MSc Data Science & Artificial Intelligence

• Computational Modelling: You will gain a comprehensive understanding of cutting-edge computational modelling techniques and how they’re applied to complex systems. You'll explore the shift from traditional observation-based methods to modern, data-driven approaches using machine learning and neural computation, while also examining the tools used to identify, analyse, and evaluate models in brain-like systems and beyond.
• Machine Learning and Applications: You will build a solid foundation in machine learning, exploring both the theoretical and practical aspects from a computer science perspective. You'll learn the statistical and mathematical principles behind data analysis and processing, and examine the real-world applications of machine learning—along with its social, legal, and ethical implications.
• Language Models and Natural Language Processing (NLP): You will gain a comprehensive understanding of NLP principles and methodologies, with a focus on language models. You’ll explore the fundamentals of language modelling, the distinctions between small and large models, their applications, and challenges, while also delving into advanced NLP topics, emerging trends, and the ethical implications of language models.
• Computer Vision: You will gain a comprehensive understanding of Computer Vision (CV) principles, methodologies, and practical applications, with a focus on building and evaluating CV models. The unit covers both traditional and cutting-edge techniques, providing you with the tools needed to solve real-world problems using CV.
• Efficient and Edge AI: You will gain a comprehensive understanding of efficient edge AI technologies, focusing on the principles, methodologies, and applications of deploying AI models at the edge of networks. The unit will cover optimising the performance of edge AI systems, addressing the challenges and opportunities of implementing AI in edge devices, and develop your ability to design and implement efficient edge AI solutions.
• Research Methods in Data Science and AI: You will gain proficiency in research methodologies essential for data science and artificial intelligence, learning various methods and design techniques to tackle related problems. You will learn how to formulate research plans for diverse stakeholders, exploring ethical considerations, and adhering to professional standards. You'll also be prepared to write a project proposal and conduct and disseminate your Masters project.
• Individual Master's Project: You will develop a good understanding of the characteristics and implications which are inherent in the solution of a complex, real-world data science and AI oriented problem.  This will be achieved within the context of a substantial, independently conducted research and development work.

Programme specifications provide definitive records of the University's taught degrees in line with Quality Assurance Agency requirements. Every taught course leading to a BU Award has a programme specification which describes its aims, structure, content and learning outcomes, plus the teaching, learning and assessment methods used.

Whilst every effort is made to ensure the accuracy of the programme specification, the information is liable to change to take advantage of exciting new approaches to teaching and learning as well as developments in industry. If you have been unable to locate the programme specification for the course you are interested in, it will be available as soon as the latest version is ready. Alternatively please contact us for assistance.

For September 2025 and January 2026: The normal requirements for embarking upon a postgraduate taught degree are:

• A Bachelors Honours degree with 2:2 in a required subject, or equivalent.
• Required subject: Computing, Technology, Maths, Physics, Engineering, Data Sciences or Data Analytics

For September 2026 and January 2027 entry: A Bachelors Honours degree with 2:2 in a required subject, or equivalent: Computing, Computer Science, Mathematics, Statistics, Physics, Electronic Engineering, Data Sciences, Data Analytics or any subject with significant maths and computing content.

If you are in doubt if you lack the formal academic qualifications needed to enter a postgraduate or post-experience degree, please get in touch with the Future Students Enquiry team.

You can find details of the international qualifications we accept, and what level of study they apply to, on our entry requirements for non-UK students' page.

Please see below some examples of the qualifications for entry:

• India: Bachelor’s degree (three years) from a recognised HE institution with a minimum overall result of 55%  
• Nigeria: Bachelor's degree from a recognised institution with a minimum classification of 2:4  
• China: Chinese Bachelor's (Honours) degree from a recognised higher education institution with 65% or above  
• Turkey: Bachelor’s degree (Lisans Diplomasi - four years) with a minimum overall GPA of 2.3/4.0  
• Ghana: Bachelor's degrees from University of Ghana or Legon with a grade of 2.00 or above, or from Cape Coast with a grade 2.5 or above  
• USA: US Bachelor’s degree (four years), with a 2.5 GPA or above  

All applications will be subject to a minimum grade and your degree may need to be in a relevant subject area.

English language requirements

If English is not your first language, you will need to provide evidence that you understand English to a satisfactory level. English language requirements for this course are normally:

IELTS (Academic) 6.0 with minimum 5.5 in each component, or equivalent.

View further information about our English language requirements.

Bournemouth University International College offers a number of pre-sessional English and preparatory programmes to prepare international students for postgraduate study at BU. Admission to the degree is guaranteed on successful completion of your course to the required level. 

This course selects candidates by looking at their applications. There are no interviews or additional selection activities and therefore we suggest that you make your application stand out from the crowd. For more information take a look at our how to apply pages.

Please see our website for the application deadlines. You should apply as early as possible to be considered for your course of choice. If you require a student visa, apply for the visa as soon as you have an unconditional offer and receive your CAS. There may be delays in visa processing in your country and you need to be in Bournemouth ready to study for the start of term.

December and January is one of our busiest application periods and therefore it may take us a little longer to process incoming applications. For courses with a January start date, we recommend submitting your application as soon as possible to avoid disappointment.

Click the green ‘Apply now’ button to submit your application free of charge online through myHub, our application portal. You will create your own myHub account so that you can track the progress of your application. Don’t forget to save your application as you go; you can return to it at as many times as you want before you submit it. For more information visit our How to apply section.

After graduating, you could find yourself working in roles such as: 

• Data Engineering Specialist
• Data Science Specialist
• Artificial Intelligence Specialist
• Data Scientist
• Data Architect
• Data Analyst
• Machine Learning Engineer
• Machine Learning Scientist
• Machine Learning Researcher
• Big Data Developer
• Big Data Engineer
• Big Data Architect.

If you want to continue your studies after achieving your Master’s, you can look into our range of doctoral programmes.

What’s included in your tuition fee?

Your tuition fee covers expenses associated with your course including tuition materials, access to facilities, mandatory field trips and the following:

• Materials for laboratory and mandatory field-based teaching activity.
• Support for finding placements (UK or abroad) and fieldwork, and non-financial support whilst on placement if this is part of your course of study.
• A range of student services – advisors, help desks, counsellors, placement support and careers service.
• The Library – access to a wide range of electronic resources (databases, e-journals and e-books), print and multimedia collections, subject librarians and study spaces.
• Access to Brightspace, our virtual learning environment, which offers a responsive and personalised learning experience with powerful learning analytics
• IT labs (some open 24/7), wireless network, AV equipment to borrow.
• Disability and additional learning support, according to individual circumstances.
• 24 hours a day, 365 days a year security team.

Additional costs

We are committed to offering you value for money and ensuring there are no hidden costs while you are studying with us, therefore we have listed below any additional costs you may incur that are not covered by your tuition fee:

• Laptops, tablets and mobile devices and any software used on personal devices. Access to a personal computer is strongly recommended for your study. If you are experiencing financial difficulty, visit our website for information regarding hardship funds.
• ​Textbooks, general stationery and other supplies. Our award-winning library is stocked with a large range of textbooks and online resources, free of charge. The Students’ Union shop stocks a wide range of stationery supplies.
• Accommodation and living costs. Please visit our website for more information.
• ​Travel costs for optional field trips, outdoor wear and footwear for mandatory and optional field trips (if applicable).
• Travel costs to and from the University campus. An annual bus pass can be purchased alongside your rent if you are living in halls of residence/Unilet accommodation or may be purchased separately.
• ​Travel costs to and from your placement (both in the UK and overseas) if this is part of your course of study. Placement year funding information can be found on our website.
• Clothing or equipment costs required for your placement if this is part of your course of study. 
• SportBU membership.

While all aspects of the programme, including required field trips, are included in the fee, additional, optional or extra curricula activities may be available for which a student contribution is required.

We offer a range of scholarships to students who are beginning their studies at BU. Our fees and funding pages also provide details on living costs, budgeting and paying your tuition fees.

International (not Rep. of Ireland) students need to pay a non-refundable deposit to secure their place on a postgraduate course. You will need to pay your deposit by the date stated in your offer letter. The remainder of your fee will be payable on registration/enrolment. There are two exceptions to the non-refundable rule on the deposit:

• You fail to meet the academic or English requirements of your offer
• You are refused a visa to enter the UK, provided the reason for the refusal is not a fraudulent application.

Zoheir Sabeur is Professor of Data Science and Artificial Intelligence at Bournemouth University. His main research expertise is on AI, knowledge extraction, human behaviour and natural processes machine detection and understanding. This was applied to multiple domain sectors, including security, environment and healthcare. For example, in healthcare with human respiratory conditions such as COPD and Asthma and their exacerbation events forecast; in environment with the impact of climate change on species migratory behaviour; and in security with crowd behaviour detection and their rapid evacuation for safety.

He has published over 200 papers in scientific journals, conference proceedings and books. Zoheir is Fellow of the British Computer Society and also Fellow of IMarEST.

Marcin's research interests lie in a broadly understood area of machine learning and data science, with a particular focus on practical applications.

"Innovation is what makes our world a better place. I believe that deep down each of us is an innovator. The committed and inspiring team at BU will help you unlock this hidden potential".

Some of Marcin’s recent research projects include data analytics and predictive modelling for public transport, computer vision techniques for retail (self-checkout) and forensic applications (shoeprint and gait analysis) or link prediction in complex network systems (like social networks). Many of these projects involve students at various levels.

Dr Balaguer-Ballester is a physicist with expertise in Computational Neuroscience (neuronal coding and dynamics, ensemble models, auditory modelling); with a focus on machine learning approaches specifically designed for analysing neuronal responses and realistic models.

Hamid is a professor of Data Science & Intelligent Systems. His major research interests include Machine Learning and Computational Intelligence with a particular focus on online learning, semi-supervised, active learning and uncertainty modelling. Recently he has been focusing on distributed and large-scale machine learning as well as big data technologies.   

“Data is the 4th paradigm of scientific discovery and Artificial Intelligence, often referred to as “the new electricity” that drives innovation. Manifestly, demand for data science skills continues to grow across all disciplines, sectors and interestingly across all job sites. BU data science programs offer our students the prospect of being top-skilled applicants to data science jobs in academia and industry.” 

In addition to theoretical research, Hamid’s research is applied across a large spectrum of innovative applications, including  smart homes, smart energy, human activity recognition, (digital and tele)health, assistive technologies and industrial monitoring. Under his supervision, undergraduate, postgraduate and doctoral students have been working in these and other areas.