MSc Data Science & Artificial Intelligence

• Research Methods & Professional Issues: This unit provides an overview of different research methods used to address scientific research questions. It covers aspects of research design, implementation and how they apply to solving data science and artificial intelligence based challenges in a quantitative, qualitative or mixed fashion.

• Search & Optimisation: This unit introduces you to classical approaches to Search and Optimisation. These techniques are employed in a vast number of areas, including health, security, transport, aerospace, finance and many more. Whether the goal is to improve the performance of a new medicinal drug, gene states discovery and expressions, aircraft structural integrity, network traffic cybersecurity, or business investment, advanced stochastic optimisation algorithms are employed by researchers and practitioners in order to design optimal, diverse, and pertinent solutions to many real-world problems for best performing operations.

• Data Processing & Analytics: The unit aims to advance your knowledge and skills in the evolving areas of big data, data modelling and analytics. You will develop a good understanding of data design, implementation and usage of data-driven systems. Moreover, you will learn how to model data and process big data, discover knowledge within the data and deal with the dimensionality of the data. Overall, you will develop critical understanding of the methodologies and techniques which lead you to process big data 5Vs, i.e. Volume, Velocity, Variety, Veracity and Value. Typical big data technology tools such as  Hadoop/MapReduce, Storm, Spark, MongoDB and more are introduced.
• Artificial Intelligence: The aim of this unit is to provide you with an introduction to the first principles and techniques that are employed in the greater field and sub-fields of Artificial Intelligence (AI), together with the skills and knowledge required to employ AI techniques for solving real-world and synthetic problems.

  You will approach AI from a Computer Science perspective, with focuses given to the challenges faced within the field, nature inspired algorithms, and their applications to complex real-world problems.

• 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.

Option units (choose one in semester 1)

• Neuronal Analysis: This unit provides you with a focus on advanced models and data analysis methods for understanding the human brain function at neuronal levels. The mathematical modelling is achieved using highly performing parallel data processors which imitate biological neuronal network functions.
• Blockchain & Digital Futures: The objective of this unit is to develop your skills and knowledge about the Blockchain technology and its usage. This includes the definition of Blockchain technology, its business aspect, encountered issues, objectives, and challenges. These also cover Blockchain horizontal and vertical scaling, together with key basics of cryptography which are required for understanding Blockchain technology concepts, cryptocurrencies, together with their respective networks, issues and challenges.

Option units (choose one in semester 2)

• Smart Systems: This unit introduces you to various facets of smart systems technology and how they could apply to different environments. A selected set of innovative applications will be investigated and discussed to provide you with practical insight on smart systems, their deployment and applications.
• Computer Vision: This unit focuses on a number of computer vision techniques, ranging from traditional approaches which have been established through research over many decades, to the most recent state-of-the-art development, using appropriate tools. The unit entails a strong empirical element where Computer Vision models are implemented, performance evaluated and validated.

You have the option to undertake a 30-week placement at the end of the course, providing an opportunity to apply your acquired knowledge and skills in the workplace. You are required to find your own placement; however, our Careers & Employability Service and your faculty placements office are on hand to support you.

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.

We provide a lot of support for you to help you find work, including a block of seminars, covering topics such as writing a CV and a covering letter, completing an application form, performing well in interviews, and we also provide language support to assist you with the written elements of your applications.

However, it is ultimately your responsibility to find work. The university does not guarantee that you will find a place.

During your time on placement you will be supported by a unit tutor and a placement development advisor who will visit you on placement and keep in touch by phone and email.

Employment prospects are now truly international and BU encourages students to consider an international work placement or volunteering experience during their degree.

One way could be through the EU funded Erasmus mobility programme which supports placements or study exchanges in Europe.

Students can also participate in international placements outside of Europe. There are opportunities to engage with summer schools and volunteering projects. These experiences help students to enhance their global employability skills.

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.

There is no application deadline for this course. However, if you will need a visa to come to the UK to study, think carefully about the length of time it will take for your visa application to be processed and make sure your visa will be ready in time for the beginning of your course. 

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.

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

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 (4 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 2:2
• Thailand:  Thai Bachelor's (Honours) degree from a recognised higher education institution with a minimum GPA of 2.5/4.0
• Turkey: Bachelor’s degree (Lisans Diplomasi - four years) with a minimum overall GPA of 2.3/4.0
• Vietnam:  Bachelor's degree/Bang tot nghiep dai hoc with an average score of 6.5/10, or a Master’s degree/Thac si.

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. 

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.
• The BU Language Centre to help you develop/improve foreign or English language skills.
• 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 shops stock a wide range of stationery supplies on both campuses.
• 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 £3,000 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 Associate Professor of Data Science 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 COPD health patients exacerbation events forecast, the impact of climate change on species behaviour, surveillance, human physical security and industrial operations. He has published over 120 papers in scientific journals, conference proceedings and books.

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.  

Avleen Malhi received her PhD in autonomous vehicles (2016). Her research interests lie in the area of Artificial Intelligence, machine learning and intelligent systems, with a particular focus on practical applications.  

Throughout her career starting from PhD, she has worked on various research projects in collaboration with industry and academia ranging from industrial projects to EU-funded H2020 research frameworks. These research projects align with her research directions on intelligent systems, explainable artificial intelligence, autonomous systems, machine learning, and the Internet of Things.