• University of Bristol Featured Masters Courses
  • University of Leeds Featured Masters Courses
  • Aberystwyth University Featured Masters Courses
  • University of Derby Online Learning Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
  • Northumbria University Featured Masters Courses
  • Jacobs University Bremen gGmbH Featured Masters Courses

Postgrad LIVE! Study Fair

Birmingham | Bristol | Sheffield | Liverpool | Edinburgh

Nottingham Trent University Featured Masters Courses
Cranfield University Featured Masters Courses
Nottingham Trent University Featured Masters Courses
Xi’an Jiaotong-Liverpool University Featured Masters Courses
University of Leeds Featured Masters Courses
"data" AND "quality"×
0 miles

Masters Degrees (Data Quality)

We have 1,146 Masters Degrees (Data Quality)

  • "data" AND "quality" ×
  • clear all
Showing 1 to 15 of 1,146
Order by 
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Health Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Health Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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

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

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

Key Features of the Health Data Science Programme

- A one year full-time taught master's programme designed to develop the essential skills and knowledge required of the Health Data Scientist.

- The Health Data Science course is also available for three years part-time study.

- An integrated programme of studies tailored to the essential skill set required for Data Scientists operating within healthcare organisations covering key topics in computation, data modeling, visualisation, machine learning and key methodologies in the analysis of linked health data.

- Hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment.

- Strong collaboration links with colleagues from the Centre for Health Services Research of the University of Western Australia, a group of leading experts in the analysis of linked health data.

- The Health Data Science course is based within the award winning Centres for Excellence for Administrative Data and eHealth Research of Swansea University, awarded by the Economic and Social Research Council (ESRC) and Medical Research Council (MRC), enhancing the quality of the course.

Who should study MSc Health Data Science?

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

Course Structure

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

Attendance Pattern

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

Modules

Modules on the Health Data Science programme typically include:

Scientific Computing and Health Care

Health Data Modelling

Introductory Analysis of Linked Health Data

Machine Learning in Healthcare

Health Data Visualisation

Advanced Analysis of Linked Health Data

Professional Development

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

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

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

Employability

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

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

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

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

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



Read less
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.



Read less
Health Data Analytics is the activity of extracting insights from health data, either to shape national policy, manage local organisations or inform the care of an individual. Read more

Health Data Analytics is the activity of extracting insights from health data, either to shape national policy, manage local organisations or inform the care of an individual. As more and more data becomes available electronically, the demand for skilled and trained individuals to take advantage of it becomes increasingly urgent.

About this degree

Students on the Health Data Analytics programme will learn about mathematical and statistical approaches to understanding health data, including operational research, machine learning and health economics. They will learn the fundamentals of how health data is collected, represented, stored and processed as well as how to analyse it effectively and how best to present analyses to have an impact on decisions.

Students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), five optional modules (75 credits) and a research project (60 credits).

A Postgraduate Diploma (120 credits, flexible study 2-5 years) is offered.

A Postgraduate Certificate (60 credits, flexible study over a period of two years) is offered.

Core modules

  • Principles of Health Data Analytics
  • Research Methods in Healthcare
  • Statistical Methods for Health Data Analytics

Optional modules

Students choose five of the following:

  • Key Principles of Health Economics
  • Public Health Data Science
  • Learning Health Systems
  • Information Law & Governance in Clinical Practice
  • Economic Evaluation of Health Care
  • Essentials of Informatics for Healthcare Systems
  • Machine Learning in Health Care
  • Clinical Decision Support Systems
  • Patient Safety and Clinical Risk

Please note that the optional modules listed here may be subject to change.

Dissertation/report

All MSc students undertake an independent research project, normally based at their place of work, which culminates in a piece of work written in the style of a journal article.

Teaching and learning

The programme is taught by 'blended learning', and therefore includes interactive online teaching and face-to-face lectures, seminars and workshops including substantial use of examples of real clinical systems. Assessment is through examination, critical evaluations, technical tasks, coursework and project reports, compulsory programming and database assignments, and the dissertation.

Further information on modules and degree structure is available on the department website: Health Data Analytics MSc

Careers

Health data analysts are employed by NHS England in a variety of roles, notably within NHS Improvement, assessing policy proposals and evaluating the economic or financial suitability of initatives. They are employed in acute trusts and in public health, mental health and other community-focused organisations to assist in the planning of services and the assessment of demand and to identify improvements in the organisation and management of services. Consultancy organisations providing services to the health sector also employ analysts as do data and IT organisations.

Employability

Our graduates will be skilled in the use of mathematical and statistical techniques for the manipulation and analysis of data. They will be familiar with state-of-the-art statistical packages but also have detailed practical experience of working with health data and the specific challenges and responsibilities that it entails. They will understand the processes by which data is collected and have insights into how that impacts its significance. These experiences will equip them to work in the NHS and also in a range of commercial and other organisations dealing with healthcare data.

Why study this degree at UCL?

Health data analysts are employed in interesting and challenging roles in healthcare organisations, government agencies and commercial organisations, including IT suppliers, consultancy organisations and pharmaceutical companies. The demand for skilled analysts is growing and graduates with the right skills and training can choose from a range of exciting and rewarding opportunities.

This programme has been designed in conjunction with the NHS to meet an identified shortage in skilled analysts. The aim is to provide a unique educational experience which not only prepares students for technical roles in analysis but equips them to take on senior roles in NHS organisations. The NHS needs not only more analytics staff, but also managers and decision makers who understand the importance of data and the role that analytics should be playing in shaping policy.

Our programme is delivered by a unique team including mathematicians, computer scientists and statisticians with expertise in the analysis of health data in a variety of forms and for a variety of purposes. The team are highly experienced not just in teaching and research but in the practical application of data analytics to the problems of health and healthcare organisations. We work closely with the NHS and with other commercial organisations to ensure our work is relevant and up-to-date.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



Read less
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.

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

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

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

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

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

A short sample of our research interests includes:

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

Many more topics can be found by exploring the Centre’s web pages, particularly the personal web pages of the Centre supervisors:

You will be supervised by one of our 58 world-renowned faculty. You will also benefit from interacting with a group of 35 leading industrial partners, including Amazon, Apple, Google, IBM, and Microsoft.

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

Training and support

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

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

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

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

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

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

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

Facilities

Our research groups contain a diverse range of compute clusters for compute and data-intensive work, including a large cluster hosted by the Edinburgh Compute and Data Facility.

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

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

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

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

Career opportunities

We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way in data science. This vision is shared by our industrial supporters, whose support for our internship programme indicates their strong desire to find highly qualified new employees.

You will be part of a new generation of data scientists, with the technical skills and interdisciplinary awareness to become R&D leaders in this emerging area.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.



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

Course Overview

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

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

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

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

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

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

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

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

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

Year 1 – Postgraduate Certificate (PG Cert)

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

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

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

Year 2 - Postgraduate Diploma (PG Dip)

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

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

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

Year 3 – Master of Arts Degree (MA)

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

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

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

Assessment

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

Read less
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.



Read less
This Joint Degree between HEC Paris and Ecole Polytechnique will equip students with both the technical skills and the strategic mindset to lead successfully any business career requiring a strong expertise in Big Data. Read more

This Joint Degree between HEC Paris and Ecole Polytechnique will equip students with both the technical skills and the strategic mindset to lead successfully any business career requiring a strong expertise in Big Data.

Study in two globally-recognised Institutions

Ecole Polytechnique and HEC Paris are both world leading academic institutions, renowned for the quality of their degrees, faculties and research (see HEC rankings).

Their association within this Joint Degree represents the best Business/Engineering combination Europe could possibly offer, with extraordinary added value for the students who will follow this program in Data Science and Business.

Lead the digital transformation of the economy

Big data marks the beginning of a major transformation of the digital economy, which will significantly impact all industries. There are three main challenges to face:

  • Technological: dealing with the explosion of data by managing the spread of vast amounts of information that is often very disorganized (IP addresses, fingerprinting, website logs, static web or warehouse data, social media, etc.)
  • Scientific: replacing mass data with knowledge,i.e. developing the expertise that makes it possible to structure information, even out of tons of vague or corrupt data.
  • Economic: managing data both to control risks and benefit from the new opportunities they offer. On the one hand, it is absolutely vital to be able to control the flow of information, anticipate data leaks, keep the information secure and ensure privacy. On the other hand, it is also essential to come up with solutions capable of transforming this flow of data into economic results and, at the same time, discover new sources of value from the data.

Acquire the skills to make a difference in tomorrow's digital world

Exploiting this vast amount of data requires the following:

  • A mastery of the sophisticated mathematical techniques needed to extract the relevant information.
  • An advanced understanding of the fields where this knowledge can be applied in order to be in a position to interpret the analysis results and make strategic decisions.
  • A strong business mindset and an even stronger strategic expertise, to be able to fully benefit from the new opportunities involved with Big Data problematics and develop business solutions accordingly.
  • The ability to suggest and then decide on the choice of IT structures, the ability to follow major changes in IT systems, etc.

Therefore the program has three objectives:

  • To train students in data sciences which combines mathematic modelling, statistics, IT and visualization to convert masses of information into knowledge.
  • To give students the tools to understand the newest data distributing structures and large scale calculations to ease decision-making and guide them in their choices.
  • To form data ‘managers’ capable of exploiting the results from analysis to make strategic decisions at the heart of our changeable businesses.

Make the most of the worldwide networking and alumni power 

Students will benefit not only from the close ties that HEC Paris has developed with the business world but also those of Ecole Polytechnique, through various networking events, conferences and career fairs.

The HEC Alumni network alone, consists of more than 52,300 members in 127 countries.

Program details

The key aim of the teaching in this Joint Degree is to provide students with the tools needed to solve real problems, using structured and unstructured data masses, teaching them to ask the ‘right’ questions (both from statistics and ‘business’ perspectives), to use the appropriate mathematical and IT tools to answer these questions.

Students will be equipped to shift constantly from data to knowledge, from knowledge to strategic decision, and from strategic decision to operational business implementations.

All these shifts carry with them numerous challenges that each require an interdisciplinary approach involving mathematics, IT, business strategy, and management skills.



Read less
The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Read more

The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Students learn techniques that are transforming medical research and creating exciting new commercial opportunities. Our recent graduates, many of whom begin paid internships while completing the MSc, have moved on to roles in industry and academia.

About this degree

Students learn how to link and analyse large complex datasets. They design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The content is drawn from epidemiology, computer science, statistics and other fields, including genetics.

Students undertake modules to the value of 180 credits.

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

A Postgraduate Diploma (120 credits) is offered.

A Postgraduate Certificate (60 credits) is offered.

Core modules

  • Principles of Epidemiology Applied to Electronic Health Records Research
  • Data Management for Health Research
  • Statistics for Epidemiology and Public Health
  • Statistical Methods in Epidemiology
  • Topics in Health Data Science

Optional modules

  • Advanced Statistics for Records Research
  • Database Systems
  • Information Retrieval and Data Mining
  • Principles of Health Informatics
  • Machine Learning in Healthcare and Biomedicine
  • Statistics for Interpreting Genetic Data
  • Electronic Health Records
  • Clinical Decision Support Systems

Dissertation/report

All students undertake an independent research project which culminates in a dissertation. Project Proposal 20% (2,000 words); Journal Article 80% (6,000 words).

Teaching and learning

The programme is delivered by clinicians, statisticians and computer scientists from UCL, including leading figures in data science. We use a combination of lectures, practical classes and seminars. A mixture of assessment methods is used including examinations and coursework.

Further information on modules and degree structure is available on the department website: Data Science for Research in Health and Biomedicine MSc

Careers

Students on this programme will be passionate about research and know that, in the 21st century, some of the most exciting, stimulating and productive research is carried out using large collections of data acquired in big collaborative endeavours or major public or private initiatives. We hope that graduates will build on that passion and, together with the experience gained on the programme, will go one to develop careers as entrepreneurs, scientists and managers, working in industry, academia and healthcare.

Employability

The programme is designed to meet a need, identified by the funders of health research and by a number of industrial organisations and healthcare agencies, for training in the creation, management and analysis of large datasets. This programme is practical, cross-disciplinary and closely linked to cutting-edge research and practice at UCL and UCL’s partner organisations. Data science is arguably the most rapidly growing field of employment at the moment and employers recruiting in health data science include government agencies, technology companies, consulting and research firms as well as scientific organisations. A number of employers are supporting the programme in different ways, including providing paid internships to selected students.

Why study this degree at UCL?

Data science is an exciting area with a dynamic job market, including in healthcare. Our graduates have gone on to work for a range of companies, including large research organisations and small start-ups, while others are working in health care or pursuing their interests in universities.

The lecturers on this programme are international experts in health data science and students will learn about cutting-edge research projects. The collaboration is part of the Farr Institute, a network of centres of excellence created to enhance the UK’s strength in data-intensive research. This MSc will draw on that collaboration, giving students access to the most advanced research in the field.

We work closely with a range of employing organisations to ensure that our graduates have the best possible preparation for a career in data science. This includes offering industry-sponsored dissertations for selected students.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



Read less
The Energy Systems and Data Analytics MSc provides an academically leading and industrially relevant study of energy systems through the lens of data analytics. Read more

The Energy Systems and Data Analytics MSc provides an academically leading and industrially relevant study of energy systems through the lens of data analytics. Advanced analytics, fuelled by big data and massive computational power, has the potential to transform how energy systems are designed, operated and maintained. You will gain the skills and knowledge to unlock the transformative potential of big energy data, and understand how it can reshape the energy sector.

About this degree

You will gain a broad understanding of energy systems as a whole, covering supply and demand, the interconnectedness and dependencies between different sectors and a multi-vector multi-sector approach to analysis. You will learn about the theory and practice of data analysis and will gain practical experience of the challenges of working with different data sets relating to energy throughout the programme and modules. 

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

Core modules

  • Energy Systems
  • Energy Data Analytics
  • Statistics for Energy Analysis
  • Energy Analytics in the Built Environment
  • Energy and Transport Analytics

Optional modules

  • Spatial Analysis of Energy Data
  • Introduction to Systems Dynamics Modelling in the Built Environment
  • Econometrics for Energy and the Environment
  • Energy, Technology and Innovation
  • UK Energy and Environment Policy and Law
  • Smart Energy Systems: Theory, Practice and Implementation
  • Eco-innovation and Sustainable Entrepreneurship

The list of optional modules is correct for the 2018/19 academic year. Enrolment on modules is subject to availability.

Dissertation/report

All students undertake an independent research project whch culminates in a 10,000-word dissertation.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, tutorials, problem-based learning and project work. Assessment is through a combination of methods including problem sets, individual assignments and coursework, group based design tasks with a report and presentation, unseen examinations and a dissertation.

Further information on modules and degree structure is available on the department website: Energy Systems and Data Analytics MSc

Careers

Graduates of the ESDA MSc will be ideally placed to gain employment as energy analysts/ data scientists in consultancies, utilities, innovative start-ups and government institutions which value expertise in energy systems and have a need for data literate analysts.

Employability

There is a strong emphasis placed on innovation throughout the programme. Based on our market research and the trends in the industry (which is increasingly driven by data) there will be a healthy demand for our graduates.

Students will also benefit from a skill set in data analytics that will be highly transferable and applicable across a range of industries and domains.

The programme has been developed with input from industry leaders. You will gain exposure to real life energy and sustainability challenges.

Why study this degree at UCL?

The MSc in Energy Systems and Data Analytics is the first programme in the UK to combine the study of energy systems with data science. The MSc is delivered by leading researchers in the UCL Energy Institute and UCL Institute for Sustainable Resources. You will benefit from their specific expertise, research communities and industry contacts (including guest lecturers drawn from the energy industry), as well as our multidisciplinary and cross-domain approach.

The UCL Energy Institute has consulted across industry to identify key skills gaps for the energy analysts that will be required by utilities, consultancies and small and medium enterprises. There is a growing need in industry for graduates who combine an understanding of energy systems with the skills and abilities to extract insights from data through the use of advanced analytics.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



Read less
Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. Read more
Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. This is one of the first MSc programmes in the UK covering these leading-edge technologies. The programme provides students with the deeper knowledge, advanced skills and understanding that will allow them to contribute to the development and design of big data systems as well as distributed/internet-enabled decision support application software systems, using appropriate technologies, architectures and techniques (e.g. data analytics, business intelligence, NoSQL, data mining, data warehousing, distributed data management and technologies, Hadoop, etc.).

Additionally, the programme enables students to understand and assess the security and legal implications of e-commerce applications and provides students with appropriate knowledge of business and commerce relevant to transacting business on the internet. The courses take a software engineering approach to the construction of applications and focus on modern software engineering methods, tools and techniques that enable an integrated life-cycle software development view.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

Visit the website http://www2.gre.ac.uk/study/courses/pg/com/cgbdbi

Computing - General

Come and study in the award-winning Department of Computing & Information Systems on the magnificent Greenwich Campus. Welcoming home and international students from all backgrounds, CIS provides an exciting, diverse and friendly environment in which to study.

The latest university league table published in the Sunday Times, has rated the computer science department as seventh in the UK for teaching excellence.

What you'll study

Full time
- Year 1:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Architectures and Administration (15 credits)
Database Tools (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Part time
- Year 1:
Students are required to study the following compulsory courses.

Database Architectures and Administration (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

- Year 2:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Tools (15 credits)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Fees and finance

Your time at university should be enjoyable and rewarding, and it is important that it is not spoilt by unnecessary financial worries. We recommend that you spend time planning your finances, both before coming to university and while you are here. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Career options

Graduates from this programme can pursue careers as data scientists, database designers and administrators, consultants, senior team members, programmers, analysts.

Find out how to apply here - http://www2.gre.ac.uk/study/apply

Read less
Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. Read more

Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

About this degree

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules in computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

Core modules

  • Introduction to Statistical Data Science
  • Introduction to Machine Learning
  • Statistical Design of Investigations
  • Statistical Computing

Optional modules

At least two from a choice of Statistical Science modules including:

  • Applied Bayesian Methods
  • Decision & Risk
  • Factorial Experimentation
  • Forecasting
  • Quantitative Modelling of Operational Risk and Insurance Analytics
  • Selected Topics in Statistics
  • Stochastic Methods in Finance I
  • Stochastic Methods in Finance II
  • Stochastic Systems

Up to two from a choice of Computer Science modules including:

  • Affective Computing and Human-Robot Interaction
  • Graphical Models
  • Statistical Natural Language Processing
  • Information Retrieval & Data Mining

Dissertation/report

All students undertake an independent research project, culminating in a dissertation usually of 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Further information on modules and degree structure is available on the department website: Data Science MSc

Careers

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study. 

The Data Science MSc is a new programme with the first cohort of students due to graduate in 2017. Recent career destinations for graduates of the related Statistics MSc include:

  • Management Associate, HSBC
  • Statistical Analyst, Nielsen
  • PhD in Statistics, UCL
  • Mortgage Specialist, Citibank
  • Research Assistant Statistician, Cambridge Institute of Public Health

Employability

Data science professionals are likely to be increasingly sought after as the integration of statistical and computational analytical tools becomes essential in all kinds of organisations and enterprises. A thorough understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should should be accompanied by statistical expertise at graduate level. Data scientists need a broad background knowledge so that they will be able to adapt to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Statistical Science

82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



Read less
This programme will help broaden your horizons and give your studies a global outlook. The dual award, which offers practical experience, builds on the Postgraduate Diploma Quality Management at UWS (see page 164) with additional study at University of Angers, France. Read more
This programme will help broaden your horizons and give your studies a global outlook. The dual award, which offers practical experience, builds on the Postgraduate Diploma Quality Management at UWS (see page 164) with additional study at University of Angers, France.

About the programme

Quality Management is the application of specialised managerial and technological skills to achieve the desired quality at a minimum cost. It also addresses strategic quality issues and leadership in establishing a total quality ethos which focuses on achieving customer satisfaction.

Our close links with commerce and industry ensure the programme reflects the latest in quality thinking and techniques, and our laboratories have industry-standard equipment. It will enhance your understanding of modern developments within the global field of quality.

This dual award programme is the same as the MSc Quality Management (see page 164) but with additional study at the University of Angers in France. Funding options are available for the period of study in France. At the end of the programme you will receive two Masters; MSc Quality Management (International) from UWS, and MSc ISMP (Ingénierie des Systèmes et Management de Project) from University of Angers. Classes in France are taught in French but you can sit exams and assignments in English.

Your learning

MSc Quality Management (International) Postgraduate Diploma
• Operations and Project Management
• Interpersonal Skills and Change Management (10 point module)
• Research Design and Methods (10 point module)

plus one from:
• Service Quality
or
• Reliability and Experimental Design for Industry

MSc ISMP
You will also study:
• Formation Générale
• Management de projet
• Qualité Logiciel

MSc

Upon successful completion of the taught modules listed above you will undertake the MSc research project, which can be carried out within industry in Scotland or France.

Our Careers Adviser says

Graduates seek employment as quality or continuous improvement managers in various organisations including manufacturing, electronics, engineering, public sector and service organisations.

First-class facilities

Get the hands on experience you need to succeed. We have excellent specialist facilities which support our research students and staff. These include an advanced chemical analysis lab: with state-of-theart chemical analysis for isotopic and elemental analysis at trace concentrations using ICPMS/OES and the identification of organic compounds using LCMS; and the Spatial and Pattern Analysis (SPAR) lab: providing high specification workstations, geographical information system (GIS) software, geochemical and image processing facilities to support data management in science research.

Read less
Your programme of study. There is a lot you can do with data in any organisation. Read more

Your programme of study

There is a lot you can do with data in any organisation. With the increase in technology and IOT plus the 'Big Data' revolution the collation of data and the power it holds to transform organisations, ensure health and safety in difficult to reach places, keep ahead of life cycles, drive change and innovation has huge potential for any organisation. Within the oil and gas and energy sectors and related supply chain the revolution of supply and demand is already happening.

If you already work in data either in the energy sector or other related sectors this programme specialises in its application to the oil and gas sector and it is partnered with Common Data Access Ltd which is a not for profit subsidiary of Oil and Gas UK. It provides data management services to the oil and gas industry. The programme is developed with academics at University of Aberdeen and industrial partners and it covers data protection, governance and quality plus project and data management and legal commercial and security aspects of data management.

The programme develops your key data management requirements working in interdisciplinary teams in the energy industry and is sponsored and input by multinationals within those industries. You can study this programme either on campus full time or part time or online part time from anywhere with an internet connection. The part time delivery is designed to fit around your work and life.

Courses listed for the programme

Campus Delivery

Semester 1

  • Fundamentals of Petroleum Geoscience
  • Petroleum Data Governance
  • Petroleum Data Management Tools and Techniques
  • Petroleum Data Quality Management

Semester 2

  • Reference, Project and Corporate Data Management
  • Petroleum Data Management Tools and Techniques 2
  • Service and Project Management
  • Petroleum Information Security, Entitlements and Obligations

Semester 3

  • Project in Data Management

Online Delivery:

Semester 1

  • Fundamentals of Petroleum Geoscience
  • Petroleum Data Management Tools and Techniques
  • Petroleum Data Governance
  • Petroleum Data Quality Management

Semester 2

  • Reference, Project and Corporate Data Management
  • Service Project Management
  • Petroleum Data Management Tools and Techniques
  • Legal, Commercial and Security Aspects of Petroleum Data Management

Semester 3

  • Project in Petroleum Data Management

Courses listed for the programme

Find out more detail by visiting the programme web page for campus delivery and online delivery

Why study at Aberdeen?

  • The advanced degree provides you with modules from Law, Engineering, Business, Geography, Geology and Computing Science
  • The degree is designed with leading industry organisations
  • University of Aberdeen is in the heart of the energy industry with very close links to major FTSE 100 companies in the city

Where you study

  • University of Aberdeen
  • 30 Months
  • Part Time
  • September start

International Student Fees 2017/2018

Find out about international fees:

Find out more about fees on the programme page

*Please be advised that some programmes also have additional costs.

Scholarships

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

Living in Aberdeen

Find out more about:

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

Find out more about living in Aberdeen and living costs 

You may also be interested in:



Read less
Efficient management of data and knowledge are key factors not only to the success of almost any enterprise, but also to the successful handling of today's vast amounts of science related data. Read more

Efficient management of data and knowledge are key factors not only to the success of almost any enterprise, but also to the successful handling of today's vast amounts of science related data: with the transition to the information age and the knowledge economy, data has become both increasingly central and critical to all activities. For example, imagine the huge amounts of genomic or patient data available electronically, and how the quality of their management can affect society.

The Data and Knowledge Management pathway allows students to take specialist themes concerned with methods and technologies for the adequate management of data and knowledge. The Managing Data theme focuses on the design, maintenance, and query processing of both structured and unstructured databases. The Learning from Data theme covers principles, algorithms, and technologies underlying machine learning, probabilistic modelling, and optimisation, while exposing students to relevant applications. The Advanced Web Technologies theme provides students with a deep understanding of the technologies that are being used to support the continuing evolution of the Web, including Semantic Web technologies.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

Students following the Data and Knowlege Management pathway have all the career choices and options as described for general Advanced Computer Science.

In addition, students of this pathway are ideally placed to work in positions requiring an understanding of modern data and knowledge management tools and technologies. This includes data and knowledge engineering positions in all areas where data is stored and managed electronically, i.e., in all areas, including the finance, retail, and healthcare sector.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.



Read less

Show 10 15 30 per page



Cookie Policy    X