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Data Science MSc
Study level: Postgraduate
Data is everywhere. As the volume and complexity of data collected continues to grow, there is increasing demand for expertise in data science to support the analysis and visualisation of all this information.
Year of entry
Location
Coventry University (Coventry)
Study mode
Full-time
Duration
1 year full-time
Course code
EECT109
Start date
May 2025
Course overview
The MSc Data Science is a conversion course for graduates from a wide range of disciplines and backgrounds looking to pursue a career, or upskill, in this new and rapidly developing field. Data Scientists are in short supply and there is high demand for data science skills across sectors including business, government, healthcare, science, finance, and marketing.
The aim of the MSc in Data Science is to support you if you have little previous experience of data analysis or computer programming. It aims to help you gain new skills such as:
- working with databases
- statistical thinking
- programming in high-level languages
- modelling
- applying data science tools and packages
- machine learning
- data visualisation
- addressing the challenges of big data.
5 QS Stars for Teaching and Facilities
QS Stars University Ratings
Ranked 11th Modern University in UK by the Times
The Times and Sunday Times Good University Guide 2025
Ranked 8th for Overall Satisfaction in PTES
Postgraduate Taught Experience Survey (PTES) 2024Why you should study this course
If you are curious about applying data to interesting questions, have an eye for data visualisation, are talented at communicating with experts or the public, or take logical approach to solving problems, then you could make a great member of a data science team in any organisation.
- This course has been designed specifically for graduates from a diverse range of disciplines to give them an opportunity to gain expertise from across the broad field of data science to help complement their existing skills and knowledge.
- The course aims to develop foundational skills in computer programming, data analysis, and mathematics, for those with little previous experience. These skills are developed in context alongside hands-on use of data science software tools across a range of common applications.
- The skills gained upon successful completion of this conversion course should complement existing knowledge and skills from your undergraduate study or work experience, such as formulating questions, building arguments, writing reports, delivering presentations, creative problem solving, and a curiosity about data.
- Features of the course include working with other students with different experiences and perspectives and having the opportunity to gain broad experience of working with a variety of types of data to address diverse and interesting questions.
Accreditation and professional recognition
This course is accredited1 and recognised by the following bodies:
Chartered Management Institute (CMI)
As part of this course, you will undertake a professional development module which is currently accredited by the Chartered Management Institute for the 2024-25 intake. Upon successful completion of this module, you will gain the CMI Level 7 Certificate in Strategic Management and Leadership Practice at no additional cost.
Coventry University’s accreditation with CMI is currently ongoing for the relevant modules and is regularly reviewed and monitored by the CMI through their quality systems. Whilst Coventry University anticipates that these reviews will continue to be successful, if they were to be unsuccessful, the relevant module in this course would no longer be accredited and we would notify applicants and students of this change as soon as possible.
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What you'll study
Data Science is a broad multidisciplinary field encompassing everything from cleaning and managing data to data visualisation and deploying predictive models.
The course supports students from diverse backgrounds to develop the necessary foundations of data science in computer programming, data analysis and statistical thinking, before building more specialised knowledge and skills in data management, machine learning, and the technological challenge of dealing with big data. Throughout the course there are many opportunities for you to build on your existing knowledge and experience from your undergraduate degree or workplace, and gain experience in the analysis of data of a variety of kinds and sizes.
The course maintains a balance between hands-on technology-dependent practical skills using modern software, knowledge and understanding of specialist methods and algorithms in learning from data, mathematical language and foundations, and broader issues around data ethics, data protection and communication with stakeholders of all kinds. In particular, the course covers: programming and software development in a high-level programming languages such as Python and R; data analytics, statistical modelling and programming with data; mathematical foundations of data science such as modelling, linear algebra, and probability; data management systems for structured and unstructured data; big data management, distributed databases and data visualisation; machine learning algorithms for learning from data; and a range of data science applications, tools, projects and current issues.
We regularly review our course content, to make it relevant and current for the benefit of our students. For these reasons, course modules may be updated.
How you'll learn
Teaching methods may include a combination of:
- lectures
- problem-solving workshops
- supervised computer laboratory sessions
- in-class discussions and presentations
- directed reading
- formative assessments.
Teaching contact hours
A 15-credit module will typically have approximately 30 hours of contact time associated with it, while a 30-credit module will have approximately 60 hours of contact time. This may include a combination of, but may not be limited to, lectures, group sessions, laboratory sessions and support sessions. In addition, you will be expected to undertake significant self-study of around 25-35 hours each week depending on the demands of individual modules.
The contact hours may be made up of a combination of face-to-face teaching, individual and group tutorials, and online classes and tutorials.
As an innovative and enterprising institution, the university may seek to utilise emerging technologies within the student experience. For all courses (whether on-campus, blended, or distance learning), the university may deliver certain contact hours and assessments via online technologies and methods.
Since COVID-19, we have delivered our courses in a variety of forms, in line with public authority guidance, decisions, or orders and we will continue to adapt our delivery as appropriate. Whether on campus or online, our key priority is staff and student safety.
Assessment
This course will be assessed using a variety of methods which could vary depending upon the module. Assessment methods may include coursework, tests, reports, projects, group work, presentations, and formal examinations.
The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards achieving the intended learning outcomes.
Entry requirements
Typical offer for 2024/25 entry.
Fees and funding
2024/25 tuition fees.
| Student | Full-time | Part-time |
|---|---|---|
| UK, Ireland*, Channel Islands or Isle of Man | £11,200 | Not available |
| EU | £11,200 per year with EU Support Bursary** £20,050 per year without EU Support Bursary** |
Not available |
| International | £20,050 | Not available |
For advice and guidance on tuition fees3 and student loans visit our Postgraduate Finance page and see the university's Tuition Fee and Refund Terms and Conditions.
We offer a range of International scholarships to students all over the world. For more information, visit our International Scholarships page.
Tuition fees cover the cost of your teaching, assessments, facilities and support services. There may be additional costs not covered by this fee such as accommodation and living costs, recommended reading books, stationery, printing and re-assessments should you need them.
The following are additional costs not included in the tuition fees:
- Any optional overseas field trips or visits: £400+ per trip.
- Any costs associated with securing, attending or completing a placement (whether in the UK or abroad).
*Irish student fees
The rights of Irish residents to study in the UK are preserved under the Common Travel Area arrangement. If you are an Irish student and meet the residency criteria, you can study in England, pay the same level of tuition fees as English students and utilise the Tuition Fee Loan.
**EU Support Bursary
Following the UK's exit from the European Union, we are offering financial support to all eligible EU students who wish to study an undergraduate or a postgraduate degree with us full-time. This bursary will be used to offset the cost of your tuition fees to bring them in line with that of UK students. Students studying a degree with a foundation year with us are not eligible for the bursary.
How do you know if you need to pay UK or international tuition fees?
Facilities
Our aim is to offer you sector-leading facilities4:
Cisco lab
The Cisco lab is used for working with general networking and towards accreditation by Cisco. Optional modules allow students to work in the lab to develop skills in preparation for the Cisco certification exam.
Virtual labs
Our virtual labs provide a cutting-edge environment to create entire virtual networks, complete with services, users and even attackers. Students can access this environment from anywhere on or off campus.
Games Technology lab
This lab contains high-end gaming PCs with the capacity to run industry standard games engines and programming environments. It also supports Virtual Reality (VR) game development.
Careers and opportunities
Upon successful completion of this course, you should be able to:
- demonstrate systematic knowledge and critical understanding of core and advanced topics in data science and its theoretical foundations.
- design and evaluate computer systems for the storage, organisation, management, retrieval and processing of different types of information and sizes of datasets, including distributed systems.
- use an analytical approach, statistical thinking and a comprehensive understanding of appropriate models, methods, algorithms and software tools to analyse data of a variety of types, and identify the limitations of any analysis.
- demonstrate practical skills and capabilities related to employment, including working effectively and constructively as part of a team, leading a team, motivating and communicating complex ideas accurately to experts and non-experts, and technical expertise with modern data science tools and technologies.
- identify and apply appropriate practices within a professional, legal, social, cultural and ethical framework, including complex, inter-related, multi-faceted issues that can be found in a variety of organisations and professional contexts.
- apply research skills such as planning research, and critical analysis of information from appropriate sources, demonstrate awareness of current issues and show originality in the application of knowledge where appropriate.
Data Scientists are in short supply and there is high demand for data science skills across business, government, healthcare, science, finance, and marketing (to name a few).
Successful graduates of this course should be well prepared to join a team in an organisation related to their undergraduate discipline (contributing data analytics skills alongside their subject knowledge) or a specialist data science team in a more general organisation or consultancy.
Coventry University is committed to preparing you for your future career and giving you a competitive edge in the graduate job market. The university's Talent Team provide a wide range of support services to help you plan and prepare for your career.
How to apply
UK students
International students
Disclaimers
