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.
Like many organisations, data centres are experiencing a shortage of senior staff with contemporary and robust skills in leadership and management.
Our MA programme aims to assist those who are already working in managerial roles to develop relevant capabilities to address the current skills gap, to engage with personal and continuing professional development, and to advance their knowledge and application of leadership and management abilities. Developing capability beyond a technical role is central to sound leadership and management in all businesses, and particularly so in this area.
Data Centre Leadership
Finance for Decision making
Sustainable Design for High Capacity Data Centres
Data Centre Infrastructure Management, Security and Disaster Recovery
HRM and Organisational Capability Development
Research Methods for Business and Management
Contemporary Issues in Leadership and Management
Decision Making in Critical Services
Postgraduate Major Project
You’ll be assessed through a range of written assignments, portfolio assessments and report work. You’ll be encouraged to explore the application of theoretical constructs to your own workplace through the use of contextualised assessments, online discussions, and tutor-lead activities.
- This is a 3 year programme
Please note that modules are subject to change and availability.
The Lord Ashcroft International Business School is one of the largest business schools in the East of England, with nearly 100 full-time teaching staff and approximately 6,000 students from more than 100 countries.
Our striking and award-winning business school building in Chelmsford, as well as new buildings in Cambridge, offer the most advanced learning technologies. We’re well-recognised for our centres of excellence by students, employers and professional bodies alike.
What makes us stand out is that our courses don't just give you sound academic knowledge – they’re at the cutting edge of current business practice and highly relevant to employers. This is owing to the close links we have with the business community and the partnerships we've developed with a wide variety of businesses and public service organisations.
We're interested in people who are confident, ambitious and ready to take the challenge of making a difference in the world of business. If that's you, we'd love to hear from you.
Have you ever wanted to ‘Mung’ data? Apply Machine Learning techniques? Search for hidden patterns? Be part of Big Data?
This course is your opportunity to specialize as a Data Scientist, one of the most in demand roles across all sectors including health, retail, and energy. Companies such as Google and Microsoft, and also public organisations such as the NHS are struggling to fill their vacancies in this field due to a lack of suitably qualified people. This course is unique in the UK in that it has been developed as a MSc conversion course – if you have a good honours degree in any discipline with a demonstrable mathematical aptitude, an enquiring mind, a practical and analytical approach to problem solving, and an ambition for a career in data science; then this course is for you.
During your time with us, you will develop an awareness of the latest developments in the fields of Data Science and Big Data including advanced databases, data mining and big data tools such as Hadoop. You will also gain substantial knowledge and skills with the SAS business intelligence software suite due to the partnership of the University with the SAS Student Academy.
"We are especially pleased to endorse the new MSc in Data Science. With the explosion of interest and investment in data science teams, our customers cannot get enough graduates with SAS-based analytical skills. Courses such as this new MSc are an important step forward by the University to addressing this skills shortage, especially amongst home students." - SAS
This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project worth 60 credits. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and could lead to ideas that you can develop for your MSc Project.
The course is focused around the underpinning knowledge and practical skills needed for employment within the data sciences industry. There will be 22 hours of lectures; 11 hours of tutorials and 22 hours workshops; 2 hours of examination-based assessment; and 245 hours of independent study, assessed coursework and preparation for examination. This makes a total of 300 hours total learning experience.
A recent report by e-Skills and SAS (Big Data Analytics: An assessment of the demand for labour and skills, 2012-1017) indicates the demand forecast for staff with big data skills is predicted to ”rise by 92% between 2012 and 2017, and by 2017 there will be at least 28,000 job openings for big data staff in the UK each year…”
With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.
The Informatics Research Centre in the School of Computing, Science and Engineering at the University of Salford builds on the history, success and achievements of the research in Computer Science and Information Systems developed at the University of Salford over the last thirty years.
Evolving around Data and Information in all their types and usages, the Centre covers all phases and processes from data pre-processing to engineering and visualisation. The Centre is developing novel methods and systems for the analysis and recognition of various data sets, learning behaviours and causal models. The techniques and systems developed have a wide range of potential applications including digitisation of historical documents, medical diagnosis, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval and data visualisation.
Forensic computing, digital investigation and Cyber security is another area of expertise supported by the centre both at the theoretical and application levels.
Many students go on to further research in the fields of:
Facilities include a new Dell Cloud Computing platform with OpenStack and lab workstations, providing access to software platforms and languages specialized in Machine Learning, Data Mining, Statistical Analysis and Big Data including:
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.
- 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.
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.
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.
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 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
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 [email protected].
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.
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:
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.
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.
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.
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.
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.