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The Applied Computing Department is a young department of modest size but is successful in attracting research funding from various sources in the UK and the EU (including industry, research councils and charitable foundations). Read more

Course Outline

The Applied Computing Department is a young department of modest size but is successful in attracting research funding from various sources in the UK and the EU (including industry, research councils and charitable foundations). It supports a significant range of research interest and over the last few years the number of research students has grown steadily. The Department has a history of involvement in EU framework projects. More recently, we were partners in two EU FP6 funded projects: SecurePhone and BroadWan. We have been working and collaborating with many European research institutions including The Technical University Graz, CNUCE, Pisa, Thales, Thomson, TELENOR, RAL, Salzburg, Telephonica – Spain, Atos Origin, The University of Saarbrucken – Germany, INFORMA – Italy, and ENST – France.

The main research areas of interest in the Department cover image / video processing and analysis techniques and applications; wireless mobile network technologies; and biometric-based authentications for constrained devices / environments. In image processing we mainly, but not exclusively, use wavelet transform techniques for facial feature detection and recognition, online image / video compression for constrained devices, visual speech recognition, feature detection in biomedical images, digital watermarking, content-based video indexing for biometric video databases. In the wireless networking area, our research effort focuses on convergence and integration of different wireless technologies and standards, wireless mesh technologies, intrusion detection and prevention, efficiency and stability of ad hoc networks.

Currently the Department has a number of research groups consisting of 5 research active academics, 12 PhD and 3 MSc/MPhil students at various stages of their studies.

Find out more about our Department of Applied Computing on http://www.buckingham.ac.uk/appliedcomputing.

Teaching Method

Candidates spend a considerable part of their studies undertaking supervised research, at the end of which they submit a thesis embodying the results of that research. This thesis must demonstrate familiarity with, and an understanding of the subject, its principal sources and authorities. It should display critical discrimination and a sense of proportion in evaluating evidence and the judgements of others. The subject should be dealt with in a competent and scholarly manner.

After your degree

We have a high graduate employment rate:

- The Higher Education Statistics Agency (HESA) ranked Buckingham top for job prospects with 96.9% (July 2013).
- The Guardian League Table for 2014 ranked Buckingham top in the category of job prospects (June 2013).
- The Complete University Guide reported that the University ranked second for Graduate Prospects (May 2013).

Our graduates have gone on to further study at most of the world’s leading universities, including Harvard, London, Oxford and Cambridge and secured jobs in senior positions around the world. Among our alumni we have a graduate who became the head of his country’s civil service and one who became a leading Formula One motor-racing driver. Another secured a position as the Minister of Sabah and one female law graduate became the first British lawyer to become a French Advocate.

What our students and alumni say

Please see the Research Students page for examples of currently on-going as well as already successfully finished research projects: http://www.buckingham.ac.uk/appliedcomputing/researchstudents.

Apply here http://www.buckingham.ac.uk/sciences/mphil/computerscience.

Read less
This degree, offered jointly by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling. Read more
This degree, offered jointly by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling. This is an attractive advanced qualification, especially suitable if you are seeking employment in asset structuring, product pricing or risk management, among other fields.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msccomputationalfinance.aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy, in particular of financial services and insurance. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will learn modern quantitative finance and computational methods for financial modeling. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The departments have expertise in a wide set of areas in Computer Science and in Economics, and the topics taught reflect these areas of excellence.

- Computer Science hosts one of strongest research groups in Machine Learning (the science of systems that learn from data).

- In the most recent Research Assessment Exercise (RAE 2008), Computer Science ranked 11th and Economics ranked 8th for their research output.

- Computer Science is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- Computer Science has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

On completion of the course graduates will have:
Throughout your degree, you will have the opportunity to acquire the following skills:

- Knowledge of the working of financial markets and their role in the context of global economy.
- Knowledge of modern mathematical and computational techniques used in finance.
- Knowledge of key ideas, principles, and methods of machine learning and their applications in finance.
- Ability to apply methods of computational finance to practical problems in computational finance, including pricing of derivatives and risk assessment.
- Ability to analyse and critically evaluate methods and general principles of computational finance and their applicability to specific problems; to critically evaluate validity and practicality of results.
- Ability to analyse and critically evaluate applicability of machine learning algorithms to problems in finance.
- Ability to implement methods of computational finance and machine learning using object-oriented programming languages and
modern data management systems.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different finance-related areas, including careers as financial analysts, accountants, bankers, journalists and business analysts. Our graduates are currently working for firms such as Accenture, TNS, RBS, Deloitte, and Baker and McKenzie. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to both departments. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major finance employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London. Thus, you will have additional access to a wealth of presentations and networking opportunities which make the most of London’s financial centre.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered jointly by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling. Read more
This degree, offered jointly by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling. This is an attractive advanced qualification, especially suitable if you are seeking employment in asset structuring, product pricing or risk management, among other fields.

As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msccomputationalfinance(yearinindustry).aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy, in particular of financial services and insurance. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will learn modern quantitative finance and computational methods for financial modeling. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world

Department research and industry highlights

- The departments have expertise in a wide set of areas in Computer Science and in Economics, and the topics taught reflect these areas of excellence.

- Computer Science hosts one of strongest research groups in Machine Learning (the science of systems that learn from data).

- In the most recent Research Assessment Exercise (RAE 2008), Computer Science ranked 11th and Economics ranked 8th for their research output.

- Computer Science is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- Computer Science has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Your placement will take up to one year and, if you are an overseas student, your visa will cover the two years of the programme. The placement attracts a salary and is assessed as part of your degree. You will be assigned a supervisor by the host company, who is responsible for directing your work. You will be assigned an academic supervisor, who visits to check if you are integrating successfully and the type of work being undertaken is appropriate, and supports you in general during your placement. If you cannot or decide not to take a placement, you revert to the normal one-year degree.

On completion of the course graduates will have:

Throughout your degree, you will have the opportunity to acquire the following skills:

- Knowledge of the working of financial markets and their role in the context of global economy.
- Knowledge of modern mathematical and computational techniques used in finance.
- Knowledge of key ideas, principles, and methods of machine learning and their applications in finance.
- Ability to apply methods of computational finance to practical problems in computational finance, including pricing of derivatives and risk assessment.
- Ability to analyse and critically evaluate methods and general principles of computational finance and their applicability to specific problems; to critically evaluate validity and practicality of results.
- Ability to analyse and critically evaluate applicability of machine learning algorithms to problems in finance.
- Ability to implement methods of computational finance and machine learning using object-oriented programming languages and modern data management systems.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.
- Work experience and appreciation of how your work fits into the organizational and development processes of a company.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different finance-related areas, including careers as financial analysts, accountants, bankers, journalists and business analysts. Our graduates are currently working for firms such as Accenture, TNS, RBS, Deloitte, and Baker and McKenzie. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to both departments. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major finance employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London. Thus, you will have additional access to a wealth of presentations and networking opportunities which make the most of London’s financial centre.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling… Read more
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations, from retailers such as Tesco or Amazon, to manufacturers like BMW, to health-care providers, and to public administration.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscdatascienceandanalytics.aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will acquire both the foundational knowledge and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations from retailers such as Tesco or Amazon, to manufacturers like BMW, health-care providers, or public administration. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning – the science behind ‘Big Data’ – is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liason Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).
Please visit our websitefor additional information on this degree.

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling… Read more
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations, from retailers such as Tesco or Amazon, to manufacturers like BMW, to health-care providers, and to public administration.

As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscdatascienceandanalytics(yearinindustry).aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will acquire both the foundational knowledge and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations from retailers such as Tesco or Amazon, to manufacturers like BMW, health-care providers, or public administration. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning – the science behind ‘Big Data’ – is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Your placement will take up to one year and, if you are an overseas student, your visa will cover the two years of the programme. The placement attracts a salary and is assessed as part of your degree. You will be assigned a supervisor by the host company, who is responsible for directing your work. You will be assigned an academic supervisor, who visits to check if you are integrating successfully and the type of work being undertaken is appropriate, and supports you in general during your placement. If you cannot or decide not to take a placement, you revert to the normal one-year degree.

On completion of the course graduates will have:
Throughout your degree, you will have the opportunity to acquire the following skills:

- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.
- Work experience and appreciation of how your work fits into the organizational and development processes of a company.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant.

Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
Distributed and networked computation is now the paradigm that underpins the software-enabled systems that are proliferating in the modern world, with huge impact in the economy and society, from the sensor and actuator networks that are now connecting cities, to cyberphysical systems, to patient-centred healthcare, to disaster-recovery systems. Read more
Distributed and networked computation is now the paradigm that underpins the software-enabled systems that are proliferating in the modern world, with huge impact in the economy and society, from the sensor and actuator networks that are now connecting cities, to cyberphysical systems, to patient-centred healthcare, to disaster-recovery systems.

This new Masters course will educate and train you in the fundamental principles, methods and techniques required for developing such systems. Given the number of elective modules offered, you will be able to acquire further skills in one or more of Cloud Computing, Data Analytics and Information Security.

Facilities include a laboratory where you can experiment with physical devices that can be interconnected in a network, and a cluster facility configured to run the Hadoop MapReduce stack.

A Year in Industry option is also available for this course.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msc-distributed-and-networked-systems.aspx

Why choose this course?

This course will develop a highly analytical approach to problem solving and a strong background in distributed and networked systems, fault-tolerance and data replication techniques, distributed coordination and time-synchronisation techniques (leader-election, consensus, and clock synchronisation), data communication protocols and software stacks for wireless, sensor, and ad hoc networking technologies in virtualisation, and cloud computing technologies.

The course develops an advanced understanding of principles of failure detection and monitoring, principles of scalable storage, and in particular NoSQL technology.

Students will acquire the ability to:
- apply well-founded principles to building reliable and scalable distributed systems
- analyse complex distributed systems in terms of their performance, reliability, and correctness
- design and implement middleware services for reliable communication in unreliable networks
- work with state-of-the-art wireless, sensor, and ad hoc networking technologies
- design and implement reliable data communication 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)
- work with modern network management technologies (Software-Defined Networking) and standards (OpenFlow)
- design custom-built application-driven networking topologies using OpenFlow, and other modern tools
- work with relational databases (SQL), non-relational databases (MongoDb), as well as with Hadoop/Pig scripting and other big data manipulation techniques.

Department research and industry highlights

Royal Holloway is recognised for its research excellence in Machine Learning, Information Security, and Global Ubiquitous Computing.
We work closely with companies such as Centrica (British Gas, Hive), Cognizant, Orange Labs (UK), the UK Cards Association, Transport for London and ITSO.
We host a Smart Card Centre and we are a GCHQ Academic Centre of Excellence in Cyber Security Research (ACE-CSR).

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. If you are in the Year-in-Industry pathway, you then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Core course units are:
Interconnected Devices
Advanced Distributed Systems
Wireless, Sensor and Actuator Networks
Individual Project

Elective course units are:

Computation with Data
Databases
Introduction to Information Security
Data Visualisation and Exploratory Analysis
Programming for Data Analysis
Semantic Web
Multi-agent Systems
Advanced Data Communications
Machine Learning
Concurrent and Parallel Programming
Large-Scale Data Storage and Programming
Data Analysis
On-line Machine Learning
Smart Cards, RFIDs and Embedded Systems Security
Network Security
Computer Security
Security Technologies
Security Testing
Software Security
Introduction to Cryptography

Assessment

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

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different [department]-related areas, including This taught masters course equips postgraduate students with the subject knowledge and expertise required to pursue a successful career, or provides a solid foundation for continued PhD studies.

Read less
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies. Read more
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscmachinelearning.aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will gain in-depth knowledge and practical skills in Machine Learning techniques, which are used by companies such as Facebook, Google, Microsoft and Yahoo to develop the next generation of search and analysis technologies. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies. Read more
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies.

As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscmachinelearning(yearinindustry).aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will gain in-depth knowledge and practical skills in Machine Learning techniques, which are used by companies such as Facebook, Google, Microsoft and Yahoo to develop the next generation of search and analysis technologies. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.
- Work experience and appreciation of how your work fits into the organizational and development processes of a company.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
Starting in 2016, and currently under development, Royal Holloway will offer a new Masters in 'The Internet of Things' (IOT). The Internet of Things is a new and fast expanding area in Computer Science, technology and engineering. Read more
Starting in 2016, and currently under development, Royal Holloway will offer a new Masters in 'The Internet of Things' (IOT).

The Internet of Things is a new and fast expanding area in Computer Science, technology and engineering: it concerns the systems of networked devices that are now sensing, transmitting and acting on data. A series of reports place the IoT as a new and transformative technology domain that will require millions of developers by 2020.

The course will educate and train you in the key areas required for operating the generation of networks of connected devices that are starting to proliferate (smart homes, smart cities, smart cars, and so on): data analysis, storage and processing; distrbuted and networked systems; and information security.

Facilities include a laboratory where you can experiment with physical devices that can be interconnected in a network, and a cluster facility for processing and analysing real data sets.

Please note this programme is subject to validation.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msctheinternetofthings.aspx

Why choose this course?

The Masters in The Internet of Things at Royal Holloway will provide you with advanced knowledge and skills in three essential and critical areas:

- Data analytics is essential for getting value from the IOT. For example, in Formula One racing there are hundreds of sensors providing thousands of data points for analysis such as tyre pressure and fuel burn efficiency, which have to be collected in real-time for very quick analysis by race engineers onsite.

- Distributed computing and systems concern technical aspects such as algorithms for distributed coordination, time-synchronisation, scalable storage, virtualisation and cloud computing technologies, as well as methodological aspects such agent-based modelling and simulation.

- Cybersecurity is another essential aspect of the IOT. Recent news such as the safety recall issued by Fiat Chrysler of 1.4m vehicles in the US after tech magazine Wired reported that hackers had taken control of a Jeep Cherokee via its internet-connected entertainment system, are examples of how privacy, safety and security are major concerns for the IOT.

During your studies you will have 24/7-access to labs equipped with a state-of-the-art cloud computing testbed and a new generation of large-scale data processing platforms (such as Hadoop and MongoDB), which will give you the opportunity to gain hands-on experience working on real-life problems in areas as diverse as social network analytics, web data mining, and botnet detection.

Department research and industry highlights

Royal Holloway is recognised for its research excellence in Machine Learning, Information Security, and Global Ubiquitous Computing.

We work closely with companies such as Centrica (British Gas, Hive), Cognizant, Orange Labs (UK), the UK Cards Association, Transport for London and ITSO.

We host a Smart Card Centre and we are a GCHQ Academic Centre of Excellence in Cyber Security Research (ACE-CSR).

During your studies you will have 24/7-access to labs equipped with a state-of-the-art cloud computing testbed and a new generation of large-scale data processing platforms (such as Hadoop and MongoDB), which will give you the opportunity to gain hands-on experience working on real-life problems in areas as diverse as social network analytics, web data mining, and botnet detection.

Assessment

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

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different Computer Science-related areas, including This taught masters course equips postgraduate students with the subject knowledge and expertise required to pursue a successful career, or provides a solid foundation for continued PhD studies.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
Starting in 2016, and currently under development, Royal Holloway will offer a new Masters in 'The Internet of Things' (IOT) with a Year in Industry. Read more
Starting in 2016, and currently under development, Royal Holloway will offer a new Masters in 'The Internet of Things' (IOT) with a Year in Industry.

The Internet of Things is a new and fast expanding area in Computer Science, technology and engineering: it concerns the systems of networked devices that are now sensing, transmitting and acting on data. A series of reports place the IoT as a new and transformative technology domain that will require millions of developers by 2020.

The course will educate and train you in the key areas required for operating the generation of networks of connected devices that are starting to proliferate (smart homes, smart cities, smart cars, and so on): data analysis, storage and processing; distrbuted and networked systems; and information security.

Facilities include a laboratory where you can experiment with physical devices that can be interconnected in a network, and a cluster facility for processing and analysing real data sets.

Please note this programme is subject to validation.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msctheinternetofthingsyearinindustry.aspx

Why choose this course?

The Masters in The Internet of Things at Royal Holloway will provide you with advanced knowledge and skills in three essential and critical areas:

- Data analytics is essential for getting value from the IOT. For example, in Formula One racing there are hundreds of sensors providing thousands of data points for analysis such as tyre pressure and fuel burn efficiency, which have to be collected in real-time for very quick analysis by race engineers onsite.

- Distributed computing and systems concern technical aspects such as algorithms for distributed coordination, time-synchronisation, scalable storage, virtualisation and cloud computing technologies, as well as methodological aspects such agent-based modelling and simulation.

- Cybersecurity is another essential aspect of the IOT. Recent news such as the safety recall issued by Fiat Chrysler of 1.4m vehicles in the US after tech magazine Wired reported that hackers had taken control of a Jeep Cherokee via its internet-connected entertainment system, are examples of how privacy, safety and security are major concerns for the IOT.

During your studies you will have 24/7-access to labs equipped with a state-of-the-art cloud computing testbed and a new generation of large-scale data processing platforms (such as Hadoop and MongoDB), which will give you the opportunity to gain hands-on experience working on real-life problems in areas as diverse as social network analytics, web data mining, and botnet detection.

Department research and industry highlights

Royal Holloway is recognised for its research excellence in Machine Learning, Information Security, and Global Ubiquitous Computing.

We work closely with companies such as Centrica (British Gas, Hive), Cognizant, Orange Labs (UK), the UK Cards Association, Transport for London and ITSO.

We host a Smart Card Centre and we are a GCHQ Academic Centre of Excellence in Cyber Security Research (ACE-CSR).

Assessment

Assessment is carried out by a variety of methods including coursework, practical projects and a dissertation. The placement is assessed as part of the Year-in-Industry degree.

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different Computer Science-related areas, including This taught masters course equips postgraduate students with the subject knowledge and expertise required to pursue a successful career, or provides a solid foundation for continued PhD studies.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less

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