The Internet of Things MSc

The course

The digital revolution is changing our world in deep and lasting ways. The Internet of Things - networked devices that are capable of sensing, transmitting and acting on data to improve our quality of life - is an area of development that is widely expected to require the services of millions of new developers over the coming years. Study the Internet of Things at Royal Holloway, University of London and you’ll acquire the skills and experience you need to become a part of an exciting, fast-expanding area of computer science with excellent graduate employability prospects.

This programme is designed to help you break into a rapidly expanding area of computer science, providing you with advanced knowledge and skills in data analytics techniques, technical and methodological aspects of distributed and networked systems, and aspects of cyber-security such as privacy and safety.

Skills that you will acquire include the ability to:

• design and implement middleware services for reliable communication in unreliable networks, and storage solutions for wireless, sensor, and ad-hoc networks
• detect sources of vulnerability in networks of connected devices and deploy
• the appropriate countermeasures to information security threats
• enforce privacy in “smart” environments
• work with open source and cloud tools for scalable data storage (DynamoDB) and coordination (Zookeeper)
• design end-to-end IoT solutions involving interconnected edge devices and clouds
• work with modern network management technologies (Software-Defined Networking) and standards (OpenFlow)
• work with low-power wireless and mesh networking standards and technologies such as IEEE 802.15.4, ZigBee and XBee
• work with state-of-the-art microcontroller devices and kits, such as Arduino and Tessel, and miniature computing technologies, such as RaspberryPi
• work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks.

Teaching & assessment

Teaching is organized in terms of 11 weeks each. Examinations are taken in April/May of each academic year, except for Data Analysis for which the exam is in January. The individual project is taken over 12 weeks during the Summer.

A weekly seminar series runs in parallel with the academic programme, which includes talks by professionals in a variety of application areas as well as workshops that will train you to find a placement or a job and lead a successful career.

Assessment is carried out by a variety of methods including coursework, small group projects, and examinations, the proportions of which vary according to the nature of the modules.

This programme can be taken part-time in day-release mode, allowing you to complete your degree by coming to campus once a week on fixed days.

Your future career

Recent alumni have gone on to enjoy rewarding careers in areas such as financial analytics and Big Data, while others have gone on to do a PhD. We bring several companies to our campus throughout the year, both for fairs and for delivering advanced topics seminars, which are an excellent opportunity to learn about what they do and discuss possible placements or jobs.

• Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
• Together with our on-site Careers and Employability Service, we run one-to-one coaching sessions and workshops, helping you to find a placement or job and lead a successful career.