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The Internet of Things with a Year in Industry MSc

UCAS code
Year of entry 2018
Course Length
2 years full time
3-5 years part time
Department Computer Science »
Main Campus
Egham »


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 with a Year in Industry 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 new and exciting programme has been developed to help students break into a rapidly expanding area of computer science. A flexible programme structure lets you choose from a range of optional modules, including Programming for Data Analysis, Machine Learning, software Security and The Semantic Web. 

You’ll study in a department renowned for cutting-edge, research-led teaching and have the chance to contribute your own findings during your Individual Project. You'll have access to a range of advanced facilities including a laboratory for experimenting with networked physical devices, and a cluster facility for processing and analysing real data sets.

Study The Internet of Things with a Year in Industry at Royal Holloway and you’ll graduate with a Masters degree in a field with excellent graduate employability prospects, developing a range of skills and knowledge during your placement year that will make you a highly employable candidate.

  • Study in a highly regarded department, ranked 11th in the UK for the quality of research qualitypublications(Research Excellence Framework 2014).
  • Gain invaluable skills, experience and connections during a rewarding year in industry
  • Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.
  • Graduate with a Masters degree in a rapidly expanding field offering excellent graduate employability prospects.
  • Tailor your learning with a wide range of optional modules.

Core modules

Year 1

Interconnected Devices

In this module you will learn about the applications of the Internet of Things (IoT) in society, the components of typical IoT systems and the trends for the future. You will be exposed to IoT design considerations, constraints and interfacing between the physical world and IoT devices. You will develop an understanding of the Arduino platform and how it works in terms of the physical board, the libraries and the IDE (integrated development environment). You will elarn how to program the Arduino via C/C++ code and how to access the pins on the board via the software to control external devices. Finally, you will gain hands-on experience in plugging shields into the main Arduino board to perform other functions such as sensing and actuating.

Data Analysis

This module covers algorithm-independent machine learning; unsupervised learning and clustering; exploratory data analysis; Bayesian methods; Bayes networks and causality; and applications, such as information retrieval and natural language processing. You will develop skills in data analysis, including data mining and statistics.

Advanced Distributed Systems

The module cover the fundamental principles of building modern distributed systems, for example in the context of the Internet of Things (IoT), focussing in particular two central components of the IoT reference architecture-cloud infrastructure and wireless networking. The module will discuss major challenges found in these environments (such as massive scales, wide distribution, decentralisation, unreliable communication links, component failures and network partitions) and general approaches for dealing with these. Topics covered will include abstract models (such as the synchronous and asynchronous distributed computing models, models for wireless networks); algorithmic techniques (such as distributed coordination, fault-tolerant design of distributed algorithms, synchronization techniques); and practical case studies. You will also have an opportunity to implement various components of a realistic distributed system through a series of formative coursework assignments, lab practicals, and a final project.

Wireless Sensor and Actuator Networks

This module combines lectures focussing on the algorithms and the protocols behind wireless sensor and actuator networks (WSANs) with lab classes that focus on how to build wireless sensor and actuator networks for a variety of applications. You will learn about the critical design factors for WSANs, the protocal stack, models and algorithms for WSANs, routing protocols and more advanced open research problems, such as topology control and mobility. The practical classes will cover how to design and build wireless sensor networks and intelligent interactive devices with the ZigBee wireless networking protocol.

Smart Cards, RFIDs and Embedded Systems Security

In this module you will develop an understanding of the applications of smart cards and security tokens and their use as assets in cyber security. You will look at the constituent components of common systems, analysing strengths and weaknesses in their manufacture and potential risks and security safeguards. You will consider the range of campabilities of SIM cards in smartphones and the main standards and applications of smarts cards for banking and finance. You will also examine the role of embedded smart card and RFID technology for passports, identity cards, and satellite TV, and the security measures that have protected past and current cards. 

Introduction to Information Security

In this module you will develop an understanding of how information security may be influenced by real world design and implementation decisions. You will look at the different cryptographic algorithsm, their use, advantages and disadvantages. You will examine cryptographic primitives in the review and evaluation of cryptographic protocols and consider the ratonal decisions in the design of number tokens and secure elements.

Year 2

You will spend this year on a work placement. You will be supported by the Department of Computer Science and the Royal Holloway Careers and Employability Service to find a suitable placement. This year forms an integral part of the degree programme and you will be asked to complete assessed work. The mark for this work will count towards your final degree classification.

Individual Project

 

Optional modules

In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.

Visualisation and Exploratory Analysis

In this module you will develop an understanding of the principles of statistical visualisation and open-ended exploratory analaysis of data. You will look at the construction of linear projections of multivariate data and non-linear dimensions reduction methods. You will gain practical experience in using standard graph visualisation methods and evaluating results, and consider how to avoid data snooping. You will also critically evaluate choices in representational mode, glyph design, and colour design for presentation graphics.

Programming for Data Analysis

In this module you will learn how to use MATLAB (Matrix Laboratory) and WEKA (Waikato Environment for Knowledge Analysis) as tools for machine learning and data mining. For MATLAB, you will develop an understanding of how to input and output data using vectors, arrays and matrics; learn techniques in data visualization, including plots in 2 and 3 dimensions, scatter plots, barplots, and histograms; and learn how to implement concepts from linear algebra and statistics, including probability and matrix decompositions. For WEKA, you will develop an understanding of how to use the software as a tool for training and testing, predicting generalisation performance, and cross-validation; and learn how to implement decision trees, naïve Bayes classifiers, and clustering methods.

Semantic Web

In this module you will develop an understanding of the fundamental concepts and standards of the semantic web. You will look at the the notions, concepts, technologies and modelling techniques that constitute the sematic web, including standards such as RDF, RDFS and OWL. You will examine the underlying logical theory behind the semantic web, such as description logic, and consider how semantics can be used in new, more effective and intelligent ways to manage information and support applications.

Intelligent Agents and Multi-Agent Systems

In this module you will develop an understanding of the notion of an agent, and how agents are distinct from other software paradigms. You will analyse the characteristics of applications that lend themselves to an agent-oriented solution and consider the key issues associated with constructing agents capable of intelligent autonomous action. You will look at the key issues in designing societies of agents that can effectively cooperate in order to solve problems and evaluate the key types of multi-agent interactions possible in such systems. You will also examine the main application areas of agent-based solution, developing a meaningful agent-based system using a contemporary agent development platform.

Advanced Data Communications

In this module you will develop an understanding of how modern multimedia communication work. You will look at the methods used for coding text, images, audio and video transfer over networking infrastructures, including layering, abstraction and the internet reference model. You will examine the use of compression, applications and standards, and quality of service requirements and consider internet technologies such as IP addressing, routing algorithms, and routing protocols such as RIP and OSPF.

Machine Learning

In this module you will develop an understanding of modern machine learning techniques and gain practical experience in developing machine learning systems. You will look at the main advantages and limitations of the various approaches to machine learning and examine the features of specific machine-learning algorithms. You will also consider how the ideas and algorithms of machine learning can be applied in other fields, including medicine and industry.

Large-Scale Data Storage and Processing

In this module you will develop an understanding of the underlying principles of large scale data storage and processing frameworks. You will look at the opportunities and challenges of building massive scale analytics soltutions, gaining hands-on experience in using large and unstructured data sets for analysis and prediction. You will examine the techniques and paradigms for querying and processing massive data sets, such as MapReduce, Hadoop, data warehousing, SQL for data analytics, and stream processing. You will consider the fundamentals of scalable data storage, including NoSQL databases, and will design, develop, and evaluate an end-to -nd analytics solution combining large scale data storage and processing frameworks.

On-line Machine Learning

In this module you will develop an understanding of the on-line framework of machine learning for issuing predictions or decisions in real-time. You will learn about protocols, methods and applications of on-line learning, covering probabilistic models based on Markov chains and their applications, such as PageRank and Markov Chain Monte-Carlo. You will examine the time series models, exploring their connections with Kalman filters, and learning models based on the prequential paradigm, including prediction with expert advice, aggregating algorithm, sleeping and switching experts. You will also consider universal algorithms, their application to portfolio theory, and how prediction within a confidence framework is achieved.

Network Security

The module is concerned with the protection of data transferred over digital networks, including computer and telecommunications networks. We review networking concepts, particularly the concepts of services and protocols, and study how services are incorporated in network communications by specifying protocols. We extend the discussion of services to address security concerns, considering how cryptographic primitives may be used to provide confidentiality, integrity and authentication services. We illustrate these concepts by considering case studies, including WEP/WPA/WPA2, GSM and UMTS, IPsec and SSL/TLS. We also study non-cryptographic countermeasures, including packet-filtering and intrusion detection.

Computer Security (Operating Systems)

In this module you will develop an understanding of the role of security mechanisms for modern computer systems, including both hardware and software. You will look at the mechanisms that are used to implement security policies, considering core concepts such as security models, subjects and objects, authorisation and access rights. You will examine the use and operation of a range of access and control methods and authentication mechanisms, such as tokens an biometrics. You will also and evaluate the main issues relating to software security and their effect on the security of compter systems, in particular the practical implementation of access control.

Security Technologies

In this module you will develop an understanding of the construction of information networks, specifically the architecture and operation of the internet protocol suite. You will look at the construction of a modern computer system, considering hardware and software components which support multiprocessing. You will examine the causes and potential effects of vulnerabilities that affect computer systems and identify appropriate countermeasures, including user authentication and access control mechanisms. You will evaluate authentication and key exchange protocols, such as how SSL and TLS are applied to the internet, and analyse the key security threats faced in network environments.

Security Testing - Theory and Practice

In this module you will develop an understanding of the common approaches and methodologies used for carrying out and managing security and penetration testing, including legal requirements for such audits. You will look at network protocols, relevant computer system architectures, and web application systems, considering their vulnerabilities, common forms of attack, and security technologies designed to mitigate these. You will gain practical experience of exploting vulnerabilities to penetrate a system, learning how to design secure systems and defend them against intrusion.

Software Security

In this module you will develop an understanding of the importance of security in the development of applications. You will look at poor programming practices and how they can be exploited, leading to catastrophic security breaches. You will consider the threat posed by malicious software and examine some of the newer research trends that are likely to influence software security work in the coming years.

Introduction to Cryptography and Security Mechanisms

In this module you will develop an understanding of the uses of cryptography. You will look at the basic cryptographic mechanisms used to provide core security services and examine differences between them, identifying suitations in which they are most usefully employed. You will consider the issues than need to be addressed to 'secure' an application, and evaluate the limitations of cryptography and methods for supporting it within a full security architecture.

Assessment is carried out by a variety of methods including coursework, practical projects and a dissertation. 

Entry criteria:

UK 2:1 (Honours) or equivalent in Computer Science, Engineering or other subjects that include a strong element of mathematics and computing, e.g. Physics,

Relevant professional qualifications and relevant experience in an associated area will also be considered.

English language requirements:

IELTS 6.5 overall with a minimum of 5.5 in all other subscores. For equivalencies, please see here


If you require Royal Hollowy to sponsor your study in the UK, your IELTS must be a UK government-approved Secure English Language Test (SELT)

International and EU entry requirements

Please select your country from the drop-down list below




Students from overseas should visit the International pages for information on the entry requirements from their country and further information on English language requirements. Royal Holloway offers a Pre-Master’s Diploma for International Students and English language pre-sessional courses, allowing students the opportunity to develop their study skills and English language before starting their postgraduate degree.

 

Study The Internet of Things with a Year in Industry at Royal Holloway, University of London and you can expect excellent graduate employability prospects in an exciting, fast-expanding area of computer science. You’ll develop a wide range of transferable skills, including cybersecurity, botnet detection, cloud computing, data mining and network analytics. You’ll also benefit from Royal Holloway’s proximity to the M4 corridor – also known as ‘England’s Silicon Valley’ – gaining invaluable skills, experience and industry connections during your placement year.

Recent alumni have gone on to enjoy rewarding careers in areas such as financial analytics, Big Data and some have gone on to do a PhD. The Department of Computer Science is located within easy reach of our College Careers service, providing you with help, support and advice regarding the next steps in your career. 

  • 90% of Royal Holloway graduates in work or further education within six months of graduating.
  • Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
  • On-site College Careers Service provides help and support for students. 

Home and EU students tuition fee per year 2018/19*: £10,400

International students tuition fee per year 2018/19*: £19,000

The fee for the Year in Industry will be 20% of the first year fee for that academic year.

Other essential costs**: There are no single associated costs greater than £50 per item on this course

How do I pay for it? Find out more about funding options, including loans, grants, scholarships and bursaries.

* These tuition fees apply to students enrolled on a full-time basis. Students studying part-time are charged a pro-rata tuition fee, usually equivalent to approximately half the full-time fee. Please email student-fees@royalholloway.ac.uk for further information on part-time fees. All postgraduate fees are subject to inflationary increases. Royal Holloway's policy is that any increases in fees will not exceed 5% for continuing students. For further information see tuition fees and our terms and conditions.

** These estimated costs relate to studying this particular degree programme at Royal Holloway. Costs, such as accommodation, food, books and other learning materials and printing, have not been included.

Scholarships for international students

A scholarship of £2,000 will be automatically provided (and deducted from the fees payable) for international students holding the equivalent of a UK first-class honours undergraduate degree.

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