MSc Internet of Things with Data Analytics

• Mobile & Wireless Networks: Mobile and wireless networking technologies are ubiquitous nowadays. A key issue facing enterprises today is how to harness the potential of mobile and wireless technologies to enhance the operational effectiveness of the business and illuminate potential opportunities. This unit reviews the broad spectrum of relevant technologies (e.g., WiFi, ad hoc networks, cellular networks, etc.), examines their operating principles/protocols and relevant standards as well as the use of these networks in different context and scenarios. The unit also explores the main challenges faced in these networks as well as how they fit into the latest networking paradigms.
• Wireless, Sensor & Actuator Networks: You will explore the operating principles, standards, design and configuration of WSANs. Future and emerging paradigms – such as Mobile Crowdsensing Systems, and technologies such as Wireless Power Transfer in ad-hoc networks will also be addressed.
• Security and Privacy in IoT: Smart objects, IoT applications, and their enabling platforms are often vulnerable to security attacks and changing operating and context conditions that can compromise the security of some of their components (e.g., local sensors, network components, application-level components). They also generate, make use of and inter-relate massive personal data in ways that can potentially breach legal and privacy requirements. This unit will develop your capability to understand and produce security architectures of IoT-related networks and systems.
• Research Methods & Professional Issues: Research requires a structured and disciplined approach at all stages. We will help you to develop key research skills in many areas from project proposals and planning to critical analysis of research findings, academic writing, and dissemination. Ensuring you give due consideration to professional standards and ethical issues in research.
• 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 (choose one semester 1)

• Cloud Computing: Cloud computing provides a secure infrastructure for systems integration, data processing and manipulation as well as storage. The concept of virtualisation including servers, storage and networks, as well as the cloud structure, services and deployment models will be discussed. Locally-based networks, IT resources/services and their migration to the cloud are elaborated and strategies for migration to the cloud will be explored.
• 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.
• Search & Optimisation: Search & optimisation techniques are employed in a vast number of areas, including medicine, defence, transporation, 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.

Option units (choose one semester 2)

• 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.

• 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.

Please note that option units require minimum numbers in order to run and may only be available on a semester by semester basis. They may also change from year to year.

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.
 
The placement is intended to foster personal and professional development, and to help you to make a connection between academic learning and the working world.

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.

The normal requirements for embarking upon this course are:

• A Bachelors Honours degree with 2:2 in any subject, or equivalent

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. 

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.

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.

Our Careers & Employability Service and your faculty placements office will support you in finding an appropriate role and help you with your application. And we’ll support you throughout your time working in industry. 

IoT is an exciting growth area. After graduating, you could find yourself working in roles such as: 

• Product Manager, Consumer IoT
• IoT Global Partner Manager
• New Technologies & Innovation Manager
• Business Transformation Manager
• Head of Connected Cities
• IoT Proposition Manager

You could also go on to further study, developing your knowledge through a doctoral programme. 

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.
• 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.
• 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.
• 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 out website for more information
• 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.
• Sport BU 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.

If you need to repeat one or more units during the course of your studies (with or without attendance) the pricing will be pro-rata of the full-time fee.

We offer a range of scholarship and bursaries to eligible students who are beginning their studies at BU. Please visit www.bournemouth.ac.uk/funding for 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.

Benjamin’s research focus is within Human Computer Interaction, specifically Accessibility where he focuses on developing technology to help people with hearing loss. His doctoral research focused on solutions to enhance the acquisition of speechreading (commonly called lipreading).

Dr Wei Koong Chai is a senior lecturer at Bournemouth University. He heads the Future and Complex Networks Research Group (FlexNet) in the Department of Computing and Informatics at BU. He is also currently a visiting academic in the Department of Electronic and Electrical Engineering, University College London (UCL), UK.

Wei Koong Chai is a senior lecturer in Bournemouth University (BU), UK. He heads the Future and Complex Networks Research Group (FlexNet) in the Department of Computing and Informatics in BU. He is also currently a visiting academic in the Department of Electronic and Electrical Engineering, University College London (UCL), UK.

Dehao Wu is a senior lecturer in Bournemouth University (BU), UK. Before joining BU, he holds the role of Sussex research fellowship and was a senior research fellow in the department of engineering and design at University of Sussex since April 2018. Before joining Sussex, he was a postdoc research fellow at Nanyang Technological University of Singapore and University of Manchester, respectively. 

His current research work focuses on machine-learning algorithms and intelligent management of 5G and beyond-5G systems, artificial intelligence for 5G verticals and IoT. His other research interests include the area of optical wireless communications, free space optics, visible light communications, RF communications, indoor high-accuracy positioning, optical sensing and detecting, underwater RF and acoustic communications, information-centric networking, and information resilience. 

He has published more than 45 peer-reviewed papers in international conferences and journals, two book chapters and two patents in indoor high-accuracy positioning technology. He is an Executive Committee member of IET RF and Microwave Technical and Professional Networks (TPN), and service as the technical committee member for several IEEE conferences. He received a bachelor's degree in optical and information engineering in 2007, an MSc degree in microelectronics and telecommunication engineering in 2009 and a PhD in optical wireless communications from Northumbria University, Newcastle, UK, in 2013. 

Jiankang Zhang is a senior lecturer in Computer Science at Bournemouth University. Prior to joining in Bournemouth University, he was a senior research fellow at University of Southampton, UK. He was a lecturer and then an associate professor at Zhengzhou University from 2012 to 2014. 

Jiankang Zhang was a named researcher of HARNet project funded by Innovate UK, the project of "Next Generation Digital Subscriber Loops" funded by EPSRC and Savana project funded by Thales. His research interests are in the areas of artificial intelligence algorithms, ad-hoc networks, aeronautical communications and networks, wireless communications and networks. 

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.