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.
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:
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.
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.
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.
King’s College London is regulated by the Higher Education Funding Council for England.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
This 100% online master’s programme gives you the opportunity to:
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.
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:
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.
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.
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:
Teaching & Assessment
All modules are designed to respect the themes of Big Data, delivering research informed teaching via:
Our assessment methodology is influenced by the learning outcomes to be tested and employs a range of methods including:
Examples of jobs available to you upon graduation include:
Salaries in these roles range from £30,000 to £75,000.
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.
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.
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.
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.
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.
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
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.
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 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.
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.
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.
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.
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 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.
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.
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.
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:
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.
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.
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.
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.
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 PAIS, Sociology, 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.