Data Science MSc 2021/22 entry

Course code:


Study options:

1 year full-time
2 years part-time

How to Apply

Coventry University (Coventry)


January 2022



Get in touch

Course code:


Study options:

1 year full-time
2 years part-time

How to Apply

Coventry University (Coventry)


January 2022



Get in touch


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.

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.

Gaining useful insights from data involves logical thinking, technical skills and deep knowledge of the domain the data comes from. Graduates from Law, Finance, Marketing, Business, Creative Arts, Social Sciences, Linguistics, Health Sciences, Sports Science, Psychology, Geography, Biological Sciences and Engineering (to name a few) are best placed to analyse data from their own discipline and bring a unique perspective (and set of questions) to a data science team.

The MSc Data Science is designed to support students with little previous experience of data analysis or computer programming to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation; and addressing the challenges of big data.

These 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 backgrounds, experience and perspectives, and gaining broad experience of working with a variety of types of data to address diverse and interesting questions.

Why Coventry University?

An award-winning university, we are committed to providing our students with the best possible experience. We continue to invest in both our facilities and our innovative approach to education. Our students benefit from industry-relevant teaching, and resources and support designed to help them succeed. These range from our modern library and computing facilities to dedicated careers advice and our impressive Students’ Union activities.


The University may deliver certain contact hours and assessments via emerging online technologies and methods across all courses. In response to the COVID-19 pandemic, we are prepared for courses due to start in or after the 2020/2021 academic year to be delivered in a variety of forms. The form of delivery will be determined in accordance with Government and Public Health guidance. Whether on campus or online, our key priority is staff and student safety.

Due to the ongoing restrictions relating to COVID-19, some facilities (including some teaching and learning spaces) and some non-academic offerings (particularly in relation to international experiences), may vary from those advertised and may have reduced availability or restrictions on their use.

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Sarah Windrum

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).

Course information

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 information retrieval, 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; information retrieval and analysis of textual data; machine learning algorithms for learning from data; and a range of data science applications, tools, projects and current issues.

Course Specification



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 introduce you to data science, 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.

In the second semester, you will study four 15-credit modules which will broaden the application areas in information retrieval, 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 an expert tutor, this project helps you to develop your research and practical skills while also gaining professional Data Science experience. The course also includes the Consulting Global Professional Development module developed in partnership with the Chartered Management Institute.


  • Semester One:

    • Programming for Data Science (30 credits)
    • Principles of Data Science (30 credits)

  • Semester Two:

    • Big Data Management and Data Visualisation (15 credits)
    • Data Management Systems (15 credits)
    • Information Retrieval (15 credits)
    • Machine Learning (15 credits)

  • Semester Three:

    • Global Professional Development – Consultancy (10 credits)
    • Data Science Project (50 credits)

In more detail...

  • Foundational skills in computer programming, data analysis and mathematics are developed alongside hands-on use of data science software tools and working on data science applications.
  • Learn alongside students with different backgrounds, experience and perspectives, on a variety of types of data using a range of different data analysis methods and tools.
  • Researchers from the Centre for Data Science at Coventry University will be involved in teaching on the course and in supervision of individual Data Science projects.
  • Students will have many opportunities to work with data addressing a wide variety of disciplines and interests.
  • There will be an opportunity for those from underrepresented in the field of data science to apply for scholarships (further details to follow).

Main study themes:

  • Develop skills across the data science project lifecycle: Different parts of a typical end-to-end data science project require different skills, from formulating questions and sourcing and cleaning data, through exploring, visualising and modelling data, to interpreting results and communicating the findings.
  • Apply modern data science tools but also build deeper foundations: Because the technology and tools surrounding data science are evolving at a very fast rate, the course also develops knowledge and understanding of specialist methods and algorithms in machine learning, data analysis, and mathematical language and foundations.
  • Develop an analytical approach and a feel for data: Through experience working with different types of data, methods and applications, the course will equip students with the ability to break down complex problems and apply statistical thinking.

The course can be studied full-time over a calendar year or part-time over two years.

Teaching methods include a combination of lectures, problem-solving workshops, supervised computer laboratory sessions, in-class discussions and presentations, directed reading and formative assessments.

There may be opportunities to attend external talks and visiting guest lectures (subject to availability).

This course will be assessed using a variety of methods which will could vary depending upon the module. Assessment methods include coursework, tests, reports, projects, group work, presentations and formal examination.

The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards the achieving the intended learning outcomes.

One successful completion of the course, you will 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.

Taught modules on the MSc Data Science will be delivered in a block teaching style (meaning that all teaching for the module will be consolidated into a condensed number of weeks).

A 15-credit module will typically have about 30 hours of contact time associated with it, while a 30-credit module will have approximately 60 hours of contact time. This will include a combination of, but may not be limited to, lectures, small-group sessions, laboratory session and support sessions. In addition, you will be expected to undertake significant self-study 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. 

If you have a desire to travel, it is possible to spend a period abroad for part of your studies, for as little as two weeks. We also offer you the chance to participate in field trips to a number of different overseas locations, which have previously included China, Poland, Spain and Finland.

*Please note that we are unable to guarantee any trip, event, internship, placement or study abroad opportunities and that all such opportunities may be subject to additional costs (e.g. travel, visas and accommodation etc.), competitive application, availability and/or meeting any applicable visa requirements. To ensure that you fully understand the requirements in this regard, please contact the International Office for further details if you are an EU or International student.

Entry Requirements

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

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

In addition, applicants will need some 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. For information regarding specific entry requirements, please contact

* The Get ready for a Masters in Data Science and AI course will be available on the FutureLearn platform and is expected to run over two weeks from 16 August 2021, with approximately 10 hours of content per week.

Select your region to find detailed information about entry requirements:

Pre-sessional English This course requires IELTS 6.0. Pre-sessional English is available if required.

Our International Student Hub offers information on entry requirements for your country, as well as contact details for agents and representatives should you need more advice.

More detail

Tuition Fees

We pride ourselves on offering competitive tuition fees which we review on an annual basis and offer a wide range of scholarships to support students with their studies. Course fees are calculated on the basis of what it costs to teach each course and we aim for total financial transparency.



January 2022

£10,400 (per year)

UK Scholarships

If you're a truly outstanding undergraduate candidate we may be able to offer you a Coventry University Scholarship. Coventry University Scholarships are awarded to recognise truly exceptional sports achievement and academic excellence.



January 2022

£17,900 (per year)


If you're a truly exceptional candidate we may be able to offer you a Coventry University Scholarship. Coventry University Scholarships are awarded to recognise truly exceptional achievement and academic excellence.

This course may incur additional costs associated with any field trips, placements or work experience, study abroad opportunities or any other opportunity (whether required or optional), which could include (but is not limited to) travel, accommodation, activities and visas.

This course may incur additional costs associated with any equipment, materials, bench fees, studio or facilities hire.

Career prospects

Graduate Immigration Route visa

Based on current information from the UK Government, international students whose study extends beyond summer 2021 may be eligible for a visa under the UK Government’s Graduate Immigration Route, which will enable students to stay and work, or look for work, in the UK at any skill level for up to two (2) years. Check the most up to date guidance available to check your eligibility and any updates from the UK Government before making an application or enrolment decision.

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).

As a graduates of this course you will be well prepared to join a team in an organisation related to your 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. 


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 2021/22 Contract can be found here. 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.

The tuition fee for the course that is stated on the course webpage and in the prospectus for the first year of study will apply. We will review our tuition fees each year. For UK and EU students, if Parliament permit an increase in tuition fees, we 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. Following the UK’s exit from the European Union, EU students should be aware that there may be a change to UK laws following the UK’s exit, this may change their student status, their eligibility to study part time, and/or their eligibility for student finance. We will act in accordance with the UK’s laws in force in relation to student tuition fees and finance from time to time.

For International students the tuition fee that is stated on the course webpage and in the prospectus for the first year of study will apply. We will review our tuition fees each year. For international students, we may increase fees for each subsequent year of study but such increases will be no more than 5% above inflation.