Data Science and Computational Intelligence MSc

Postgraduate

This course uses a blend of theory and hands-on practical elements to explore advanced models and techniques for addressing large-scale, complex and dynamic data challenges.

Year of entry

2025-26 2026-27

Location

Coventry University (Coventry)

Study mode

Full-time
With Professional Placement

Duration

1 year full-time
Up to 2 years full-time with professional placement

Course code

EEST038

Start date

September 2026
November 2026
January 2027
March 2027
May 2027
July 2027

How to apply

Book an Open Day

Postgraduate events

Course overview

There is a 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.

Study topics in big data management, data protection and data ethics, statistical modelling, machine learning, deep learning, computer vision, natural language processing, generative AI and reinforcement learning.
Explore how data science can be used to extract meaningful insights from both structured and unstructured data, leveraging concepts and tools from mathematics, statistics, computer science, machine learning and related disciplines.
Learn about computational intelligence and how it plays a pivotal role in solving complex problems and simulating human-like intelligence in computational systems.

5 QS Stars for Teaching and Facilities

QS Stars University Ratings

Voted 1st in West Midlands for Postgraduate

Whatuni Student Choice Awards 2025

Ranked 4th for Overall Satisfaction in PTES

Postgraduate Taught Experience Survey (PTES) 2025

Why you should study this course

Comprehensive technical knowledge - get an in-depth understanding of a broad range of concepts, algorithms, models, applications, and issues in data science and computational intelligence.
Advanced AI applications - engage deeply with complex challenges in natural language processing, reinforcement learning, computer vision, big data management and statistical modelling.
Ethics and responsibility - learn about critical legal, ethical, social and professional aspects, including responsible AI use, bias mitigation, data protection, transparency and sustainability.
Research-informed teaching - study a course that has been designed in collaboration with Coventry University’s Centre for Computational Science and Mathematical Modelling. Our current research staff are involved in teaching some modules, supervising student projects and using current research to inform curriculum content.
Professional placement opportunity - gain practical experience and boost your CV with an additional professional placement. See the modules for more details.²

Ranked 8th

for overall satisfaction in Computing

Postgraduate Taught Experience Survey (PTES) 2025 (ranked out of 67 HEIs)

Accreditation and professional recognition

Chartered Management Institute

The module The Data Science Professional meets the criteria set by the Chartered Management Institute (CMI) for the CMI Level 7 Certificate in Strategic Management and Leadership Practice. Students who successfully pass this module will be eligible to gain the award as an additional qualification at no additional cost.

I’m really enjoying the Data Science and Computational Intelligence MSc programme, especially learning from the experienced professors at Coventry University’s Centre for Computational Science and Mathematical Modelling whose expertise and passion make the experience both very rigorous and inspiring. The programme not only offers classes on classical ML but also has a strong focus on cutting edge areas like Generative AI. All in all a full stack AI programme.
Mohammed Khan - Postgraduate student (2026)

Female sitting in a dark room working on a laptop

What you'll study

You will have the opportunity to specialise in a range of topics. This includes how you can use machine learning and statistical modelling to extract insights from data (structured and unstructured), the use of generative AI and its applications, the exploration into the latest advancement in deep learning and more.

Modules

Machine Learning and Statistical Modelling – 30 credits

Review the fundamental concepts of probability and statistics and develops deeper understanding of statistical models, estimation, inference and stochastic processes. Survey a range of statistical and machine learning models (including supervised learning and unsupervised learning) with applications to real-world datasets. Consider techniques for model evaluation and discuss wider modelling issues such as bias, fairness, under/overfitting, interpretability and scalability.

Build a solid foundation in both statistical methods and modern machine learning techniques, equipping you with a versatile skill set. Apply statistical and machine learning models to practical, real-world datasets. Use industry-standard tools⁴ and techniques for model evaluation, validation and optimisation, ensuring you are prepared for real challenges in data science.

Compulsory

Deep Learning and Computer Vision – 30 credits

Develop fundamental concepts, algorithms and architectures of artificial neural networks, deep learning and image processing. These fundamentals are applied and integrated in a broad range of real-world applications with a particular focus on practical and computational challenges in computer vision. This module will provide an in-depth exploration of the latest advancements in deep learning and computer vision. It aims to offer practical experience with real-world applications, enabling you to work on projects that involve building and deploying deep learning models for computer vision tasks.

Compulsory

The Data Science Professional – 30 credits

This module aims to provide you with sound knowledge of the theoretical and practical underpinnings of the management of big data in centralised and distributed environments. There is a strong emphasis on data engineering, data protection (including GDPR), data governance and data ethics. The module also develops practical skills in data management (such as SQL and NoSQL databases), cloud and distributed computing, and leadership in a data science context.

This module is designed to include the criteria set out by the CMI for the CMI Level 7 Certificate in Strategic Management and Leadership Practice¹.

Compulsory

Generative AI and Reinforcement Learning – 30 credits

Build knowledge and understanding of the concepts, algorithms, limitations and challenges of such artificial intelligence technologies, alongside developing practical skills implementing and experimenting with these systems. This module covers advancements in generative AI and reinforcement learning, equipping students with knowledge of technologies that are revolutionising various industries. It emphasises hands-on projects where you can implement generative models and reinforcement learning algorithms, ensuring you gain real-world experience and technical proficiency. It also provides insights into diverse applications of AI across fields such as natural language processing and autonomous systems, preparing students for versatile career opportunities.

Compulsory

Master’s with professional placement

If you successfully secure a placement in industry within your first semester, this master’s with professional placement option allows you to extend your 12-month master’s course up to an additional year to complete the placement before starting your final 60-credit module.

Gain valuable industry insights and skills as you apply your academic knowledge and skills to a professional placement.
The placement must be sourced and secured by you during your first semester. Our careers and employability team are available to support you with the sourcing process.
Start your professional placement after completing the first 120 credits of your course.
The professional placement will be integrated into your course learning and outcomes. This will take the form of a reflective diary demonstrating your learning and engagement with the placement experience.
The professional placement option is subject to additional fees, living costs, visa requirements, availability, competitive application and university approval of the placement.²

For full terms and conditions please visit the enhanced master’s landing page.

Optional

Individual Research Project – 60 credits

The aim of this module is to equip you with the necessary skills and knowledge to undertake independent research, culminating in the production of a dissertation. It will provide a comprehensive understanding of research methodologies, data collection, analysis, and interpretation techniques. The module should develop your ability to structure and write a coherent dissertation, manage your time effectively, and adhere to academic integrity standards

Compulsory

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 - provide a strong foundation in core theories, algorithms and computational models underpinning data science and AI, helping you understand both the mathematics and real-world applications behind intelligent systems.
seminars - encourage critical discussion of emerging topics such as machine learning advances, ethical AI and big data challenges, helping you evaluate research and industry developments in depth.
tutorials - offer focused support to strengthen your understanding of complex concepts such as statistical modelling or optimisation techniques, with opportunities for personalised feedback.
presentations - develop your ability to communicate technical findings clearly to both technical and non-technical audiences - an essential skill in data-driven organisations.
group projects - simulate real-world data science teams, enabling you to collaborate on problem-solving, model development and data analysis while building teamwork and project management skills.
workshops - provide hands-on experience with programming tools, machine learning frameworks and data processing techniques, allowing you to apply theory to practical challenges.
practical laboratory sessions - enable you to design, implement and test algorithms using real datasets, building technical confidence in coding, experimentation and model evaluation.

Teaching contact hours

As a full-time postgraduate student, you will study modules totalling 180 credits each academic year. A typical 30-credit module requires a total of 300 hours of study. Study hours are made up of teaching contact hours, and guided and independent study.

Teaching hours

Teaching hours may vary, depending on where you are in your studies, but on average you will have between 8 and 12 teaching and learning hours each week. You will also have the opportunity to attend optional sessions including time with a Success Coach or to meet with staff for advice and feedback.

Guided and independent study

Throughout your studies, you will be expected to spend time in guided and independent study to make up the required study hours per module. You will be digging deeper into topics, reviewing what you’ve learnt and completing assignments. This can be completed around your personal commitments. As you progress to the end of your studies, you’ll spend more time on independent learning.

Online learning

As an innovative university, we use different teaching methods, including online tools and emerging technologies. So, some of your teaching hours and assessments may be delivered online.

Assessment

This course will be assessed using a variety of methods which could vary depending upon the module. Assessment methods may include:

reports
tests
essays
practical coursework
assignments
vivas
presentations.

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.

Entry requirements

Typical entry requirements:

An honours degree 2:2 or above (or international equivalent) in a relevant discipline such as computer science, mathematics, statistics or engineering.

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

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 honours degree 2:2 or above (or international equivalent) in a relevant discipline such as computer science, mathematics, statistics or engineering.

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

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.

Fees and funding

Student	Full-time	Part-time
UK, Ireland*, Channel Islands or Isle of Man	£11,700 £1,575 professional placement fee (if placement secured)	Not available
EU	£11,700 per year with EU Support Bursary £1,575 professional placement fee (if placement secured) per year with EU Support Bursary £19,500 per year without EU Support Bursary £1,900 professional placement fee (if placement secured) per year without EU Support Bursary	Not available
International	£19,500 £1,900 professional placement fee (if placement secured)	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 Postgraduate Master's 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?

We assess your fee status using the information in your application. This status determines your tuition fees and the scholarships or financial support you can get. The Department for Education sets the rules for who pays UK (home) or international (overseas) fees in England.

The regulations list which students can pay the home fee rate. Because these rules are complex, the UK Council for International Student Affairs (UKCISA) provides fee status guidance to help you find the right category. If you meet all the criteria for one category, your institution must charge you the home rate.

Facilities

Sir Frank Whittle Building

Our Engineering, Environment and Science facilities boast modern, multifunctional teaching and research buildings that support hands-on learning. Laboratories and workshops are equipped to commercial and industrial standards and are available to students both in and out of class time (subject to availability).

Beatrice Shilling Building

The four-storey building is home to a host of facilities, including a gaming and virtual reality studio, a specialist area for 3D printing and rapid prototyping, a laser facility and physics and electronics laboratories. All learning spaces are designed around a full height central atrium to promote student and staff collaboration.

People walking in front of a building which has a big library sign

Lanchester Library

The library is usually open 364 days a year. It’s where you can access your course’s specialist Academic Liaison Librarian. It’s also home to specialist teams which can support you with your academic writing and maths and statistics questions.

Glass modern building with a spire in the background

The Hub

The Hub is the centre of student life on campus. Facilities include a food court, convenience store, multi-faith centre, medical centre, hairdresser, coffee shops and the Your SU offices. It has fully licensed function spaces and a bar.

Two people working together with a laptop in front of them

Careers and employability

Get one-on-one guidance lasting up to 18 months from the end of your course. We’ll help you find placements and graduate roles, offer CV and application checks, mentoring, skills workshops, employer events and more.

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.

Careers and opportunities

On successful completion of this course, you should be well qualified to apply your technical, research, programming, problem-solving and analytical skills across various sectors including technology, industry, business and government.

There could be career opportunities in AI research and development, machine learning, data management and data analysis. Potential employers include AI research institutions, major technology companies, tech startups, data science teams within businesses and government agencies, and professional consultancy firms.

On successful completion of this course, you may be able to seek positions as:

Data scientist - develop advanced skills in statistical modelling, machine learning and big data management. Practical laboratory sessions and group projects give you experience working with real datasets, building predictive models and communicating insights, all key requirements for data science roles.
Machine learning/AI engineer - through modules in computational intelligence, reinforcement learning and algorithm design, you should gain both theoretical understanding and hands-on implementation skills needed to build, test and optimise intelligent systems.
Data analyst/business intelligence analyst - training in data analytics, visualisation and interpretation prepares you to extract actionable insights from complex datasets. Presentations and applied projects help you develop the ability to explain findings clearly to decision-makers.
Computer vision or NLP specialist - engage with advanced topics such as natural language processing and computer vision, supported by practical experimentation in labs. This prepares you for specialist AI roles in areas like automation, robotics or language technologies.
AI ethics and governance specialist - the course explores legal, ethical and professional issues including responsible AI use, bias mitigation and transparency. This supports emerging roles focused on AI regulation, compliance and responsible innovation.

The graduate destinations listed above illustrate potential career paths. You may need to gain additional qualifications or practical experience, pass professional examinations, complete training, cover associated costs and meet specific visa or immigration requirements to secure employment in these fields.

Where our graduates work

Successful graduates of this course have gone on to work for companies managing cutting-edge projects in data science, artificial intelligence and computational intelligence.

How to apply

UK students

To apply to study for a postgraduate course at Coventry University, you can apply online. Please read the entry criteria page before applying.

Start your application

For further support or more information about your course get in touch with us today.

+44 (0)24 7765 6565

ukadmissions@coventry.ac.uk

Complete our contact form.

International students

Full-time international students should apply directly to the university. Please read our application pages to find out your next steps to apply.

How to apply

For further support for international applicants applying for postgraduate degrees view our International hub.

You can also download our international mini guide for an overview of study options and why you should study with us.

Get in touch with us today for further advice and guidance.

+44 (0)24 7765 6565

applications.io@coventry.ac.uk

Complete our contact form.

Disclaimers

Coventry University, 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.

¹Accreditations, partnerships and memberships

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. See the relevant body website for more details). Accreditations, partnerships, exemptions and memberships are subject to successful renewal in accordance with the relevant bodies’ standard review process and subject to the university maintaining the same high standards of course delivery. If the accreditation, recognition or membership of this course changes, we will seek to notify applicants and students as soon as possible.

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, guest speakers, 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 annually, but such increases will be no more than 5% above the inflation rate. If you defer your course start date or extend your studies beyond the normal duration of the course (for example, 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.

⁴Facilities

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 2025/2026 contract is available on the website for information purposes however the 2026/2027 contract will apply for the 2026/2027 intake. 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.