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Masters Degrees (Big Data)

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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.

  • 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 visualisation.
  • 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)

Description

This Big Data in Culture & Society MA offers you the opportunity to develop your knowledge and understanding of the role of Big Data in culture and society. It will enable you to analyse Big Data across social, political and economic areas. In addition to the required content we cover, you will have the opportunity to pursue your own academic interests through our optional modules and to undertake an internship and a group project module.

By bringing together domain knowledge and technical skills and approaching these from an Arts and Humanities perspective, the course will help you develop highly valued employment skills and expertise for careers in Big Data.

The course will provide you with:

  • 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.
  • Understanding of 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

Teaching

If you are a full-time student, we will provide you with 120 to 180 hours of teaching through lectures and seminars across the year. We expect you to undertake around 1,674 hours of independent study.

If you are a part-time student, we’ll provide you with 90 hours of teaching through lectures and seminars in your first year, and 50 hours in your second. We’ll expect you to undertake 720 hours of independent study in your first year and 954 hours in your second.

Typically, one credit equates to 10 hours of work.

Assessment

We assess our modules entirely through coursework. This will comprise a mixture of essays, project work, and workshop reports, depending on the modules you choose.

Regulating body

King’s College London is regulated by the Higher Education Funding Council for England.

Career prospects

Our graduates will follow a broad range of career paths. The skills you develop are likely to be particularly transferable to work in social media management, analytics & website management, CRM management, digital advertising, metrics management, market research, marketing and across cultural industries.

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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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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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Embark on a career in a leading-edge field and master the exciting and challenging world of big data!. Big data techniques are revolutionising how organisations and industries acquire and analyse data, offering valuable insights into how people live, work, play, travel, shop and exercise. Read more

Embark on a career in a leading-edge field and master the exciting and challenging world of big data!

Big data techniques are revolutionising how organisations and industries acquire and analyse data, offering valuable insights into how people live, work, play, travel, shop and exercise. These insights are valuable to marketers, researchers, designers, city planners, app developers, educators and many more.

GCU's MSc in Big Data Technologies helps students build the fundamental knowledge and practical skills for success in this fast-growing field. You'll develop competence in a range of emerging technologies: big data, cloud computing and the internet of things. You'll learn from the experts; GCU is internationally recognised for the strength of its research in these exciting subjects, driving 21st century innovation.

With both full-time and part-time study available, the programme is ideal for someone with a background in computer science, software engineering, web technologies or computer engineering who wants to enhance or update their skills. Those with backgrounds in mathematics and electronics are also well suited.

The up-to-date curriculum keeps a career-focused approach, so you'll gain valuable skills you can immediately put to work in the industry.

  • Apply leading-edge tools and technologies from companies such as IBM, Microsoft and SAS
  • Explore industry-standard open-source development platforms such as Hadoop
  • Achieve industry recognition with SAS joint certification in the programme's Data Analytics module

Your expertise in big data will enable you to provide new insights into human behaviour and psychology, which can help us build stronger and happier societies across the globe. Your work could shape smart, sustainable cities; remove barriers to education; help people make healthier choices day-to-day; improve public health… and so much more. All meaningful ways of contributing to the common good.

What you will study

Full-time students complete six taught modules; three in trimester A and three in trimester B and an MSc dissertation project in trimester C. Part-time students complete six taught modules; three in Year 1, three in Year 2and an MSc project in Year 3.

Cloud Computing and Web Services

This module provides analytical and practical coverage of cloud computing and web services. It focuses on the technology, frameworks and associated standards: cloud models, cloud platforms and scalability. It also provides coverage of current web service technology and data transport representations, and integrated cloud and web service application development. Current examples from industry technology are used throughout.

Big Data Landscape

This module covers the process of managing Big Data throughout its lifecycle, from requirements through retirement. The lifecycle crosses different application systems, databases and storage media. Students will gain an understanding of the full Big Data value chain. They will be able to analyse the challenges and opportunities associated with the different stages that Big Data passes through.

Data Analytics

This module covers the basic concepts of statistics needed to understand the critical concepts of data mining, machine learning and predictive analytics used in the visualisation and analysis of data, particularly Big data. Students will gain an understanding of data preparation, the process models used in analytics, the algorithms and their requirements, the implementation of these algorithms using current technologies, and their applicability to different types of scenario. They will also gain advanced practical skills in the design, implementation and evaluation of analytical solutions to problems involving Big Data.

Big Data Platforms

This module covers the platforms that support data storage, processing and analytics in Big Data scenarios. It focuses on highly scalable platforms that provide operational capabilities for real-time, interactive processing and on platforms that provide analytical capabilities for retrospective, complex analysis. Students will gain an advanced understanding of the principles on which these platforms are based, and their strengths, weaknesses and applicability to different types of scenario. They will also gain advanced practical skills in the design and implementation of scalable Big Data platform solutions.

Internet of Things

This module provides fundamental and practical coverage of the set of converging technologies known as the Internet of Things (IoT). It focuses on representative IoT applications, technologies, frameworks and associated standards that support and underpin IoT applications, such as sensor networks, messaging protocols, security, data storage, analytics, services and human interaction. The module provides in-depth practical coverage of representative IoT implementation frameworks including cloud-based service delivery models.

IT Professional Issues and Project Methods

This module seeks to develop understanding and practical skills in advanced project methods which are inline with industry regulations, standards and practices and are applicable to complex IT projects. Study is undertaken in an integrated fashion to ensure that the professional frameworks within which such projects are developed, deployed and managed are fully understood.

Masters Dissertation

Students will investigate a topical or emerging theme in Cloud Computing or related technologies. The dissertation acts as a vehicle for extending the knowledge and understanding of the student and the technical community in some specialist technical area. It serves through its length, complexity and rigour as a suitable vehicle for extending students' range of personal, interpersonal and communication skills. In addition it serves to develop and extend a range of high-level thinking skills, including analysing and synthesising skills and affords the opportunity for the student to demonstrate initiative and creativity in a major piece of technical work.

Work placements

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment methods

The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Graduate prospects

When you graduate, you'll be a competitive candidate for roles as a systems developer, architect or administrator in data and analytics. You'll find opportunities in a diverse range of industries: engineering, pharmaceuticals, finance, healthcare, retail, security, smart environments and more.



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The modern world is experiencing a growth of online data in a variety of forms, including social networks, web documents, digital libraries, blogs, medical records, biological data, remote sensing, imaging, forecasting etc. Read more
The modern world is experiencing a growth of online data in a variety of forms, including social networks, web documents, digital libraries, blogs, medical records, biological data, remote sensing, imaging, forecasting etc. This data may not be fully structured but still contains valuable information that needs discovering, such as emerging opinions in social networks, consumer purchase behaviour, trends from search engines, and other patterns that emerge from such huge data sources.

These developments mean traditional applications are no longer appropriate to the processing and analysis of the amount of data available. Companies, such as Google, are leading the movement from a large-scale relational database reflecting the desire to analyse data automatically and on a larger scale than previously seen.

Course content

The course is designed to respond to critical skill shortages in the rapidly expanding field of Big Data. It offers a balance of practical skills combined with academic rigour in the field of Big Data. This is a unique offering which builds on the strengths and experience of Staffordshire University in delivering practical scholarship relevant to real world situations.

It is intended to assist students and career professionals enter and succeed in the growing, high demand analytics workforce. The course recognises and acknowledges the changing patterns in study including the growing demand for extended and distance learning modes of study and builds on the many years of experience the faculty has of delivering these modes.

As a full time student, you would study in the first semester:
-Managing Emerging Technologies
-Data Harvesting and Data Mining
-Distributed Storage
-Distributed Processing

This first semester is concerned with those areas of big data fundamentals and is used to examine how big data is stored, processed and how an organisation can start to use tools to examine this data and start to improve businesses awareness of its customer base.

In the second semester you will study:
-Research Methods
-Virtualisation
-Big Data Applications
-Data Modelling and Analysis

This semester encompasses a module on how to manage big data within a network, a maths module on algorithms that are required to enhance big data and a module which will prepare you for the master project in the last semester. The last module will examine existing big data applications that can help get the most out of big data.

The final semester is a major research project. The actual content is open to discussion with the award leader and project supervisor must be a discipline related to Big Data.

On completion of the award you will have developed detailed knowledge and understanding of Big Data and the ability to apply this knowledge in an academic or commercial context.

The award also aims to instil sound academic & professional skills required for lifelong learning & development - for example, skills in research methods, critical thinking & analysis, academic and professional report writing, and communication skills.

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Recent technological advances decreasing hardware costs and the ‘Internet of things’ has led to a rapid explosion in the amount of data generated in a variety of domains, including data-driven science, telecommunications, social media, large-scale e-commerce, medical records and e-health. Read more

Recent technological advances decreasing hardware costs and the ‘Internet of things’ has led to a rapid explosion in the amount of data generated in a variety of domains, including data-driven science, telecommunications, social media, large-scale e-commerce, medical records and e-health. Big data refers to the ability of exploiting these massive amounts of extremely heterogeneous in structure and content data that are routinely generated at an unprecedented scale from an ever-expanding variety of data sources. Business and industry used their big data to extract a better understanding of customers’ needs and behaviour, to develop targeted new products and to cut operational costs. The competitive advantages and productivity gains that big data brought led to a great number of a big data projects and a shortage of people with the required skills.

This course is aimed at people who want to move into this rapidly expanding and exciting area; it has a strong vocational flavour as it has been designed to build your knowledge and understanding of big data systems architectures and to equip you with the range of highly marketable, hands-on skills employed by the core technologies utilised in big data projects.

The course is suitable for recent graduates who wish to study for a higher qualification and/or gain technical and professional skills related to the use of big data technologies and/or data management. It's also suitable for practitioners looking to update their knowledge and technical skills in this highly prominent discipline.

The course addresses technologies, advanced theories and techniques, along with their application, implementation and integration with legacy systems. You will analyse new demands and the application of technologies in the management of data and information resources, and examine big data technologies shaping the way data is now stored and utilised including the use of cloud stored massive datasets, distributed systems of an enterprise and how data utilisation can change and improve business processes.

Teaching approaches include lectures, tutorials, seminars and practical/hands on sessions. You will also learn through extensive course work, class presentations, group work, and the use of a range of industry standard software such as R, Python, Hadoop, MySQL, and Oracle. Assessment usually involves a combination of exams and coursework, leading to a product such as a presentation, group investigation, technical solution, a piece of software or a research review.

Professional accreditation

This programme is accredited by BCS, The Chartered Institute for IT, for fully meeting the further learning educational requirement for Chartered IT Professional (CITP) status and for partially satisfying the underpinning knowledge requirements set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC) and the Science Council for Chartered or Incorporated Engineer (CEng or IEng) status. Note that there are additional requirements, including work experience, to achieve full CITP, CEng, or IEng status. Graduates of this accredited degree will also be eligible for professional membership of BCS (MBCS).

The BCS accreditation is an indicator of the programme’s quality to students and employers; it is also an important benchmark of the programme’s standard in providing high quality computing education, and commitment to developing future IT professionals that have the potential to achieve Chartered status. The programme is also likely to be recognised by other countries that are signatories to international accords.

Associated careers

The course equips you with the technology knowledge and the highly sought hands on/practical skills for a successful career in big data application domains. Graduates of the programme are expected to find employment as developers, analysts, architects of big data systems, database/web application developers, data compliance officers, data quality officers, data governance officers, data governance analysts, OLAP programmers, ETL programmers and application developers, specialists in data acquisition, knowledge/information extraction, data analysis, data aggregation, data representation.



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Gain the skills and knowledge to truly capitalise on the potential of big data and analytics. Boost your ability to integrate and deploy data-driven solutions that help build competitive advantage. Read more

Gain the skills and knowledge to truly capitalise on the potential of big data and analytics. Boost your ability to integrate and deploy data-driven solutions that help build competitive advantage. Develop your confidence in the practical application of the latest big data analytics tools, and use our innovative learning environment to study online from anywhere in the world.

“The best part of online study with the University of Liverpool was the teamwork with people from around the world.”

George Bagropoulos (Greece) IT graduate

Unlock the power of big data to drive business strategy

This 100% online master’s programme gives you the opportunity to:

  • Acquire a practical understanding of big data analytics and how it can empower organisations to become more effective, efficient and competitive.
  • Advance your potential career potential by acquiring a comprehensive and demonstrable understanding of big data and analytics tools and techniques.
  • Get hands-on experience of big data management frameworks and the ecosystems that can be used to support advanced data analytics.
  • Equip yourself with the tools and methods used in data mining, including data pre-processing, to generate a systematic understanding of the end-to-end process.
  • Create data warehouses using data from multiple sources and use state-of-the-art data visualisation technology to ‘tell a story’.
  • Analyse and understand the practical challenges of integrating and deploying big data management systems.
  • Demonstrate your skills in big data analytics and data-driven decision making to current or future employers via an e-portfolio of IT artefacts.

Grow with one of the world’s leading universities

The University of Liverpool is ranked in the top 1% of universities worldwide1 and is a member of the prestigious Russell Group of research-led British universities.

The 2014 Research Excellence Framework rated 97% of the research produced by the University’s Department of Computer Science as world-leading or internationally excellent – among the highest ratings of computer science department in the UK.

The University has developed an innovative, cloud-based server platform to allow online IT students to develop practical skills in an environment that mirrors real-world IT workspaces.

Careers

Study a master’s programme that puts you at the forefront of new, in-demand technologies. Position yourself to move into senior data or analytics roles2 such as:

  • Director of Analytics
  • Director of Business Analytics
  • Manager of Business Analytics
  • Director of Business Intelligence
  • Analytics Manager
  • Senior Big Data Engineer

1 As listed in the International Handbook of Universities, published by the International Association of Universities (2014).

2 Career options may require additional experience, training or other factors beyond the successful completion of this degree programme.



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Our MSc Big Data course addresses the growing importance of big data in business, and society at large. International Data Corporation (IDC. Read more

Our MSc Big Data course addresses the growing importance of big data in business, and society at large.

International Data Corporation (IDC: a market research firm) forecast that the Big Data technology market will grow at a 26.4% compound annual growth rate (CAGR) to £28.79 billion by 2018 – approximately six times the growth rate of the overall information technology market; with 30% organizations collecting big data and/or the market of data driven services.

Our modules will prepare you to make notable contributions in modern day organizations with Big Data technologies. Equipped with necessary knowledge and hand-on experience you will enhance your employability within UK and internationally.

Unique and challenging modules are introduced, including Mobile networks and smartphone applications, Data mining and visualisation in addition to Ethics for IT professionals and Object oriented analysis and design that provide the foundation for Big Data.

Course Details

You will study the latest trends and technologies in Big Data in the following modules together with a Master's dissertation to obtain the MSc degree:

  • Mobile Networks and Smartphone Application
  • Data Mining and Visualization
  • Ethics for IT professionals
  • Object Oriented Analysis & Design
  • Research Design and Methods
  • Emerging Topics in Smart Networks
  • Advanced Data Science*
  • Intelligent Systems*

*Specialist modules

Teaching & Assessment

All modules are designed to respect the themes of Big Data, delivering research informed teaching via:

  • Lectures
  • Tutorials
  • Laboratory sessions

Our assessment methodology is influenced by the learning outcomes to be tested and employs a range of methods including:

  • essays
  • reports
  • strategic planning proposals
  • critical incident analysis
  • projects
  • research proposal
  • dissertation

Career Prospects

Jobs

Examples of jobs available to you upon graduation include:

  • Data analysts
  • Data scientists
  • Data mining analysts
  • Technical developer
  • Project manager in Big Data

Salaries in these roles range from £30,000 to £75,000.

Further Study

Successful completion of our course prepares you for advanced research studies in related technology areas. You will have the priority to be admitted to the MPhil/PhD degree courses.



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The Big Data in Business pathway will provide you with the knowledge and skills to understand and direct the strategic use of the vast amounts of information being generated by businesses today. Read more

The Big Data in Business pathway will provide you with the knowledge and skills to understand and direct the strategic use of the vast amounts of information being generated by businesses today.

Commercial focus

Our students learn to develop a strategic approach to managing Big Data in business, through the analysis of business problems as well as understanding different approaches to business intelligence. Through this, they are able to create usable business intelligence to create competitive advantage for their organisation.

After you’ve graduated

Our graduates have will leave us with the knowledge and skills necessary to analyse and manage Big Data to benefit business in a variety of sectors.

Not sure which pathway to choose from 3 choices? Apply for the one that you feel fits you better and you will be able to change the pathway within the first few weeks from your arrival to the university.

Why Henley?

  • Consistently maintain highest standards: Henley is in top 1% of business schools worldwide to hold accreditation from all three bodies in the UK, Europe and US
  • Excellent networking potential : 72,000 Henley alumni members in 150 countries
  • High calibre students: always oversubscribed, 1,000 ambitious new Masters students join Henley each year
  • Award winning campus: beautiful, green, 134 hectares, with state of the art facilities
  • World-leading faculty: widely published, frequently asked for expert comment by media and to speak at events
  • Henley is proud to be part of the University of Reading. The University is ranked within the top 200 universities worldwide (Times Higher Education World University Rankings 2016/17 and QS World University Rankings 2018) and 98% of the research is rated as being of international standard.

Course content

Compulsory modules

Optional modules

In addition students must choose two optional module from the list below.

Please note there is no guarantee that in any one year all modules will be available. 

How we teach you

A holistic approach

Effective leadership requires more than first-class business acumen. It also requires a degree of self-awareness and sensitivity. Henley is renowned for its well-researched, professional approach to this aspect of business education and all our postgraduate programmes examine this aspect of leadership - helping to create emotionally intelligent graduates who can be fully effective in their chosen careers.

How you will learn

Henley Business School enjoys a strong reputation for the practical application of business ideas and concepts, underpinned by academic excellence and the strength of our research. We offer high-quality technical skills training as well as a deep understanding of the importance of personal development for leaders, a thread that runs through all of our Masters programmes.

Our postgraduate masters programmes feature a mix of core and optional modules, allowing you to tailor your degree towards your individual personal development needs and career ambitions. You will complete up to 10 taught modules during your programme, totalling 180 credits. One module usually equates to 20 credits or 10 hours of work per week. Your week will include lectures, tutorials, workshops and personal study, with each accounting for 25% of your time on average. This stimulating mix of lectures and interactive tutorials provides you with the opportunity to discuss and explore the subject material in depth with your lecturers and fellow students. You will be introduced to the latest thinking and research findings and be able to challenge some of those that have created it. You will also explore real-world issues and tackle current business challenges, and interact with guest lectures and speakers from industry, giving you the opportunity to test, extend and refine your knowledge and skills.

How we assess you

You will learn and be assessed through a wide variety of teaching methods which vary depending on your chosen Masters programme. These include online materials and multimedia content, guest lectures, individual and group assignments, case studies, field visits, dealing room simulations, presentations, applied projects, consultancy work and examinations.

On average examinations form around 70% of the assessed work with the remaining 30% coming from coursework, including a written dissertation or project depending on your chosen programme. The exam period falls between April and June in the summer term, with students taking an average of 5 or 6 exams. Graduation normally takes place in December.

Ongoing support

While postgraduate students are self-motivated and determined individuals, study at this level can present additional pressures which we take seriously. Lecturers are available to discuss the content of each module and your personal tutor can meet with you regularly to discuss any additional issues. Full-time support staff are also available to help with any questions or issues that may arise during your time at Henley

Careers and accreditations

Each pathway of our MSc Information Management is designed to give a rigorous academic understanding of real-life and current business issues. Graduates of the Big Data in Business pathway will be equipped to develop strategies to manage Big Data. These skills are much in demand, in a variety of fields.  

A number of our students join our PhD programmes each year.

Students who pass the module – Business Domain and Requirements Analysis with a mark of 60 or above will be eligible for the British Computer Society Professional Certificate in Business Analysis Practice.



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Institute for Digital Technologies. The. Institute for Digital Technologies. aims to address major technological challenges, with a focus on Big Data, Interactive and Creative Media, Cyber Security, Smart Living, Green Digital Technologies, and Advanced 5G Systems. Read more

Institute for Digital Technologies

The Institute for Digital Technologies aims to address major technological challenges, with a focus on Big Data, Interactive and Creative Media, Cyber Security, Smart Living, Green Digital Technologies, and Advanced 5G Systems.

Renowned for its teaching and research excellence, the Institute for Digital Technologies has built strong collaborations with national and international academic, research, and industrial organisations including Thales, BBC, Telefonica, IRT, and Rohde & Schwarz.

Each programme offers teaching from pioneering researchers and creative innovators, to expose students to the latest theories and developments from across the discipline. Our programmes are shaped by the principles and discoveries of our current research, and students are encouraged to participate in development projects and industry-focused work experience opportunities where possible.

For further information, see our programme page for Cyber Security and Big Data MSc

This programme

This programme aims to provide students with the very latest Cyber Security and Big Data principles, practices, tools, and techniques through analysing and evaluating practical application problems in the Cyber Security and Big Data industry and responding to important challenges the world is facing.

Our students will have a comprehensive understanding of the challenges in Cyber Security and Big Data faced by industry and society and the necessary skills to address those challenges in the most effective way. Our programme is designed to build students’ knowledge and develop their expertise in network security, cryptography, data science, and big data analytics through action-based learning, analysis and evaluation of application problems.

An essential element built in the programme is to develop our students’ employability skills that are essential to the Cyber Security and Big Data industries or related businesses, e-commerce, and governmental organisations.

Your personal development

Enterprise Through the Curriculum is an intrinsic element of every master’s programme at Loughborough University London and has been carefully designed to give students the best possible chance of securing their dream role. From employability profiling to live group projects set by a business or organisation, and from site visits to organisation-based dissertation opportunities, Loughborough University London is the first of its kind to develop a suite of activities and support that is positioned as the underpinning of every student’s experience.

Future career prospects

Our graduates will be in a very strong position to take on digital technology posts in a wide range of sectors, including Internet and cloud based businesses, finance firms, governmental organisations, consultancy companies operating in information, communication and network security, as well as those sectors dealing with massive personal data, such as health and wellbeing, where users’ privacy and data security needs safeguarding.

Graduates will also have the opportunity to enhance their knowledge and career prospects further by undertaking an MRes or PhD programme.

Speak to a programme specialist

If you'd like to know more about this programme, you can request an email or telephone call from an academic responsible for the teaching of this programme.

Complete the contact request form

Scholarships for 2018 entry

Our ambition is to inspire high achieving students from all backgrounds, to benefit from our outstanding teaching and cutting edge research facilities.

Inspiring Success Scholarship

The Inspiring Success Scholarship offers 100% off the full cost of tuition fees for selected unemployed and underemployed graduates, who obtained GCSE or A-level (or equivalent) qualifications from Hackney, Tower Hamlets, Newham or Waltham Forest.

East London Community Scholarship

The East London Community Scholarship offers 50% off the full cost of tuition fees for students who obtained GCSE or A-level (or equivalent) qualifications from Barking and Dagenham, Greenwich, Hackney, Newham, Tower Hamlets or Waltham Forest.

Excellence scholarship

The Excellence scholarship automatically awards high-achieving students 20% off the full cost of our master’s tuition fees, regardless of their full-time programme or nationality. To be eligible for this scholarship, students must have an upper-second class degree or equivalent qualification recognised by Loughborough University.

Alumni Bursary

The Alumni Bursary automatically awards graduates of Loughborough University 10% off the full cost of our master's tuition fees, regardless of their full-time programme or nationality.

Further details about the full range of scholarships we offer are available on our website.



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Why this course?. This masters degree programme will allow you to select leading classes that span the breadth of both computer and information sciences, including theoretical computer science, human-computer interaction, information sciences, software engineering, machine learning and big data. Read more

Why this course?

This masters degree programme will allow you to select leading classes that span the breadth of both computer and information sciences, including theoretical computer science, human-computer interaction, information sciences, software engineering, machine learning and big data.

You’ll study

You'll gain an understanding of the new challenges posed by the advent of the big data revolution, particularly in relation to its modelling, storage, and access. You'll also come to understand the key algorithms and techniques embodied within data analytics solutions, and be exposed to a number of different big data technologies and techniques, seeing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts.

You'll learn key technologies that are at the heart of big data analytics such as NoSQL databases and Hadoop and the Map-Reduce programming paradigm. You will also be equipped with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how and when to apply these.

You will also have the opportunity to implement and experiment with these machine learning algorithms using the most popular languages such as R and Python, and explore their applications to areas as diverse as analysing activity-related data captured using a smartphone to financial time-series prediction.

Individual project/dissertation

You’ll take on an individual research project on an approved topic related to your selected pathway. You’ll pursue a specific interest in further depth, giving scope for original thought, research and technical presentation of complex ideas.

Learning & teaching

Teaching methods include lectures, tutorials and practical laboratories. Dissertation is by supervision.

You’ll also have the opportunity to meet industry employers and participate in recruitment events.

Careers

Opportunities for graduates of the MSc Advanced Computer Science with Big Data exist in industries ranging from finance, films and games, pharmaceuticals, healthcare, consumer products and public services to dedicated IT organisations.

Future career options will include:

  • big data analyst
  • software engineer
  • big data
  • software engineer
  • data scientist
  • data consultant


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Cloud computing is revolutionising the way that large, and often complex, datasets are stored and analysed. Our course aims to produce experts in cloud computing and big data required by academia and industry. Read more

Cloud computing is revolutionising the way that large, and often complex, datasets are stored and analysed. Our course aims to produce experts in cloud computing and big data required by academia and industry.

The MRes can only be applied for as part of the four-year (MRes plus PhD) EPSRC Centre for Doctoral Training in Cloud Computing for Big Data. The programme is suitable for students from both computing and mathematical backgrounds. It is very skills-focussed and also offers a high degree of research training.

Our course focuses on both theory and practice so that you can understand and implement cloud computing applications. You will cover key subjects such as advanced object-oriented programming, data mining and big data analytics.

All academic staff involved in teaching cloud computing modules have international reputations for their contributions to the field and some have extensive experience as practitioners in industry.

Delivery

During the MRes you will undertake advanced Masters’ level training in cloud computing and data analytics. The training will begin with a module in either computing science for mathematicians (for those with a statistics background) or statistics for computing scientists (for those from a computer science background).

All students will then be taught topics including statistics for big data, programming for big data, cloud computing, machine learning, big data analytics and time series analysis. The taught component will finish with a substantial group project, where you will have the opportunity to work with students from different backgrounds on a practical industry-focused data analysis problem.

Following this in years 2-4, you will carry out PhD research, guided by PhD supervisors from within the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data, and typically additional advisors from industry.

Facilities

You will have access to free cloud computing resources to manage your research, a purpose-built Decision Theatre and 3D visualisation facility and a 3D printing learning lab.

You will be based in The Core building, where you will have the opportunity to work alongside experts in key areas of computing science, as well as access to industrial partners. You will also receive funding to attend selected conferences in emerging areas of your research discipline. We also offer funding for equipment and software to support your research.



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Big data and quantitative methods are transforming political processes and decisions in everyday life. Read more

Big data and quantitative methods are transforming political processes and decisions in everyday life. Local, national and international administrations are making "open data" available to wide audiences; giant, world-level web organisations are putting more and more "services" in synergy (search, map, data storage, data treatment, trade, etc.); and some private companies or governments are developing strongly ideological projects in relation with big data, which may have major consequence on the means by which we are ruled. All these issues involve data in text, image, numeric and video formats on unprecedented scales. This means there is a growing need for trained specialists who will have the cpacity to compete and/or collaborate with strictly business or technique-oriented actos on the basis of sound knowledge from political and international studies.

Programme content

In contrast to degrees such as Data Science or Data Analytics, where the focus ends up being almost exclusively on data practices and computational tools, the MA in Big Data and Quantitative Methods provides you with a knowledge and understanding of the central and innovative quantitative approaches in political science, the debates they have generated, and the implications of different approaches to issues concerning big data and public policy. The MA also draws on the considerable expertise which Warwick now has in quantitative methods located in PAISSociology, the Centre for Interdisciplinary Methodologies (CIM) and the Q-Step Centre.

Given that a noteworthy part of big data is actually social data, this MA programme seeks to attract students from a variety of social science-related disciplines, including politics, sociology, philosophy and economics; you do not need a background in statistics to be eligible for the course. Students are required to take three core modules: Fundamentals in Quantitative Research Methods (previously Quantitative Data Analysis and Interpretation); Big Data Research: Hype or Revolution?, and Advanced Quantitative Research, and have a range of optional modules to choose from in PAIS or from other departments across Warwick including Law, Philosophy, Sociology and the CIM. Graduates of this degree will be able both to engage technically with data released at a new scale and to keep a critical expertise on their relevance and quality, skills which are increasingly required in the competitive global job market.

In addition to regular modules, the Warwick Q-Step Centre is offering a range of different masterclasses. Topics include Reproducibility, Quantitative text analysis, Web data collection, Geostatistics, Inferential network analysis, Machine learning, Agent-based simulation and Longitudinal data analysis. All masterclasses are designed as comprehensive but gentle introductions to methods that are not covered at length in core method modules. They are intended to broaden your horizons and provide concepts and tools to be applied in your future research.



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Our MSc Big Data Analytics programme is designed to provide students with in-depth knowledge of the new field of big data analytics from a computing perspective. Read more
Our MSc Big Data Analytics programme is designed to provide students with in-depth knowledge of the new field of big data analytics from a computing perspective. Data is being generated on an exponential scale by individuals and organisations. Valuable insights can be drawn from this data to inform strategic decisions, resulting in increased market share, profitability, possible cost savings and procedural efficiency. You will develop a critical understanding of the contemporary tools, techniques and models used for big data analytics.

The programme will enable you to develop practical skills, using tools and techniques from the forefront of business computing, and use these effectively to conduct big data analytics. It also seeks to promote an awareness of the moral, ethical and professional framework, within which you will operate as an IT professional in a business environment.

A key aspect of the programme philosophy is that the learning experience tightly integrates the use of Oracle commercial software (a world leader in this field), with investigation of the wider theoretical context. You will also learn about the skills needed to become a successful entrepreneur in the IT sector.

Why choose us?

-Our course is accredited by the British Computer Society, ensuring our course is fresh and relevant.
-The University is one of Oracle’s university-based academies, as well as being a member of UK Oracle User Group.
-This is the only big data analytics programme developed in partnership with Oracle, which is a major global leading IT vendor in the field.
-Previous graduates have progressed into roles with established companies such as Hewlett Packard, BT, Capgemini, Cisco, IBM and more.

Course breakdown

The MSc programme is normally studied over one year full-time or two years part-time (one year and one term full-time for January start). You may move between full and part-time modes of attendance. The course is divided into taught modules of 20 credits and a Masters project of 60 credits. Students complete 60 credits for Postgraduate Certificate, 120 credits for Postgraduate Diploma and 180 credits for the full MSc. Each credit represents 10 notional hours of student learning and assessment. The structure of the course, the module, levels and credit ratings and the awards that can be gained are shown below.

A range of assessment methods are employed, assessment criteria being published in each assignment brief. Knowledge and skills are assessed, formatively and summatively, by a number of methods: coursework, examinations (seen and unseen, open and closed-book), presentations, practical assignments, vivas, online forums, podcasts and project work.

Modules
-Research Methods and Project Management 20 credits
-Applied Statistics 20 credits
-Databases for Enterprise 20 credits
-Big Data Management 20 credits
-Data Mining 20 credits
-Web/Social Media Analytics and Visualisation 20 credits
-Master’s Project 60 credits

Enhancing your employability

This course is suitable for undergraduates and those who have worked in the industry but do not have the recognised qualifications. Students will be provided with the opportunity to complete industry-recognised Oracle Professional Certification.

The school boasts graduates who have gone on to work for Hewlett Packard, Bell Micro, Birmingham City Council, BT, Cap Gemini, Cisco, Deloitte, Ericsson, Fujitsu, IBM, Intel Corporation, NHS, Motorola, National Express, NEC, Royal Mail, Shell IT, JP Morgan Chase and Co, Carillion plc, Siemens and Nokia and many more.

You will also be provided with the opportunity to complete industry recognised Oracle Professional Certification.

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Increasingly, big data are used to track and trace social trends and behaviours. In turn, governments, business and industries worldwide are rapidly recruiting graduates who can understand and analyse big data. Read more
Increasingly, big data are used to track and trace social trends and behaviours. In turn, governments, business and industries worldwide are rapidly recruiting graduates who can understand and analyse big data. This course addresses how big data challenge traditional research processes, and impact on security, privacy, ethics, and governance and policy. You will learn practical and theoretical data skills, both in quantitative methods and the wider theoretical implications about how big data are transforming disciplinary boundaries.

You will take three core modules and a dissertation. Three option modules (see below) allow further specialisation. Lab work, report writing, data skills training and guest lectures by industry experts will form an integral part of your learning experience. You will be invited to attend short certified ‘Masterclasses’ to further extend your methodological repertoire. An annual Spring Camp on a key theme (e.g. health; networks; food) is also provided, allowing you to gain expertise in a wide range of cutting-edge quantitative methods.

You don’t need a computer science, mathematics or statistics background to apply. The focus is on conducting and understanding applied quantitative social science, so a willingness to engage with real world social science issues is essential.

Course Overview

Core Modules
-Big Data Research: Hype or Revolution?
-Principles in Quantitative Research
-Advanced Quantitative Research
-Dissertation

Masters Optional Modules
-Visualisation
-Social Informatics
-Big Data Research
-Hype or Revolution?
-Complexity in the Social Sciences
-Media and Social Theory
-Digital Sociology
-Post Digital Books
-User Interface Cultures
-Design, Method and Critique
-Playful Media
-Ludification in the Digital Age

Assessment
A combination of essays, reports, design projects, technical report writing, practice assessments, group work and presentations and an individual research project.

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