Data Science and Computational Intelligence MSc

Study level: Postgraduate
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This master’s course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.

Year of entry

Location

Coventry University (Coventry)

Study mode

Full-time
Part-time
Sandwich

Duration

1 year full-time
2 years part-time
2 years sandwich

Course code

EECT044

Start date

January 2025
May 2025


Course overview

The main theme throughout this course is automatic big data analytics and natural language processing through machine learning, especially deep neural networks.

  • We aim to cover how to apply cutting-edge machine learning techniques to analyse big datasets, assess the statistical significance of data mining results and perform advanced data analytics.
  • We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with powerful languages such as Python and R.
  • We will look at emerging theories, practices, approaches, and management of distributed and intelligent computing systems, examining a wide range of case studies to see how applications have been developed and for what purposes, such as steganography detection system for colour stego images.
  • The focus of the course is on applications of data science methods and tools, combined with computational intelligence techniques for data-driven problem solving including the analysis, interpretation and visualisation of complex data, which is in increasing demand in fields such as marketing, pharmaceutics, finance, transportation, medicine, and management.
  • You will have the option to apply for a ‘work placement’ opportunity2, designed to further develop your skills and knowledge with the aim of maximising your employability prospects. See modules for more information.
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Rated Gold Overall

Teaching Excellence Framework (TEF) 2023

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5 QS Stars for Teaching and Facilities

QS Stars University Ratings

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Top 5 Student City in England (Coventry)

QS Best Student Cities Index 2025

Why you should study this course

Big data is enabling companies to unlock previously hidden information in areas ranging from customer behaviour to how their businesses function, providing vital insight that can affect the profitability and sustainability of an organisation.

  • In a world where technology is advancing at a rapid pace, data-driven scientific discovery represents one of the most exciting developments – already making a huge impact on the social and services sectors.
  • This course is designed to equip you with the skills and expertise in the emerging big data mining techniques required for the analysis, interpretation and visualisation of complex, high-volume, high-dimensional, structured and unstructured data from a variety of sources.
  • We aim to provide an understanding of data science and computational intelligence, including specialist knowledge in machine learning, neural networks, data mining, and Natural Language Processing (NLP), as well as important development tools and platforms.
  • Through practical activities, industry input and a focus on skills development, we seek to foster an informed, flexible and critical approach to problem-solving, giving you the confidence, professionalism, knowledge and skills to adapt to modern technological environments.
  • Enjoying high levels of student satisfaction for our teaching, we offer modern facilities4 alongside the utilisation of industry-standard software and collaboration coding platforms, such as Github.
  • You will be given the chance to work alongside staff currently conducting research in the fields of deep learning, NLP, distributed systems and modelling, computer vision, digital security and forensics, and biomedical technologies. (Please note that staff may be subject to change).

What you'll study

Over the course of your studies, you will study several mandatory modules.

Ultimately, you will be expected to apply the knowledge and skills you have learned by undertaking an in-depth individual project which may be industry-based or undertaken in collaboration with one of the university research groups2. Guided by an expert tutor, this project helps to develop your research and practical skills while also gaining professional data science experience.

Past student projects have included analysing big data for the movie industry; helping in assessing oil wells to evaluate extraction costs; recognising customer emotion through face gestures; analysing text sentiment in a social media exchange; performing automatic scene labelling and object recognition; and designing a robotics controller for helping the elderly.

Modules

With work placement pathway

The ‘With work placement’ opportunity2 enables you to apply in semester 1 for an optional work placement of up to 12 months, extending the duration of your master’s to 24 months. The placement provides an opportunity for you to develop expertise and experience in your chosen field with the aim of enhancing your employability upon graduation. The work placement would take place in semesters 3, 4 and 5.

Please note that the optional placement modules will incur an additional tuition fee of £4,000. Placement opportunities may also be subject to additional costs, visa requirements being met, subject to availability and/or competitive application. Work placements are not guaranteed but you will benefit from the support of the Talent Team in trying to find and secure an opportunity. Find out more about the work placement option.

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:

  • Lectures
  • Seminars
  • Tutorials
  • Presentations
  • Group projects
  • Workshops
  • Practical laboratory sessions

This course can be studied on a full-time or part-time basis. Whilst 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

The number of contact hours may vary from semester to semester, however, on average, it is likely to be around 12 contact hours per week in the taught semesters.

Additionally, you will be expected to undertake significant self-directed study of approximately 35 hours each week, depending on the demands of individual modules.

Your project-based semester will be supervisor supported, self-directed study in the region of 45 hours per week as well as supervisor meetings around 0.5 hours per week.

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, essays, projects, group work and formal examination.

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


International experience opportunities

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 trips2 to several different overseas locations, which have previously included China, Poland, Spain and Finland.

 


Entry requirements

Typical offer for 2024/25 entry.

Applicants for this programme will normally be expected to possess a minimum of a second class honours degree in computer science, mathematics or other relevant discipline.

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.

If you do not have the typical entry requirements, you may want to consider studying this course with an international pre-master's. Upon successful completion our International Pre-Master's - Computing will provide you with the knowledge and skills you need to progress onto this postgraduate degree.

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.

English language requirements

  • IELTS: 6.5 overall (with at least 5.5 in each component area)

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 | £4,000 (Work placement option additional fee)   Request fee information
EU £11,200 | £4,000 (Work placement option additional fee) per year with EU Support Bursary**
£20,050 | £4,000 (Work placement option additional fee) per year without EU Support Bursary**
Not available
International £20,050 | £4,000 (Work placement option additional fee)   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.


Facilities

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

On successful completion, you will have knowledge of:

  • The fundamental principles and techniques of data science and computational intelligence.
  • Analysing complex, high-volume, high-dimensional, structured/unstructured data from varying sources.
  • The combination of theory and practical application of data science and computational intelligence methods and techniques.
  • Professional, legal, social, cultural and ethical issues related to data science, computational intelligence and an awareness of societal and environmental impact.

On successful completion, you will be able to:

  • Critically evaluate current research problems and apply cutting-edge developments of data science and to computational intelligence areas.
  • Critically evaluate a range of possible options solutions or architectures to address a sizeable data application and present a soundly reasoned justification for the final solution.
  • Demonstrate competence, creativity, and innovation in solving unfamiliar problems.
  • Effectively communicate outcomes from major projects to technical and non-technical audiences. Select and apply relevant knowledge and skills in big data applications using relevant tools and technologies.
  • Identify and make effective and systematic use of a range of suitable techniques for developing solutions to complex data and analytical problems.

Opportunities following successful completion of this course could include careers as data scientists, data professionals and data analysts in variety of sectors including financial services, retail, marketing, customer and business intelligence.

Where our graduates work

This master’s course aims to provide you with the analytical tools to construct more desirable technical solutions using advanced computational methods, with an emphasis on rigorous statistical reasoning. As a result, on successful graduation, you should gain the skills for roles in a wide range of sectors including finance, marketing, academia, scientific research, health and medicine, the retail market, information technology, government, ecommerce, energy, transportation, telecommunications, biotechnology and pharmaceutical companies.


How to apply