide range of opportunities for personal and professional development through involvement in many aspects of student life.

Co-curricular opportunities to develop employability skills include national and international work experience and study abroad programmes and volunteering, together with students' union and athletic union societies, social and leisure activities.

For the MSc Health Data Science course, we are in the process of identifying opportunities for our students to complete volunteering placements with a number of our collaborative partners.

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The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Read more
The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data.

If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, MSc Data Science at Essex is for you. You study a balance of solid theory and practical application including:
-Computer science
-Programming
-Statistics
-Data analysis
-Probability

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

You also benefit from being taught in our School of Computer Science and Electronic Engineering, who are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of their research rated ‘world-leading’ or ‘internationally excellent’ (REF 2014).

The collaborative work between our departments has resulted in well-known research in areas including artificial intelligence, data analysis, data analytics, data mining, data science, machine learning and operations research.

Our expert staff

Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

The academic staff in our School of Computer Science and Electronic Engineering 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 Paul Scott, who researches data mining, models of memory and attention, and artificial intelligence, and Professor Maria Fasli, who researches data exploration, analysis and modelling of complex, structured and unstructured data, big data, cognitive agents, and web search assistants.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We have six laboratories that are exclusively for computer science and electronic engineering students
-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
-You 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
-We host regular events and seminars throughout the year
-Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
-The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment

Your future

With a predicted shortage of data scientists, now is the time to future-proof your career. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course opens the door to almost any industry, from health, to government, to publishing.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Dissertation (optional)
-MSc Project and Dissertation (optional)
-Applied Statistics
-Machine Learning and Data Mining
-Modelling Experimental Data
-Text Analytics
-Artificial Neural Networks (optional)
-Bayesian Computational Statistics (optional)
-Big-Data for Computational Finance (optional)
-Combinatorial Optimisation (optional)
-High Performance Computing (optional)
-Natural Language Engineering (optional)
-Nonlinear Programming (optional)
-Professional Practice and Research Methodology (optional)
-Programming in Python (optional)
-Information Retrieval (optional)
-Data Science and Decision Making (optional)
-Research Methods (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)

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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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Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Read more
Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Whilst the amount of data grows, the science of gaining insights from this data grows with it. Industry, research institutions and government all seek to extract value from data to improve products and services, serve their customers better and run more operationally efficient organisations. Data Scientists use their mathematical, computational and presentational skills to mine data for value and their skills are highly sort after. There is a significant shortage of skilled Data Scientists and so there are many job opportunities available.

Course content
We have designed this MSc course in consultation with industry partners.

This has enabled us to understand their needs for Data Scientists, what skills will be required and on successful completion of this course individuals will be highly employable within businesses.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to these looking for a career in the Data Sciences.

The course will be of specific interest to :

A mathematics graduate wishing to use your skills in a vocational business based environment
A computer science graduate wishing to follow a vocational route
Individuals currently working in Business and looking to grow their career through gaining Data Science and Business Analytics skills
Six modules go to make up this MSc:

Data Science Foundation
Managing Data
Data Exploration and Analysis
Mathematics
Machine Learning & Cognitive Computing
Data Visualisation and Presentation
The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects.

You will be assigned a Personal Tutor from the start of your course who will work with you throughout your studies to help you achieve your academic best.

The knowledge we provide you with in these areas will give you all of the essential know-how on methods, tools and techniques to deliver in your career as a Data Scientist.

We believe Data Science is very much an intellectual ‘contact sport’ and through this course we provide you with every opportunity to put your theoretical knowledge into practice.

The project work we have imbedded within the course has been chosen and developed based on real-world scenarios across a range of industry and government sectors and is specifically designed to:

Provide an essential link between your theoretical learning and real-world challenges
Create an environment where you decide the methods and tools best suited to the challenge based on what you have learnt
Recreate some of the challenges facing industry and Government today and those very similar to what you will encounter in the workplace as a Data Scientist
Be adaptable to reflect new methods / tools and scenarios in this fast developing discipline
Be able upon completion of the projects to reference your experience in working with such challenges

Fees for 2017

Home fees - 1 year full-time: £8000.00

International fees: £10,920.00

Our facilities
You will undertake your workshops in training rooms that are bang up-to-date with design features, touch screen electronic white boards and high speed wifi; housed across three stunning Georgian mansions.

All of our current students love the learning environment, the culture, camaraderie and the fact that tutors know them by name so they are more than just a ‘face in the crowd’.

You will have access to the very best IT facilities in order to support your studies. These range from computer labs to access to cloud analytics from the leading providers.

We will use software from the academic programs of the major enterprise I.T. vendors such as IBM and Amazon as well as commonly used open source programs and frameworks.

From September 2018, many of the teaching sessions will take place in the purpose-built Engineering and Digital Technology building in the Bognor Regis campus.

What's more, you have lots of other facilities on this dedicated university campus including latest books, journals and online data in a truly modern library, an IT centre, a student zone complete with Costa Coffee, a gym and much more.

Where this can take you
The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations.

On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace perhaps in retail, banking, government or transport.

Indicative modules
Data Science Foundation (20 Credits)
Managing Data (20 Credits)
Data Exploration and Analysis (20 Credits)
Mathematics (20 Credits)
Machine Learning & Cognitive Computing (20 Credits)
Data Visualisation and Presentation (20 Credits)
Dissertation/Project (60 Credits)


Teaching and Assessment
Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following:

We place a lot of emphasis on course work related activity.
Opportunities to work with organisations on current commercial/business problems and projects. These experiences are used to provide the basis for assessments that enable you to apply your learning within authentic commercial situations.

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Data science provides a huge opportunity to harness new forms of data with increasingly powerful computer techniques which will increase operational efficiency, improve services and provide better insights for decision making and policy making. Read more
Data science provides a huge opportunity to harness new forms of data with increasingly powerful computer techniques which will increase operational efficiency, improve services and provide better insights for decision making and policy making.

Course overview

This newly developed Data Science course will provide you with the technical and practical skills to analyse big data that is key to success in future business, digital media and science.

Data science offers enormous opportunities for an insight into a range of domains, including: business, marketing, science and technology. Study industry-specific topics and specialise in areas such as data mining, machine learning, data analytics and visualisation, security of big data.

Our close links to industry and businesses in the North East, as well as the research expertise of our academics makes this course unique and ensures that the course structure is developed according to the needs of the employment sector. You’ll be taught by experts in: novel techniques for managing and discovering knowledge in big data and open data sets, using big data to address cybercrime, big data and cybersecurity and big data challenges in digital forensics.

The course is pending accreditation from the British Computer Society, the UK’s Chartered Institute for IT.

Course content

The course mixes taught elements with independent research and supportive supervision. At Masters level, responsibility for learning lies as much with you as with your tutor.

Modules on this course include:
-Research Skills and Academic Literacy (15 Credits)
-Big Data in Organisations (15 Credits)
-Data Science Fundamentals (30 Credits)
-Data Visualisation (15 Credits)
-Machine Learning and Data Mining (15 Credits)
-Data Analytics (15 Credits)
-Big Data Security (15 Credits)
-Master Project (60 Credits)

Teaching and assessment

We use a wide variety of teaching and learning methods which include lectures, group work, research, discussion groups, seminars, tutorials and practical laboratory sessions.

Compared to an undergraduate course, you will find that this Masters requires a higher level of independent working. Assessment methods include written reports and research papers, practical assignments and the Masters project.

Facilities & location

The course is taught at the David Goldman Informatics Centre, based at the Sir Tom Cowie Campus at St Peter’s, it looks out over the River Wear and is less than a mile from the seaside.

Sunderland offers one of the most modern and best equipped computing environments in the UK. The open-plan David Goldman Informatics Centre is equipped with over 300 computers, which are continuously upgraded and have attracted praise in an independent evaluation by the BCS.

Join an accredited Cisco Academy department and have access to laboratories fully equipped with Cisco networking equipment, including: routers, switches, terminals and specialist equipment for simulating frame relay and ISDN links.

Benefit from the Remote Global Cisco Academy and have access to our software whether you’re using the WiFi in our halls of residence or you’re at home.

We host high-performance computing platforms, including a Beowulf cluster and a grid distributed system, for concurrent processing of complex computational tasks. You can also access the equipment and licences for our own public mobile cellular network.
Access hundreds of PCs, Apple Macs, or the free WiFi zones across the campus and find the best place for you to study in our unique and vibrant learning space. The University is very diverse with a strong international presence and provides you with the opportunity to explore different cultures.

Study at a uniquely designed library and have access to more than 430,000 books, 9,000 electronic journal articles and benefit from a £1 million annual investment in new resources.

Employment & careers

Job trends data shows a 15,000% increase in the job prospects between 2011 and 2012, recognising big data as the ‘next big thing’ to revolutionise how we work, live and communicate (according to Indeed, 2016).

Progress in some of the most attractive fields and industries, including government agencies, high technology companies, consulting and market research firms.

Benefit from the University’s close links with businesses and employers in the North East and join an industry-driven programme.
Businesses and industries across the UK have identified a skills gap in data science and currently the role of a Data Scientist is one of the highest paid jobs in the computing discipline.

According to the McKinsey Report (2011), “the demand of people with data science skills is predicted to double over the next five years”.

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The Department of Computer Science at The University of Liverpool is delighted to announce the opportunity for Home and European students to receive industrial sponsorship to cover tuition fees for this programme. Read more
The Department of Computer Science at The University of Liverpool is delighted to announce the opportunity for Home and European students to receive industrial sponsorship to cover tuition fees for this programme. For more information visit our Postgraduate Funding Tool or contact Dr Martin Gairing.

The MSc in Big Data and High Performance Computing provides students with an in-depth understanding of big data analysis and processing using high performance computing technology. Run in conjuction with the STFC Hartree Centre, this MSc programme enables students to gain a specialist qualification in an area of computing that is in great demand worldwide.

Big data is commonly described as data that is so large that it cannot be readily processed using standard techniques. Our current global ability to collect data is such that “big data” sets are becoming common-place.

The most obvious example of this is the exponential growth of the World Wide Web; however there are many public and private enterprises where the analysis of large-scale data sets is critical to growth. Although significant computer power exists, the necessary skills-base is lagging behind the technology.

There is an employment gap looming in the field of big data, especially in the context of the skills required with respect to the application of High Performance Computing (HPC) capabilities to address big data problems.

The MSc in Big Data and High Performance Computing is designed to address this anticipated skills gap and provide those completing the programme with the necessary abilities (abilities which will be highly desirable within the employment market) to address big data centric problems in the context of HPC.

The programme has been designed and operates in close collaboration with the Hartree High Performance Computing Centre and focuses on the practical application of Big Data and HPC technology.

The Hartree centre is underpinned by £37.5 million of Government investment and hosts the UK’s premier supercomputing environment. This partnership provides a unique and unrivalled MSc programme and ensures that students completing the programme have a ready route into employment, facilitated by commercial contacts provided as part of the individual project.

You may also be interested in our Big Data Management MSc, Geographic Data Science MSc and Risk and Uncertainty MSc. For more information visit http://www.liverpool.ac.uk/study/postgraduate

The programme is organised as two taught semesters followed by an individual project undertaken over either the summer or, if desired, during the following year of study. Within each semester students study a number of modules adding up to 60 credits per semester (120 in total). This will be followed by a project dissertation, also 60 credits, making an overall total of 180 credits.

Why Computer Science?

Excellent partnerships

The MSc in Big Data and High Performance Computing programme has been developed, and operates, in close collaboration with the STFC Hartree Centre at Daresbury. The Hartree centre is underpinned by £37.5 million off Government investment and hosts the UKs premier supercomputing environment. The Department of Computer Science at Liverpool provides for a wide range of Big data, HPC and related skills and experience. This partnership means that this programme is unique and unrivalled. The partnership also ensures that students completing the programme have a ready route into employment facilitated by commercial contacts provided as part of the individual project element of the programme, which will in most cases is conducted with respect to real commercial requirements.

State of the art teaching and research

MSc Students who pursue their postgraduate study within the Department of Computer Science at the University of Liverpool will be an integral part of a department that is internationally renowned for its advanced research and teaching. The Department came seventh nationally in the 2008 research assessment exercise.

The Department of Computer Science is organised into four main research groups:

Agents
Algorithmics
Logic and Computation
Economics and Computation
Together these groups provide a critical mass of expertise equal to the most complex challenges in Computer Science, within a setting that offers world-class research facilities and support.

Teaching

You will be taught by lecturers who are internationally known for their research. The MSc in Big Data and High Performance Computing is offered full-time on-campus.

The taught components of the programme offer a choice of contemporary computing topics, a strong theoretical basis and the opportunity to gain sound practical and critical analysis skills. The programme can be taken in the form of a single year (12 months) of study with the individual project being undertaken over the summer months, or alternatively the project can be undertaken in the following academic year.

The computing resources include an extensive integrated network of workstations running the Linux operating system and the X-Windows graphical interface, together with a large number of PCs running Microsoft Windows. Staff and students have easy access to high quality laser printing facilities and a range of specialist software.

Career prospects

The MSc in Big Data and High Performance Computing (HPC) is specifically designed to fill a "skills gap" in the employment market. More specifically it is designed to provide students with the necessary skills to allow them to apply Big Data and HPC concepts to real problems. The programme has been structured to facilitate the practical application of this "cutting-edge" technology to real-world problems. The intention is that at the end of the programme students will be able to apply the knowledge gained on the programme specifically to real-world big data and HPC problems. However, the programme is also designed to furnish students with a set of transferable skills that are of particular relevance across the IT industry.

The programme has been developed, and is delivered, in close collaboration with the Hartree Centre at Daresbury which operates the UK's largest supercomputer (capable of a thousand trillion calculations per second). Hartree have close links with industry, and provide assistance with respect to the group and final individual projects, the latter conducted in partnership with commercial and/or non-commercial organisations.

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Our Big Data in Culture & Society MA recognises the growing importance of Big Data in contemporary society and addresses the theory and practice of Big Data from an arts and humanities perspective. Read more
Our Big Data in Culture & Society MA recognises the growing importance of Big Data in contemporary society and addresses the theory and practice of Big Data from an arts and humanities perspective.

What is Big Data? Beyond the unprecedentedly large data sets that can be analysed to reveal patterns, trends, and associations, it is increasingly about our everyday lives. In short, it is about how the data we generate is transforming social, cultural, political and economic processes as well as the generation of knowledge.

This course is likely to appeal to a broad range of students across the Arts and Humanities from Sociology to Political Science to English to Business and beyond. It will attract forward-thinking students interested in emerging trends who recognise that data scientists and analysts require collaborators with domain specialisation and critical insights.

Key benefits

- Taught by scholars working at the leading edge of digital studies and big data

- Offers a lively mix of theory and practical work

- Equips students with skills that are highly attractive to employers in our digital age

- Provides a series of workshops with data scientists and analysts to learn collaborative practices and applications in social media and cultural analytics, mobile platforms, and data visualization

- Is at the forefront of digital developments - Big Data is transforming society, politics, the economy and culture and impacting work

- Offers innovative interdisciplinary methods of study crossing technological and cultural perspectives

- Links Big Data to Culture, Law & Ethics, Geography, Public Health, and Social Life

- Located in a highly ranked department - the Digital Humanities department was ranked first in the UK for research power (2014 Research Excellence Framework)

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/big-data-in-culture-and-society-ma.aspx

Course detail

- Description -

The MA Big Data in Culture & Society will cover domain knowledge and data technique and practices which augment services across sectors. In addition to the core content covered by the programme, across the areas of specialisation, our students will have the opportunity to do an internship and a group project module, providing them with key skills going into the job market.

The programme will provide:

- Knowledge and understanding of the effects of Big Data on contemporary society
- Critical and theoretical approaches to the analysis of Big Data
- Knowledge of the historical antecedents of Big Data
- Understanding of the innovative methods for generating new knowledge through the use and analysis of Big Data
- Big Data in relation to the broader study of digital culture, the digital humanities and traditional humanities disciplines
- Understanding of appropriate personal and professional conduct in the context of digital culture as an emerging discipline

- Course purpose -

The MA Big Data in Culture and Society offers students the opportunity to develop their knowledge and understanding of the role of Big Data in culture and society. It enables them to analyse Big Data across social, political and economic areas and provides them with a background for pursuing careers in Big Data by bringing together domain knowledge and technical skills.

- Course format and assessment -

- 120 credits from taught modules assessed by essays and project reports
- 60 credits from individual dissertation supervised by staff member
- Full time study – typically 6 hours of taught classes per week
- Part time study – typically 3 hours of taught classes per week
- Dissertation – 15,000 words working with dedicated member of academic staff
- Modules assessed through coursework essays, workshop projects, reports, oral presentations and through participation in seminars
- Part Time study 60 credits in year 1 and 120 credits in year 2

Career prospects

Career paths will be quite broad and are likely to be in social media management, analytics & website management, CRM management, digital advertising, metrics management, market research, marketing, and across cultural industries.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 21 universities worldwide (2016/17 QS World University Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

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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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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

Research profile

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

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

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

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

A short sample of our research interests includes:

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

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

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

Training and support

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

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

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

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

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

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

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

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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This is a challenging one-year taught Master’s degree programme that provides students with a range of advanced topics drawn from communication networks (fixed and wireless) and related signal-processing, including associated enabling technologies. Read more
This is a challenging one-year taught Master’s degree programme that provides students with a range of advanced topics drawn from communication networks (fixed and wireless) and related signal-processing, including associated enabling technologies. It provides an excellent opportunity to develop the skills needed for careers in some of the most dynamic fields in communication networks.

This programme builds on the internationally recognised research strengths of the Communications Systems and Networks, High Performance Networks and Photonics research groups within the Smart Internet Lab. The groups conduct pioneering research in a number of key areas, including network architectures, cross-layer interaction, high-speed optical communications and advanced wireless access.

There are two taught units related to optical communications: Optical Networks and Data Centre Networks. Optical Networks will focus on Wavelength Division Multiplexed (WDM) networks, Time Division Multiplexed (TDM) networks including SDH/SONET and OTN, optical frequency division multiplexed networks, and optical sub-wavelength switched networks. Data Centre Networks will focus on networks for cloud computing, cloud-based networking, grid-computing and e-science. There is a further networking unit: Networked Systems and Applications, which provides a top-down study of networking system support for distributed applications, from classical web and email to telemetry for the Internet of Things.

The programme is accredited by the Institution of Engineering and Technology until 2018, one of only a handful of accredited programmes in this field in the UK.

Programme structure

Your course will cover the following core subjects:

Semester One (40 credits)
-Communication systems
-Digital filters and spectral analysis
-Mobile communications
-Networking protocol principles

Semester Two (80 credits)
-Data centre networking
-Advanced networks
-Broadband wireless communications
-Networked systems and applications
-Engineering research skills
-Optical communications systems and data networks
-Optical networks

Project (60 credits)
You will carry out a substantial research project, starting during Semester Two and completed during the summer. This may be based at the University or with industrial partners.

Careers

This one-year MSc programme gives you a world-class education in all aspects of current and future communication networks and signal processing. It will prepare you for a diverse range of exciting careers - not only in the communications field, but also in other areas such as management consultancy, project management, finance and government agencies.

Our graduates have gone on to have rewarding careers in some of the leading multinational communications companies, such as Huawei, China Telecom, Toshiba, China Mobile and Intel. Some graduates follow a more research-oriented career path, with a number of students going on to study for PhDs at leading universities.

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