Data Science MSc

Study level: Postgraduate
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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



Coventry University (Coventry)

Study mode



1 year full-time
2 years part-time

Course code


Start date

September 2024
January 2025
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.
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Joint Top Modern University for Career Prospects

Guardian University Guide 2021 and 2022

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5 QS Stars for Teaching and Facilities

QS Stars University Ratings

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Top 5 UK Student City in England (Coventry)

QS Best Student Cities Index 2024

Why 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

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.

CWLEP chair upskills with data science course

Technology entrepreneur Sarah Windrum believes Coventry University’s Data Science MSc course will help her business and aid her role as Chair of the Coventry and Warwickshire Local Enterprise Partnership (CWLEP).

Discover how the course is helping Sarah
Sarah Windrum

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.

This MSc Data Science course is composed of a combination of modules that cover a broad range of data science methods, applications, and foundations.

In the first semester, you will study two 30-credit modules which aim to introduce you to data science, provide you with an opportunity to develop skills in computer programming, build expertise in data analysis, and establish mathematical foundations. Additional one-to-one support is available through the sigma Mathematics and Statistics Support Centre (subject to availability).

In the second semester, you will study four 15-credit modules which aim to broaden your knowledge in the application areas in data management systems, machine learning and big data. These modules respond to different challenges in data management and data analysis. Within these modules, a wide range of types and scales of data and data analysis methods will be introduced and applied, from supervised and unsupervised learning to the analysis of text documents.

In the final semester, you will be expected to apply the knowledge and skills you have learned in the first two semesters by undertaking an in-depth individual Data Science project. This may be on some current issue or challenging application in data science and could be industry-based or undertaken in collaboration with one of the university research groups. Guided by a university tutor, this project helps you to develop your research and practical skills while also gaining professional Data Science experience.


  • This module aims to provide a broad overview of data science and to develop essential skills in computer programming for data science applications. It will cover the nuts and bolts of procedural and object-oriented programming in a high-level programming language, including the design, development and testing of code.


  • While data science tools and technologies are evolving rapidly, this module aims to build foundational knowledge and understanding of the mathematical concepts, statistical models, and data analytics skills at the heart of data science.


  • Organisations and businesses are being inundated with very large volumes of data - structured and unstructured - on a daily basis. These data are too big and complex for processing and analysing them using well-known traditional methods. This module aims to introduce you to the current management and visualisation methods for Big Data. Cutting-edge techniques will be taught which should enable you to discover patterns, relationships and associations in big data sets.


  • The aim of this module is to provide you with a sound knowledge of the theoretical and practical underpinnings of data management systems in centralised and distributed environments.


  • The Individual Research Project is a substantial piece of research in an area of study chosen by the student, under guidance from a supervisor and with relevance to their degree course. In this preparatory module, you will identify a suitable topic of study and project supervisor. You will then exercise and extend your skills in gathering, understanding and critically evaluating literature; assessing and acting on relevant ethical and legal issues; and applying planning processes for the undertaking of a significant piece of work.


  • This module provides you with an introduction to machine learning techniques, the associated concepts, and applications.


  • This module aims to provide you with a framework of knowledge and understanding of how to effectively lead and develop people in a strategic and entrepreneurial way.


  • The project is intended to provide you with the opportunity to demonstrate competence in applying the concepts and skills acquired during the taught part of the course. You will apply a level of intellectual rigour which is commensurate with the standard of your master’s level programme of study.


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

This course can be studied on a full-time or part-time basis. While we would like to give you all the information about our part-time offering here, it is tailored for each course each year depending on the number of part-time applicants. Therefore, the part-time teaching arrangements vary. Please request information about studying this course part-time.

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.


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.

An applicant will normally be expected to possess at least one of the following:

  • An honours degree or equivalent qualification.
  • An unclassified degree in a relevant field plus professional experience.

In addition, applicants will need a little knowledge of computer programming. Applicants from non-programming backgrounds are encouraged to take part in a free online course* with the aim of bringing their knowledge of programming and basic data science topics up to the required level for successful application.

Each application will be considered on its merits and the final decision will be made by the Course Director.

*The Get ready for a master’s in Data Science and AI course is available on our FutureLearn platform and is free to access for a limited time when you select the ’Limited Access’ subscription option. (Please note, this online Platform Provider may be subject to change.)

We recognise a breadth of qualifications, speak to one of our advisers today to find out how we can help you.

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Select your region to find detailed information about entry requirements:

You can view our full list of country specific entry requirements on our Entry requirements page.

Alternatively, visit our International hub for further advice and guidance on finding in-country agents and representatives, joining our in-country events and how to apply.

Typical entry requirements

An applicant will normally be expected to possess at least one of the following:

  • An honours degree or equivalent qualification.
  • An unclassified degree in a relevant field plus professional experience.

In addition, applicants will need a little knowledge of computer programming. Applicants from non-programming backgrounds are encouraged to take part in a free online course* with the aim of bringing their knowledge of programming and basic data science topics up to the required level for successful application.

Each application will be considered on its merits and the final decision will be made by the Course Director.

*The Get ready for a master’s in Data Science and AI course is available on our FutureLearn platform and is free to access for a limited time when you select the ’Limited Access’ subscription option. (Please note, this online Platform Provider may be subject to change.)

English language requirements

  • IELTS: 6.5 overall, with no component lower than 5.5.

If you don't meet the English language requirements, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course. 

For more information on our approved English language tests visit our English language requirements page.

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Fees and funding

2024/25 tuition fees.

Student Full-time Part-time
UK, Ireland*, Channel Islands or Isle of Man £11,200   Request fee information
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.

  • We carry out an initial fee status assessment based on the information you provide in your application. Your fee status determines your tuition fees, and what financial support and scholarships may be available to you. The rules about who pays UK (home) or international (overseas) fees for higher education courses in England are set by the government's Department for Education. The regulations identify all the different categories of student who can insist on paying the home rate. The regulations can be difficult to understand, so the UK Council for International Student Affairs (UKCISA) has provided fee status guidance to help you identify whether you are eligible to pay the home or overseas rate.

    If you meet all the criteria required by any one category, including any residence requirements, your institution must charge you the home rate. You only need to find one category that you fit into.


Our aim is to offer you sector-leading facilities4:

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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.

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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.

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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

  • Coventry University together with Coventry University London, Coventry University Wrocław, CU Coventry, CU London, CU Scarborough, and Coventry University Online come together to form part of the Coventry University Group (the University) with all degrees awarded by Coventry University.


    The majority of our courses have been formally recognised by professional bodies, which means the courses have been reviewed and tested to ensure they reach a set standard. In some instances, studying on an accredited course can give you additional benefits such as exemptions from professional exams (subject to availability, fees may apply). Accreditations, partnerships, exemptions and memberships shall be renewed in accordance with the relevant bodies’ standard review process and subject to the university maintaining the same high standards of course delivery.

    2UK and international opportunities

    Please note that we are unable to guarantee any UK or international opportunities (whether required or optional) such as internships, work experience, field trips, conferences, placements or study abroad opportunities and that all such opportunities may be unpaid and/or subject to additional costs (which could include, but is not limited to, equipment, materials, bench fees, studio or facilities hire, travel, accommodation and visas), competitive application, availability and/or meeting any applicable travel, public authority guidance, decisions or orders and visa requirements. To ensure that you fully understand any visa requirements, please contact the International Office.

    3Tuition fees

    The University will charge the tuition fees that are stated in the above table for the first Academic Year of study. The University will review tuition fees each year. For UK (home) students, if Parliament permit an increase in tuition fees, the University may increase fees for each subsequent year of study in line with any such changes. Note that any increase is expected to be in line with inflation.

    For international students, we may increase fees each year, but such increases will be no more than 5% above inflation. If you defer your course start date or have to extend your studies beyond the normal duration of the course (e.g. to repeat a year or resit examinations) the University reserves the right to charge you fees at a higher rate and/or in accordance with any legislative changes during the additional period of study.


    Facilities are subject to availability. Access to some facilities (including some teaching and learning spaces) may vary from those advertised and/or may have reduced availability or restrictions where the university is following public authority guidance, decisions or orders.

    Student Contract

    By accepting your offer of a place and enrolling with us, a Student Contract will be formed between you and the university. A copy of the current 2023/2024 contract is available on the website for information purposes however the 2024/25 Contract is currently being updated so please revisit this page before submitting your application. The Contract details your rights and the obligations you will be bound by during your time as a student and contains the obligations that the university will owe to you. You should read the Contract before you accept an offer of a place and before you enrol at the university.

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