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Masters Degrees (Pig)

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Do you want to develop your technical pig production practice to postgraduate level?. Harper Adams University has developed a Masters degree in Pig Production. Read more
Do you want to develop your technical pig production practice to postgraduate level?

Harper Adams University has developed a Masters degree in Pig Production.
The course

Recognise the global context within which food production now operates.
Explore the sciences underpinning food animal husbandry and animal production systems
Support students to identify, analyse and solve biological, technological and economic problems encountered in pig production systems,
Support students to evaluate the wider global, environmental, economic, social, ethical and political issues associated with pig production systems.

How will it benefit me?
The course will:
Prepare students for a career in Pig Production.
Offer vocational training in the area of applied Pig Production.
Prepare students for PhD studies.

Example modules:
Pig Production Systems
Mono-gastric Nutrition and Ration Formulation
Pig Breeding
Genetics and Product Quality
Pig and Poultry Environment, Health and Welfare
Emerging Issues in Mono-gastric Production Systems
Major Research Project (MSc)

Elective Modules:
Elective modules from the list below can be studied in addition to the core modules identified above.

Food chain related
Food Product Development
Meat Science and Public Health
Animal Production, Meat Processing & Quality
Food Policy and Ethics

Farm Business Management
Farm Business Management
Farm Business Analysis
Farm Business Strategy

Agri-Business Management
Leadership & People Management
Principles of Finance
Strategic Management & International Agribusiness
Food Business Operations Management
Agri-Food Marketing

Systems Related
Precision Farming Technology
Animal Welfare and Bioethics

Modules are usually delivered as an intensive short course, taught over a one week block, with a maximum of 5 days per 15 credit module providing in the region of 35 hours of contact time.

Teaching may consist of formal lectures, seminars, tutorials, practical exercises, laboratory sessions, study visits or the use of guest speakers.

The PgC, PgD and MSc are offered full-time and part-time to allow those in work to study towards an award at a pace that suits their needs and time available.

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Our MSc/PGDip Clinical Periodontology programme provides the busy General Dental Practitioner with a part-time educational route to acquire the skills and knowledge required of a Dentist with Special Interest (DwiSI). Read more
Our MSc/PGDip Clinical Periodontology programme provides the busy General Dental Practitioner with a part-time educational route to acquire the skills and knowledge required of a Dentist with Special Interest (DwiSI). This programme focuses on contemporary practice, teaching evidence-based principles and systems to ensure an optimal outcome for the patient and practitioner.

Applicants will be invited to an Advice day held at Greenbank Building at UCLan, where prospective students will be given an opportunity to talk to the Course Leader and tour the specialist facilities including the UCLan Dental Clinic where students will carry out their 15 clinical placements throughout their course in which we provide the patients.

INDUSTRY LINKS

Completion of this programme of study provides 60 allowable credits towards the FGDP (UK) Career Pathway (Clinical); 30 allowable credits towards the Career Pathway (Other).

LEARNING ENVIRONMENT AND ASSESSMENT

The programme encompasses a blended learning approach and consists of a combination of lectures, seminars, workshops, and clinic training sessions. Each person will be assigned a personal tutor for the entire programme.

We offer MSc students 15 clinic placements in which we provide the patients at the UCLan Dental Clinic during the programme.

Each module of your course will have a series of assessments and examinations - these are designed to develop and test your core knowledge and skills at regular intervals throughout the programme. Assessments focus on your higher levels skills of diagnosis and planning, rather than simply remembering facts. Typical assessments would include analysis of given clinical cases, OSCEs, portfolios and essays.

LEARNING OUTCOMES

-Thorough case assessment and record taking
-Risk factors and their management
-Appropriate treatment planning
-Non-surgical management of periodontal disease
-Flap design and suturing
-Surgical procedures including crown lengthening
-Use of antibiotics as an adjunct to mechanical therapy
-Peri-implantitis

FURTHER INFORMATION

Our MSc/PGDip Clinical Periodontology programme provides the busy General Dental Practitioner with a part-time educational route to acquire the skills and knowledge required of a Dentist with Special Interest (DwiSI). This programme focuses on contemporary practice, teaching evidence-based principles and systems to ensure an optimal outcome for the patient and practitioner.

During the course (two years PGDip; three years MSc) you will be expected to attend up to 15 study/assessment days per year. Many of these sessions will be within the School of Medicine and Dentistry on the main UCLan Preston Campus, though some sessions will be timetabled in the UCLan Dental Clinic, where you will observe, assist and ultimately lead in clinical treatment. To accompany the study days, much of the course content, including lecture notes, PowerPoint slides, videos of lectures and assignments will be delivered to you via the University’s eLearn system allowing you to both prepare work for study days and undertake additional work independently from your home location.

Work in the early part of the course will comprise plenary lectures and practical sessions in our state-of-the-art phantom head facility and work on pig’s head and similar systems. As you move through the course you will progress to working on live patients under close supervision in the UCLan Dental Clinic. Here skills will be developed and assessed through Direct Observations of Procedural Skills (DOPS). The academic underpinning that supports this discipline will be developed though plenary lectures, directed reading and case-based discussions, which you and others in the group will be expected to prepare and lead. Group sizes are generally small (typically 12 per cohort) leading to an informal and supportive learning environment where you can ensure that your own learning needs are being met.

We must of course have assessments and examinations - these are designed to develop and test your core knowledge and skills at regular intervals throughout the programme. Assessments focus on your higher levels skills of diagnosis and planning, rather than simply remembering facts. Typical assessments would include analysis of given clinical cases OSCEs, mini clinical examinations and essays.

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This course will provide you with an in-depth specialisation in organic farming and food production systems and it is currently the only specialised MSc in organic and ecological farming in England. Read more

This course will provide you with an in-depth specialisation in organic farming and food production systems and it is currently the only specialised MSc in organic and ecological farming in England. You will learn and test the latest approaches in the integrated delivery of soil, crop and livestock, and food supply chain management.

Through a combination of lectures, field trips, seminars, practical classes and research projects you will develop advanced knowledge and skills in:

-Managing organic farming and food production units or businesses in different macroclimatic, agronomic and market contexts

-Agronomic approaches used in organic/biological/ecological/sustainable food production systems

-Underlying principles and standards of organic/biological/ecological/sustainable food production, processing and retailing/marketing systems

-Applied and strategic research underpinning the development of organic and other sustainable farming and food production systems

-A wide range of analytical laboratory methods

You will have the opportunity to attend a 10-day field trip as part of the module on Mediterranean perennial crop production systems in Crete, Greece. The trip is organised in collaboration with ecological farming experts from the Greek National Science Foundation (NAGREF).

As part of your studies you will also undertake a major project, similar to one you might experience in the workplace. You will be supported through training in designing and delivering a laboratory project or field-based investigation. You will collect, analyse and interpret data to produce a thesis reporting your investigation and results in a critical manner.

This research project and thesis may be undertaken at the University, in industry, in Crete as part of existing Nafferton Ecological Farming Group research and development projects, or in another country.

Our staff

You will benefit from being taught by lecturers who are industry experienced and research active. Our research in integrated agricultural production focuses on soil science, plant science and ecology, spanning a range of scales from: pot – plot – farm – landscape.

Strategic research embraces work on:

-Soil quality

-Rhizosphere function

-Plant-soil feedback

-Soil-carbon dynamics

-Nutrient cycling

Applied research addresses issues of:

-Climate change mitigation (including biofuels)

-Ecological (organic) farming systems

-Low-input crop systems

-Agriculture-environment interactions

Professor Carlo Leifert is the Degree Programme Director for MSc in Organic Farming and Food Production Systems. Carlo is a member of the Food Security Network in the Newcastle Institute for Research on Sustainability (NIReS) and is part of the Nafferton Ecological Farming Group (NEFG). He currently manages EU and DEFRA funded projects focused on improving resource efficiency, productivity and food quality and safety in organic and 'low input' crop and livestock production systems.

Delivery

The course is taught in a block format with a six-week block and then two-week teaching blocks.

You will be taught through:

-Lectures

-Seminars

-Practical and field classes

-Tutorials

-Case studies

-Small group discussions

You will be expected to undertake independent study outside of these structured sessions. Your knowledge and understanding will be assessed through written examinations, coursework, presentations and your final major project.

You can also study through the Credit Accumulation Transfer Scheme (CATS). This allows us to award postgraduate level qualifications using credit-bearing stand-alone modules as 'building blocks' towards a qualification. This means that the credits from modules undertaken within a five-year period can be 'banked' towards the award of a qualification.

Facilities

Farms

Our multi-purpose farms provide demonstration facilities for teaching purposes and land-based research facilities (especially in the area of organic production). They are both viable farming businesses.

Cockle Park Farm

Cockle Park Farm is a 262ha mixed farm facility that includes the Palace Leas Plots hay meadow experiment and a new anaerobic digestion plant that will generate heat, electricity and digestate - an organic fertiliser - from pig and cattle manure.

Nafferton Farm

Nafferton Farm is a 300ha farm with two main farm units covering conventional and organic farming systems. The two systems are primarily focussed upon dairying and arable cropping.

Both also operate beef production enterprises as a by-product of their dairy enterprises, although the organic system is unique in maintaining a small-scale potato and vegetable production enterprise.

Laboratories

Our modern laboratories provide important teaching and research environments and are equipped with analytical equipment such as High-Performance Liquid Chromatography (HPLCs), GCs, CNS analyser (Carbon and Nitrogen analysis), centrifuges, spectrophotometers and molecular biology equipment. Our specialist research facilities include:

  • tissue culture laboratory
  • plant growth rooms
  • class II laboratory for safe handling of human biological samples
  • taste panel facilities and test kitchen
  • thin section facility for soils analysis

We operate closely with other schools, institutes and the University's central scientific facilities for access to more specialist analytical services.

For work with human subjects we use a purpose built Clinical Research Facility which is situated in the Royal Victoria Infirmary teaching hospital and is managed jointly by us and the Newcastle upon Tyne Hospitals NHS Foundation Trust.

nu-food Food and Consumer Research Facility

The NU-Food Food and Consumer Research Facility has undergone a £700,000 refurbishment and now boasts a culinary training suite, a sensory laboratory and food handling facility, all supported by multi-functional rooms and a reception.



Read less
The rapid growth of technological and scientific innovation in genetics, biotechnology, conservation biology, reproduction and nutrition has resulted in a need for further training for scientists across animal industries in all areas. Read more
The rapid growth of technological and scientific innovation in genetics, biotechnology, conservation biology, reproduction and nutrition has resulted in a need for further training for scientists across animal industries in all areas. The Master of Animal Science offers you advanced technical training in a focused area of animal science: genetics, nutrition or reproduction, biotechnology and animal production. Undertaking electives from a range of units of study, you will be equipped with advanced skills applied in a variety of industres including poultry, wildlife, pig, aquaculture, dairy, companion and pedigree animals, sheep and beef. The course is designed to enhance your research skills in managing the planning and implementation of a successful research project and in designing, conducting and writing-up a research project.

To ask a question about this course, visit http://sydney.edu.au/internationaloffice/

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The MSc has been devised through input from academics and industry experts and provides a learning environment in which individuals can develop their conceptual approach to the intensive livestock food chain and their proficiencies in terms of skills, knowledge and attitudes as competent and reflective agri-food sector professionals. Read more
The MSc has been devised through input from academics and industry experts and provides a learning environment in which individuals can develop their conceptual approach to the intensive livestock food chain and their proficiencies in terms of skills, knowledge and attitudes as competent and reflective agri-food sector professionals.

Under the microscope

With global demand for farmed livestock and fish products continuing to grow, there are exciting opportunities for professionals working within these sectors. Improvements in productivity are required for the livestock and aquaculture industries to remain competitive, meet global demand, ensure food security and to reduce environmental impact. Our online courses are designed specifically to enable professional development and promote industry specific skills for individuals working with intensively farmed livestock.

By addressing the challenges faced by those working in agricultural industries such as; pig production and poultry production, as well as aquaculture and food safety, our distance learning courses are helping to improve the standards of the intensive farming industries, while allowing individuals from across the globe to expand their knowledge and realise their career goals.

Modules

- Applied animal nutrition
- Infectious diseases of intensively reared pigs
- Infectious diseases of intensively reared poultry
- Animal health economics
- Food safety: a system-wide approach
- Biosecurity
- Genetics and genomics
- Applied animal welfare
- Epidemiology

How will I learn?

This course is delivered on a part-time, distance learning basis. It is structured online and takes between 2 and 5 years, making the most effective use of virtual learning tools, including online library access, discussion forums, and multimedia resources. This delivery allows you to study for your qualification alongside work and family responsibilities. You will however be required to attend campus for induction and some assessments depending on choice of elective modules at PG Diploma level.

Learning outcomes

MSc graduates will be able to:

- Understand and evaluate theories, methods and practice of the agri-food system that can be applied to their area of the intensive livestock production industry
- Demonstrate a critical awareness of current problems and new insights from across the intensive livestock production industry
- Develop new processes/techniques to improve intensive livestock production, supporting animal health and welfare
- Identify, critically assess and address the emerging needs of the intensive livestock sector
- Adopt new techniques to improve skills development
- Be a reflective, self-evaluative and self-managing professional
- Critically appraise research and practices in livestock and related food production fields, and develop skills to undertake qualitative and quantitative research using appropriate methods
- Continue to develop independent and lifelong learning skills to promote their own personal and professional development as producers, researchers and leaders.

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 .

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.

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

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