Data Science and Computational Intelligence MSc

Study level: Postgraduate
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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

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

EECT044

Start date

September 2025
November 2025
January 2026
March 2026
May 2026
June 2026


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. 
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5 QS Stars for Teaching and Facilities

QS Stars University Ratings

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Ranked 11th Modern University in UK by the Times

The Times and Sunday Times Good University Guide 2025

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Ranked 8th for Overall Satisfaction in PTES

Postgraduate Taught Experience Survey (PTES) 2024

Why you should study this course

  • Get an in-depth understanding of a broad range of concepts, algorithms, models, applications, and issues in data science and computational intelligence.
  • Engage deeply with complex challenges in natural language processing, reinforcement learning, computer vision, big data management and statistical modelling.
  • Learn about critical legal, ethical, social and professional aspects, including responsible AI use, bias mitigation, data protection, transparency and sustainability.
  • 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.
  • Gain practical experience and boost your CV with an additional professional placement. See the modules for more details.

Accreditation and professional recognition

Chartered Management Institute (CMI)

This course is designed to include the criteria set out by the Chartered Management Institute (CMI) for the CMI Level 7 Certificate in Strategic Management and Leadership Practice. It is expected that students who successfully pass the module The Data Science Professional will be eligible to be considered by CMI for the award as an additional qualification.

This module is undergoing assessment by the CMI to confirm that all criteria are met to the required standard and therefore, until this assessment is completed, remains subject to accreditation. Should CMI accreditation not be received by the time you are due to study this module we will write to you to confirm this status.



What you'll study

You will have the opportunity to specialise yourself 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

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.

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.

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.

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 2025/26 fees TBC
2024/25 fees - £11,200 | £4,000 (work placement option additional fee)  
Not available
EU 2025/26 fees TBC
2024/25 fees - £11,200 | £4,000 (work placement option additional fee) per year with EU Support Bursary**
2025/26 fees TBC
2024/25 fees - £20,050 | £4,000 (work placement option additional fee) per year without EU Support Bursary**
Not available
International 2025/26 fees TBC
2024/25 fees - £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

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.

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Lanchester Library

The library is usually open 24/7, in term-time. 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.

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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.

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Careers and employability

Get one-on-one career and employability guidance lasting up to 36 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 seek positions as:

  • artificial intelligence engineer
  • artificial intelligence scientist
  • machine learning engineer
  • data scientist
  • data analyst
  • data engineer
  • data architect
  • data analytics specialist
  • database administrator
  • deep learning engineer
  • ai software developer
  • computer vision engineer
  • natural language processing engineer.

 

On successful completion of this course, you will be able to:

  • demonstrate systematic knowledge and critical understanding of core and advanced topics in data science and computational intelligence and their theoretical foundations, such as machine learning, deep learning, natural language processing, computer vision, data management and statistical modelling.
  • 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.
  • demonstrate a comprehensive understanding of appropriate data science methods, practices, algorithms and software tools, and their limitations.
  • select and apply relevant knowledge and techniques to formulate and analyse real-world problems and issues in computational intelligence, both systematically and creatively, including in complex and uncertain environments.
  • demonstrate practical skills and capabilities related to employment, including working effectively and constructively as part of a team, and motivating and communicating complex ideas accurately to experts and non-experts.
  • identify and apply appropriate practices within a professional, legal, social, cultural, ethical and risk management 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 evaluation and analysis of information from appropriate sources, demonstrate awareness of current issues and show originality in the application of knowledge where appropriate.
  • critically evaluate the principles for leading and developing people and entrepreneurial practice in strategic contexts.

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

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