MSc Data Science and Artificial Intelligence

This course provides you with advanced knowledge, methods and processes as an enabler for deploying data science and artificial intelligence. This will lead to solving 21st century world problems with greater scalability and efficiencies.

Delivery:
Full time according to Funding Council definitions, Part-Time, Sandwich (Thick) out of college.

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Why study MSc Data Science and Artificial Intelligence at BU?

Learn about recent advances in the fields of data analytics, big data tools and technologies, machine intelligence while concretely experimenting on machine knowledge extraction and decision-support
Use a broad range of data science tools and technologies, from those which are established (MATLAB, R and Weka), to the new favourites which prepare you for mainstream data science jobs (Python, Jupyter notebook, Apache Spark and libraries such as Keras, TensorFlow, and PyTorch)
Graduate with important skills in strategic thinking for scientific research implementation and communication
We’ve established close relationships with companies, research and government agencies that are interested in recruiting skilled graduates in data science and artificial intelligence
Take part in organised codejams/hackathons, visit organisations and work on practical data science and artificial problems. This will support you in establishing an internship or placement
Tailor your learning towards the areas that interest you, with option units covering topics such as neuronal analysis, smart systems, computer vision and Blockchain.

Find out more about the content of this course.

Career opportunities

You’ll explore various investigative data science and artificial intelligence-based approaches, relevant to the security, environment, human behaviour understanding, transport, health, smart cities sectors and more. You’ll possess the practical skills and theoretical knowledge necessary to enter fields within data science and artificial intelligence.

See what it's like to study this course

Image description — Students working in computer lab

Next start date:

September 2021, January 2022, September 2022

Location:

Bournemouth University, Talbot Campus

Duration:

September start: 1 year full-time, 2 years part-time or 2 years full-time with a 30-week placement, January start: 16 months full-time, 32 months part-time or 24 months with a 30-week placement

Required subjects:

Computing, Technology, Maths, Physics, Engineering, Data Sciences or Data Analytics

Entry requirements:

A Bachelors Honours degree with 2:2 in a required subject, or equivalent.

International entry requirements:

If English is not your first language you'll need IELTS 6.0 (Academic), with a minimum of 5.5 in each component. For more information check out our full entry requirements.

Course details

Details of the assessment methods and contact hours for each unit of the course can be found in the programme specification.

Download the programme specification (pdf 271 kb)

Core units

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

Option units (choose two)

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.
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.

Programme specification

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.

Placement opportunities

An exciting and valuable part of your studies with us is the opportunity to gain valuable experience through full-time paid industrial placements, for a minimum of 30-weeks.

Find out more about placements for postgraduate students

What support is available?

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.

International opportunities

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.

Your application

Selection methods

How and when to apply

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.

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.

Entry requirements

General entry requirements

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.

International entry requirements

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:

China: 学士学位 (Bachelor degree) with a minimum of 65% overall
Nigeria: Bachelor's degree from a recognised institution in Nigeria
Thailand: Thai Bachelor's (Honours) degree from a recognised higher education institution.
Vietnam: Bachelor's degree/Bang tot nghiep dai hoc with an average score of at least 7.0, or a Master’s degree/Thac si.
Turkey: Bachelor’s Degree (Lisans Diplomasi -four years) to be considered for a postgraduate course at BU.

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.

Careers

Upon completion of this course, you will possess the practical skills and theoretical knowledge necessary to enter fields within data science and artificial intelligence.

Potential job roles

Further study

Costs and fees

You can find full information about the deposits required and how to pay your fees in our postgraduate fees and funding section, including details of the Postgraduate Loan (subject to fee status).

All fees are quoted in pounds sterling and are per annum. Fees quoted are for tuition only unless stated otherwise. Your tuition fees will be the same for each year of your course.

Find out more about living expenses for postgraduate students

No hidden extras

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 field-based teaching activity
Support for finding placements (UK or abroad) and fieldwork, and non-financial support whilst on placement
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 capabilities, integrated social media and advanced video features.
IT labs (some open 24/7), wireless network, AV equipment to borrow
Peer Assisted Learning (PAL) scheme
Disability and additional learning support
The BU Language Centre to help you develop/improve foreign or English language skills
24 hours a day, 365 days a year security team.

Costs of living and other expenses you need to consider

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
Accommodation and living costs. Our accommodation price guide can be found on our website.
Travel costs, outdoor wear and footwear for optional field trips (where applicable)
Text books, general stationery and other supplies. Our award-winning library is stocked with a large range of text books and online resources, free of charge. The Students’ Union shops stock a wide range of stationery supplies on both campuses
Any expenses relating to placements e.g. travel, specialist clothing etc
SportBU membership.

Financial help available from BU

Deposits

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.

Our staff

On this course you will be taught by staff with relevant expertise and knowledge appropriate to the content of the unit. This could include senior academic staff, qualified professional practitioners and research students, many of whom are actively engaged in research and/or professional practice which is integrated into the teaching of this course. Please note that teaching staff can change.

Dr Zoheir Sabeur – Programme Leader

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.

View Dr Zoheir Sabeur's staff profile

Professor Marcin Budka – Professor of Data Science

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.

View Professor Budka's staff profile

Dr Emili Balaguer-Ballester – Associate Professor in Computational Neuroscience

Professor Hamid Bouchacia – Professor of Data Science

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. 

View Prof Hamid Bouchacia's staff profile

Dr Avleen Malhi – Lecturer in Data Science and AI

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.

View Dr Avleen Malhi's staff profile

Statistics shown throughout this page are taken from Unistats and BU institutional data unless otherwise stated.