This programme provides practical, career-orientated training in social science research methods, including research design, data collection and data analysis relating to both qualitative and quantitative modes of inquiry.
Students will have the opportunity to specialise in particular methodologies and to learn more about the application of these methodologies to illuminate important issues and debates in contemporary society.
The programme is designed to provide a fundamental grounding in both quantitative and qualitative research skills, along with the opportunity to specialise in more advanced training in quantitative research, qualitative research or in practical applications of research techniques.
This module offers an introduction to the different styles of social science research as well as guidance and illustrations of how to operationalize research questions and assess them empirically. Students will be shown how to conduct systematic literature searches and how to manage empirical research projects. The module will also explore issues around the ethics of social science research as well as the connection between social science research and policy concerns. It is designed as preparation for undertaking postgraduate research and dissertation work.
This module aims to deepen students' understanding of key debates in social theory and research, providing advanced level teaching for those building upon basic knowledge and undertaking postgraduate research. It is designed to demonstrate and explore how social theory is utilised, critiqued and developed through the pursuit of social science research.
The purpose of this module is to illuminate the theoretical underpinnings of qualitative research. The module will discuss the impact of various theories on the nature and conduct of qualitative research particularly around questions of epistemology and ontology. The role of different types of interviewing in qualitative research will be utilised in order to explore the relationship between theory and methods.
The aim of the module is to provide a comprehensive overview of the theory and practice of measurement and constructing quantitative data in the social sciences. Through lectures and practical exercises, this module will provide students with relevant knowledge of secondary data sources and large datasets, their respective uses and usefulness, and their relevance for the study of contemporary social issues
The module will provide students with an overview of different approaches to qualitative data analysis. It will include introductory training to this skill that includes such techniques as thematic analysis and discourse analysis, as well as computer assisted qualitative data analysis. It will provide the knowledge necessary for the informed use of the qualitative data analysis software package NVivo. The module gives students a base level introduction to the analytical and technical skills in qualitative data analysis appropriate to the production of a Master's dissertation and/or use of CAQDAS software for social science research purposes.
This module provides an introduction to the basics of quantitative data analysis. The module will begin with a brief review of basic univariate and bivariate statistical procedures as well as cover data manipulation techniques. The module is taught through a series of seminars and practical workshops. These two strands are interwoven within each teaching session. Please note that students may be granted an exemption from this module if they have already successfully completed a module that has the equivalent learning outcomes.
This module advances students' confidence and knowledge in the use of SPSS. The module focuses on multivariate regression models, including the appropriate use and awareness of statistical assumptions underlying regression and the testing and refinement of such models.
A dissertation of no more than 15,000 words on a topic relevant to social science research methods training. The thesis will involve either carrying out and reporting on a small social science research project which includes a full and considered description and discussion of the research methods employed or the discussion of a research issue or technique to a level appropriate for publication.
We offer a range of advanced modules in quantitative and qualitative research methods, for example, logistic regression, internet-based research and visual research methods. We also provide specialist modules which reflect the teaching team’s diverse research interests, from the social logic of emotional life to conflict and change in divided societies. Optional modules generally run during the Spring semester and are offered subject to sufficient student demand and staff availability. Students will be able to choose a maximum of three to four option modules (depending on whether they need to complete Quantitative Data Analysis: Foundational). Please note that it is unlikely that all the following modules will be available for 2017/8. Please check with the Programme Director for queries about specific modules.
This one year MSc programme in Statistics and Computational Finance aims to train students to work as professional statisticians, not only at the interface between statistics and finance, but to provide skills applicable in sociology, health science, medical science, biology, and other scientific areas where data analysis is needed.
The emphasis of the programme is on data analysis. It equips students with contemporary statistical ideas and methodologies as well as advanced knowledge, which will make students very competitive to industry, academic and governmental institutions. There are excellent career prospects for employment in industry and the public sector for our graduates. An MSc degree in Statistics and Computational Finance provides attractive employment opportunities in financial industries, government, consultancy companies, research centres, and other industries where data analysis is needed. Students with an interest in academic work may also decide to continue on a PhD programme in Statistics or a related field, for which the MSc in Statistics and Computational Finance provides a sound foundation.
There are excellent career prospects for students with a background in statistics and data analysis. The programme is designed to equip students with contemporary statistical ideas and methodologies which makes our students very competitive when seeking employment in industry and governmental institutions, as well as in academic careers. The skills taught are applicable in sociology, health science, medical science, biology and other related disciplines where data analysis is needed.
Recent destinations of graduates from the MSc in Statistics and Computational Finance have included:
-PhD in the Department of Mathematics at the University of York (Non-parametric modelling in high dimensional data analysis)
-PhD at Florida State University
-Modelling Analyst (automotive data provider)
-Graduate Technical Analyst (HSBC)
-Research and Development in a Property and Casualty Insurance company, specialising in catastrophe insurance
-Mainframe Software Solution Sales in a major IT brand
-Data Analyst in a health data company
-Trainee Chartered Accountant
To achieve an MSc degree students must complete modules to the value of 180 credits, including 100 credits of core taught modules, 20 credits chosen among the optional taught modules, and a 60-credit dissertation.
These postgraduate programmes aim to create highly sought-after researchers who are ready to apply their advanced knowledge and practical skills in the workplace or on further research.
You will learn how to collect, analyse and interpret social data and become skilled in interview techniques, surveys, problem-solving, communication skills and the latest industry software.
Students examine issues from across the social sciences and are introduced to both quantitative and qualitative research methods before having the option of specialising.
During the programme, you will research real world issues such as evaluating local health care services, predicting voting behaviour during elections or researching the impact of Hull’s year as the 2017 UK City of Culture on local people.
Taught by experienced researchers who are experts in their fields, the interesting and varied curriculum will be delivered through an enquiry-based approach to teaching including small-group work, tutorials, workshops and independent study.
It was designed with input from industry experts, former students and leading academics to ensure that it means the demands of the modern social research industry.
Students will be provided with a high level of academic support across the programme and all modules will be taught on one specific day (currently Thursdays) to accommodate part-time and working students.
There are four variants:
MSc in Social Research
Semester 1 (PGCert)
Semester 2 (PGDip)
Summer period (Masters)
MSc in Social Research with Quantitative Methods
Semester 1 (PGCert)
Semester 2 (PGDip)
Summer period (Masters)
MA in Social Research with Qualitative Methods
Semester 1 (PGCert)
Semester 2 (PGDip)
Summer period (Masters)
MSc in Social Research (Doctoral Training Pathway)
Semester 1 (PGCert)
Semester 2 (PGDip)
Summer period (Masters)
* All modules are subject to availability.
These programmes are an ideal route for those aiming for research careers in the public, voluntary or private sectors, including would-be senior civil servants keen to take advantage of the Government’s Fast Stream scheme to find the leaders of the future.
It equips students with practical skills and experience for a wide range of organisations including research agencies, charities, independent organisations, trade unions, pressure groups and lobby groups.
The programmes also offer continuing professional development for those already working as researchers and who want to advance their careers. It is also an excellent training programme for those wishing to progress to PhD level study.
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.
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:
On this established and well respected course, you gain the knowledge, skills and attributes needed to be an effective sport and exercise science practitioner and/or researcher. You develop strong technical, analytical, practical and professional skills, alongside specialist skills in • biomechanics and performance analysis • physiology and nutrition • strength and conditioning.
The course enables you to
We offer a first-class suite of research and teaching laboratories alongside excellent facilities offered by our partnership venue at the English Institute of Sport, Sheffield. Our laboratories are all British Association of Sport and Exercise Science (BASES) accredited.
The four overarching themes in the programme are
Many of the teaching staff support elite athletes as part of their work and undertake research in sport and exercise. We benefit from the expertise of our staff in the Centre for Sport and Exercise Science (CSES). The team for sport performance have worked successfully with athletes competing at the Olympics, Paralympics, and Winter Olympics. They have provided, or are currently providing, sport science research and consultancy services at elite level for the • Amateur Boxing Association • Amateur Swimming Association (diving and swimming) • British Cycling • British Speed Skating Association • British Skeleton-Bob Team • English Bowls Association • English Golf Union • Royal Yachting Association • GB table tennis • GB volleyball.
You benefit from CSES' activities as they allow us to keep course content at the cutting edge, based on our knowledge and experience of sport and exercise science delivery. You can also benefit from a work-based learning programme to help develop your experience of working in multidisciplinary teams, supporting athletes and coaches.
During the course you use a mix of traditional and online learning resources to ensure the course is flexible and can fit in with your existing commitments.
The quality of our provision was rated 24/24 by the Higher Education Council.
Sheffield Hallam are a Skills Development Partner of the Chartered Institute for Managing Sport and Physical Activity.
This course is designed to meet some of the needs of the British Association of Sport and Exercise Science (BASES), and the United Kingdom Strength and Conditioning Association accreditation.
The masters award is achieved by successfully completing 180 credits.
30 credits from:
As a graduate you benefit from the skills and experience gained from the employability modules and our connections with industry.
Previous graduates have gone into careers as • developers for suppliers of sport equipment • sport science officers • advisors for national governing bodies and the English Institute of Sport • coaches • developing corporate wellness programmes in the health and fitness industry • advisors to local authorities and local health trusts • strength and conditioning coaches • sport and exercise nutritionists • researchers • technicians • university lecturers.
The course's strong focus on research skills provides an ideal platform for further study at PhD level. It is also an important first step into employment and can open many other doors into further training.
Sport scientists support athletes or sports clubs, they generally provide advice and support, designed to monitor and improve sport performance, alongside a team of specialists including coaches, psychologist, performance managers and medical staff. Areas of expertise include • strength and conditioning • physiology • nutrition and analysis of movement and tactical performance.
Exercise scientists are more concerned with improving a person's health and helping them recover from illness through a structured programme of physical activity and other health-based interventions. They are also involved with preventative treatments and work closely with GPs and primary care trusts or private healthcare organisations. Exercise scientists might be employed by local authorities to run community based health and exercise initiatives.
It may be possible to move into a particular clinical area, such as cardiology, or work as a health promotion specialist for a local authority or healthcare trust. Our close links with the National Centre for Sport and Exercise medicine, part of which is based in Sheffield, will provide additional opportunities to those wishing to pursue careers in this area.
Other careers also include • the pharmaceutical industry • the armed and uniformed services • journalism • teaching. If you are thinking about an academic career, many universities with sport-related courses require staff to have a higher degree.
This course has been designed for students who wish to develop their quantitative and qualitative research methods and applied data analysis, from basic to advanced levels to advance their careers and become leaders in their clinical field.
Knowledge and critical understanding of clinical research methods are becoming increasingly important skills for all professionals in the health, social care and private sectors, where an evidence based approach, supported by academic rigour is crucial to decision making, clinical practice and delivery of integrated services.
The MRes Clinical Research will provide you with training in quantitative and qualitative research methods and applied data analysis from basic to advanced levels as well as provide opportunities to apply this research knowledge to clinical settings.
We will enable you to produce high quality, publishable research and give you the skills and knowledge to develop your clinical academic research career to become a leader in your clinical field.
You will learn from experts in clinical research who are renowned nationally and internationally.
You will undertake a work-based research placement with a research centre/ unit/ project team of their choosing. The purpose of the placement is to enable the student to develop and refine awareness, knowledge, understanding, experience, and skills in undertaking research in clinical practice. Students identify their own research site, and negotiate mutually beneficial learning objectives for the time period in placement.
Teaching is conducted via a mixture of lectures, class discussions and seminars, student presentations, poster presentations, analysis of case studies, worked examples, interactive computer-based exercises, an online VLE and self-directed reading.
Formal assessments will be conducted via: essays, a systematic review, a research proposal, critical reviews, written examinations and a research project on an approved topic.
In addition, there are short practical assignments throughout the course during sessions.
You will be expected to allocate an average of 150 hours of taught and self-directed learning per 15-credit module.
Alternatively, you can take modules from this Masters degree as standalone CPPD (Continuing Personal and Professional Development) courses. In this case, course costs might vary. For further information please visit our CPPD pages.
As a student on this course you will receive the research and academic training to become a clinical academic researcher across all health service settings including the NHS, charities, industry, government, private practice and academic and research settings.
You will gain vital transferable skills which are applicable to all health and medical related careers where attention to detail, conducting research and evaluation for evidence based practice, and report writing is a career advantage.
MRes Clinical Research graduates may also choose to advance to doctoral studies on completion of the programme.
The course is suitable for professionals from clinical and non-clinical backgrounds, including those who have worked in:
The competencies that you will develop on the course will help you design, conduct and interpret research that aims to understand or improve specific issues in the organisation and delivery of our health services. The course is particularly relevant for professionals working in the health services who wish to expand their role, or move to a new role, that requires a deeper understanding of research methods and evidence-based practice and policy.
Alternatively, the course provides a stepping stone if you are considering developing your career by pursue an MPhil or PhD- in Health Services Research.
The MSc in Health Services Research will help you:
Health Services Research is the study of healthcare quality, access and costs in order to make health services more effective, equitable and efficient. Health Services Research is inherently multidisciplinary and requires strong research competencies as a foundation to promote evidence-based practice and policy.
The MSc in Health Service Research provides training in a wide range of qualitative, quantitative, and systematic review methods. Beyond these core modules, you will be able to select from a range of electives modules (subject to availability and compatibility with your other elective choices) that allow you to tailor the programme to your own needs and interests. We offer electives modules that focus on practice, management and policy levels of health services. This flexibility allows you to concentrate on a more specialise area or generalise to gain a broader understanding of health services at different levels (micro, meso and macro).
Teaching and learning for your Health Services Research MSc takes place through an engaging mix of approaches, including:
Modules are assessed through a combination of methods:
This course consists of 180 credits. You will receive comprehensive theoretical and practical training in research methods and data analysis in a programme that comprises a range of qualitative, quantitative and mixed methods courses and practical workshops. You will gain in-depth knowledge and understanding of the process of developing theory-driven complex interventions for the improvement of health and healthcare.
The taught component of the MSc in Health Services Research is structured as follows:
As a postgraduate student, you will be expected to allocate an average of 150 hours of taught and self-directed learning per 15-credit module.
You will select three of the following:
This course will give you a thorough grounding in practical research and statistical skills. As a result, it will open-up a wide range of career options for you to explore in management, service provision and practice roles.
You can go on to develop your career across the broad scope of health service settings, including:
You will gain vital transferable skills which are applicable to all health and medical related careers, where attention to detail, conducting research and evaluation for evidence based practice, and report writing is in high demand.
As a Health Services Research MSc Graduate, you may also wish to pursue further academic achievements by undertaking doctoral-level study.
Our programme will give you cross-disciplinary skills in a rare combination of areas of expertise, from bioinformatics and evolutionary inference to computational biology and fieldwork.
You will be taught by researchers who apply genomic methods to a wide range of issues in ecology and evolution, from bat food-webs and genome evolution to microbial biodiversity in natural and engineered ecosystems. For example, Professor Steve Rossiter carries out world-leading research on bat genome evolution; Dr Yannick Wurm has discovered a social chromosome in fire-ants; and Dr China Hanson is using genetic methods to study microbial biogeography. This means that teaching on our programme is informed by the latest developments in this field, and your individual research project can be at the forefront of current scientific discovery.
You will conduct your own substantive six-month research project, which may be jointly supervised by contacts from related institutes or within industry. You will also take part in a field course in Borneo - see photos from a recent trip on Flickr - giving you the opportunity to develop first hand experience of theory in action.
By choosing to study at a Russell Group university you will have access to excellent teaching and top class research. You can find out more about our research interests and view recent publications on the School of Biological and Chemical Science's Evolution and Genetics group page.
This MSc programme combines taught modules with individual and collaborative research projects. You will apply the knowledge and techniques from your taught modules in a practical setting and may be able to publish your project findings.
If you have any questions about the content or structure, contact the programme director Dr Christophe Eizaguirre.
This programme is for students who have a numerate first degree or can demonstrate numerate skills. Students are often at the early stages of their careers in diverse professions including economics, statistics and computer science.
Students will have a curiosity about data, and will want to learn new techniques to boost their career and be part of exciting current industry developments. The MSc in Data Science includes some complex programming tasks because of the applied nature of the course, so many students have a mathematics or statistics background and enjoy working with algorithms.
The demand for data scientists in the UK has grown more than ten-fold in the past five years *. The amount of data in the world is growing exponentially. From analysing tyre performance to detecting problem gamblers, wherever data exists, there are opportunities to apply it.
City’s MSc Data Science programme covers the intersection of computer science and statistics, machine learning and practical applications. We explore areas such as visualisation because we believe that data science is about generating insight into data as well as its communication in practice.
The programme focuses on machine learning as the most exciting technology for data and we have learned from our own graduates that this is of high value when it comes to employment within the field. At City, we have excellent expertise in machine learning and the facilities students need to learn the technical aspects of data analysis. We also have a world-leading centre for data visualisation, where students get exposed to the latest developments on presenting and communicating their results – a highly sought after skill.
Accredited by BCS, The Chartered Institute for IT for the purposes of fully meeting the further learning academic requirement for registration as a Chartered IT Professional, and on behalf of the Science Council for the purposes of partially meeting the academic requirement for registration as a Chartered Scientist and a Chartered Engineer.
MSc Data Science students can participate in our professional internships programme, which is supported by the Professional Liaison Unit. This will enable you to undertake your MSc project in an industrial or research internship over an extended period compared to regular projects. For example, the individual project can be carried out as a 6-month internship in one of the companies with which City has a long-standing relationship and history of collaboration in the big data and data science area.
Examples of company placements internships taken by our Data Science students in the recent past include: Google, SagePay, Reward, Black Swan.
The teaching and learning methods we use mean that students’ specialist knowledge and autonomy increase as they progress through each module. Active researchers guide your progress in the areas of machine learning, data visualization, and high-performance computing, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.
Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:
Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.
Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.
In addition to lectures, laboratory sessions and tutorial support, you also have access to a personal tutor. This is an academic member of staff from whom you can gain learning support throughout your degree. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.
We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Each module is assessed through a combination of written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply data science methods and techniques.
The individual project is a substantial task. It is your opportunity to develop a research-related topic under the supervision of an academic member of staff. This is the moment when you can apply what you have learnt to solve a real-world problem using large datasets from industry, academia or government and use your knowledge of collecting and processing real data, designing and implementing big data methods and applying and evaluating data analysis, visualisation and prediction techniques. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.
From health to retail, and from the IT industry to government, the Data Science MSc will prepare you for a successful career as a data scientist. You will graduate with specialist skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction and explanation, which are in high demand.
City's unique internships, our emphasis on machine learning and visual analytics, together with our links with the industry and Tech City, should help you gain employment as a specialist in data analysis and visualization. Graduates starting a new business can benefit from City's London City Incubator and City's links with Tech City, providing support for start-up businesses.
After successful completion of the course you may wish to consider a PhD degree in Computing.