MSc Data Science and Artificial Intelligence

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

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Our MSc Data Science and Artificial Intelligence will give you the knowledge of methods and processes that will enable you to analyse, devise, and deploy data science and artificial intelligence solutions for real-world problems. In particular, this degree emphasises different facets of exploratory/confirmatory data science techniques and artificial intelligence algorithms in different contexts, ranging from digital health to fraud detection. You will learn about recent advances in the fields of data science and artificial intelligence, including state-of-the-art tools to perform analytics and experiments to enable data-driven decision making and automation.

You will graduate with skills in methodological thinking, research disposition, and communication, in addition to the theoretical and practical skills within data science and artificial intelligence.

Image description — Students working in computer lab

Key information

Next start date:

September 2019, January 2020, September 2020, January 2021

Location:

Bournemouth University, Talbot Campus

Duration:

September: 12 months full-time, 24 months with a 12 month placement or 2 years part-time. January: 16 months full-time

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 and Professional Issues: This unit will provide an overview of different research methods used to address clinical research questions. It will cover aspects of research design and how they apply to the question being asked whether the approach is quantitative, qualitative or mixed methods.
Search and optimisation: These techniques are employed in a vast number of areas, including medicine, defence, transportation, aerospace, and finance. Whether the goal is to improve the performance of a new drug, aircraft, traffic signal controllers, or investment decisions, stochastic optimisation algorithms can be employed by researchers and practitioners to design optimal, diverse, and pertinent solutions to many real-world problems. This unit introduces classical approaches to search and optimisation before moving onto the state-of-the-art in computational intelligence. The unit entails a strong empirical element where Computational Intelligence models will be implemented and evaluated.

Data Processing and Analytics: The unit aims to develop student knowledge and skills in the evolving areas of Data Modelling, Data Analytics and Big Data Analytics. Students develop an understanding of data design, implementation and use of data-driven systems. Moreover, they learn how to model data and big data, discover knowledge within the data and deal with the dimensionality of the data. Overall, they develop critical understanding of the methodologies and techniques to cope with Data and Big Data, i.e. data of high volume, high velocity and high variety, utilising the appropriate platform (e.g. Hadoop, Storm, Spark, MongoDB).
Artificial Intelligence: The aim of this unit is to provide you with an introduction to the principles and techniques employed within the greater field and sub-fields of Artificial Intelligence (AI), and the skills and knowledge required to employ AI techniques to solve real-world and synthetic problems. We will approach AI from a computer-science perspective, with focus given to the challenges faced within the field, nature inspired algorithms, and their applications to complex real-world problems.
Individual Masters Project: You will develop an understanding of the characteristics and implications inherent in the solution of a complex, real-world problem within the context of a substantial, independently-conducted piece of work.

Option units

Option units (choose two)

Neuronal Analysis: This unit focuses on the study and application of data analysis techniques in neuroscience. Such algorithms are either adapted or specifically designed for analysing neuronal activity in physiological and pathological brain states. The mathematical modelling of basic neuronal functions over the last century, inspired the development of sophisticated parallel data processors that imitate biological neurons and networks to a certain degree. A successful example is the widely used family of deep learning-based approaches. In parallel, methods from e.g., computational statistics, dynamical systems, partial differential equations and more recently machine learning, feedback to the neuroscience field; and provided valuable insights in the understanding of the nervous system. This unit discusses state-of-the-art analytical tools for identifying normal and altered behaviour of neuronal activity at multiple spatiotemporal scales, their applications and current limitations.
Blockchain and Digital Futures: The objective of this unit is to develop your skills and knowledge about the Blockchain technology and its usage. The material, lectures and seminars includes defining the Blockchain technology, its business aspect, issues, objectives, and challenges, covering Blockchain horizontal and vertical scaling, key basics of cryptography required for understanding the Blockchain technology concepts, different cryptocurrencies, and their issues, challenges, and networks. The unit also covers a few data analysis-based Blockchain technology scenarios and case studies. The aim is to develop related skills and an understanding of critically evaluating the key issues, challenges, and existing solutions.
Smart Systems: Artificial Intelligence is being embedded in various systems and tools to achieve better decision making and more autonomy. The unit draws on a large spectrum of smart systems technologies. It covers basic as well as advanced topics with the goal of providing an overall introduction into these technologies. Positioned at the cross of many disciplines, this unit introduces various facets of smart systems technology and illustrates how they apply to different environments. A selected set of innovative applications will be discussed to provide a practical insight into such technology covering in particular the underlying modelling, perception, reasoning and learning techniques.
Computer Vision: The field of Computer Vision has been developing rapidly over the last decade and became the cornerstone of many recent innovations across a number of domains and application areas, including state-of-the-art image classification (e.g. for use in search engines), object detection (e.g. in autonomous vehicles), semantic segmentation (e.g. in identification of tumours in x-ray images), biometrics (e.g. face verification) or automatic annotation of medical images, to name a few. There is a shortage of skilled individuals with deep understanding of the underlying principles and able to confidently apply them in order to solve real-world problems. This unit focuses on a number of Computer Vision techniques, ranging from traditional approaches established over many decades of research, to the latest state-of-the-art developments, together with appropriate tools. The unit entails a strong empirical element where Computer Vision models will be built and evaluated.

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

The optional placement provides an excellent opportunity for you to gain first-hand industry experience and apply the learning that you have achieved through the course.

The placement can be paid employment but voluntary work can be just as useful.

Find out more about placements for postgraduate students

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

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.

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

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:

One set of study-related consumables such as a memory stick/ DVD
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
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:

Accommodation and living costs. Our accommodation price guide can be found on our website.
Optional fieldwork travel, outdoor wear and footwear (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.

Financial help available from BU

Deposits

International (non-EU) students need to pay a non-refundable £2,000 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. Shahin Rostami - Course Leader

Dr. Shahin Rostami is a Senior Academic in Data Science. He teaches both postgraduate and undergraduate units, such as Search and Optimisation, Artificial Intelligence, and Data Mining and Analytic Technologies.

“Data science is without a doubt one of the most exciting fields to study. Here at BU we’ll give you the theoretical and practical background needed to start your career.”

Dr. Rostami holds a Ph.D. in the field of Computational Intelligence with applications to Concealed Weapon Detection. His research interests lie within Data Science and Artificial Intelligence, ranging from theory to their application to Digital Healthcare and Threat Detection. Currently, he is consulting for and supervising PhD research projects in Non-Contact Vital Sign Measurement and Multi-Objective Concealed Weapon Detection. He has published in many high-impact journals and conferences, and organised/chaired special sessions including the IEEE CIBCB 2017 “Machine Learning in Medical Diagnosis and Prognosis”. He also leads the Computational Intelligence Research Initiative (CIRI).

View Dr Rostami's staff profile

Dr. Rashid Bakirov - Lecturer

Rashid is a lecturer in Computing. He is currently teaching units related to data analytics and databases both for undergraduates and postgraduates.

“I am fascinated with machine learning and hope to convey this to my students."

Rashid is interested in adaptive machine learning, particularly for streaming data, online machine learning, reinforcement learning and related areas.

View Dr. Bakirov'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 Dr Budka's staff profile

MSc Data Science and Artificial Intelligence

Confirm application

Key information

Next start date:

Location:

Duration:

Required subjects:

Entry requirements:

International entry requirements:

Scholarships

Our stories

Planning your future

Course details

Core units

Option units

Programme specification

Placement opportunities

International opportunities

Your application

How and when to apply

Entry requirements

General entry requirements

International entry requirements

Careers

Potential job roles

Costs and fees

No hidden extras

Costs of living and other expenses you need to consider

Financial help available from BU

Deposits

Our staff

Dr. Shahin Rostami - Course Leader

Dr. Rashid Bakirov - Lecturer

Professor Marcin Budka - Professor of Data Science

MSc Data Science and Artificial Intelligence

Course search

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Confirm application

Key information

Next start date:

Location:

Duration:

Required subjects:

Entry requirements:

International entry requirements:

Scholarships

Related courses

Our stories

Take a look at Eldrida’s guide on activities to get involved in as a PG student

Watch Ellie’s vlog on the social life of a postgrad student

Planning your future

Course details

Core units

Option units

Programme specification

Placement opportunities

International opportunities

Your application

How and when to apply

Entry requirements

General entry requirements

International entry requirements

Careers

Potential job roles

Costs and fees

No hidden extras

Costs of living and other expenses you need to consider

Financial help available from BU

Deposits

Our staff

Dr. Shahin Rostami - Course Leader

Dr. Rashid Bakirov - Lecturer

Professor Marcin Budka - Professor of Data Science