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Information Technology is now fundamental in every aspect of our daily lives. IT systems are crucial for delivering every day services such as banking, web based services and information systems. Read more
Information Technology is now fundamental in every aspect of our daily lives. IT systems are crucial for delivering every day services such as banking, web based services and information systems.

The MSc Information Technology is a full time, one year taught course, intended for students who are seeking a professional career in the IT industry. There is no requirement for a first degree in computing, but proficiency in at least one programming language is a requirement.

The course covers a range of topics including advanced programming, user-interface design, software engineering and management.

This course will give you the knowledge of IT from an organisation oriented viewpoint, allowing you to be capable of designing and implementing IT systems for a wide range of organisations.

The course has been specifically designed to suit the requirements of the IT industry, where you will be able to take up technical or management positions. Our graduates enter employment in many roles, including computer programmers, technical authors and research associates.

Course Aims
-Programming: You will gain a thorough grounding of advanced programming concepts using Java including efficient data structures and algorithms and high performance distributed computing.
-User-Interfaces: You will learn the theory of human computer interaction (HCI) and put this into practice in a number of ways, including user centred design of aspects of people's interaction with digital systems.
-Software Engineering: You will learn and be able to apply the principles of software engineering and case studies using UML, software testing techniques, and privacy and security aspect of software systems.

Learning Outcomes
We expect our graduates to be capable of designing and implementing IT systems for a wide range organisations. A thorough understanding of the following subjects are expected:
-Designing user interfaces following sound principles of interface design
-Designing, specifying, implementing and testing software components and systems using UML, Java and a range of software testing techniques
-Dependability of IT systems including topics in privacy and security
-Computer architectures and high performance distributed computing

Project

The dissertation project undertaken by students in Terms 3 and 4 (Summer Term and Vacation Term) is carried out individually, which might involve collaboration with another organisation. The subject matter of projects varies widely; most projects are suggested by members of staff, some by external organisations, and some by students themselves, usually relating to an area of personal interest that they wish to develop further.

A collaborative project is supervised by a member of the Department, but the collaborating organisation will normally provide an external supervisor. Organisations that have collaborated in projects in the past include Glasgow Town Planning Department, British Rail Passenger Services Department, North Yorkshire Police, North Yorkshire Fire Services, NEDO, the Royal Horticultural Society, Biosis UK, Centre Point sheltered housing, York Archaeological Trust, and the University of York Library.

The subject matter of projects varies widely; most projects are suggested by members of staff, some by external organisations, and some by students themselves, perhaps relating to an area of personal interest that they wish to develop further.

All project proposals are rigorously vetted and must meet a number of requirements before these are made available to the students. The department uses an automated project allocation system for assigning projects to students that takes into account supervisor and student preferences.

Examples of previous project include:
-A Study into the User Experience and Usability of Web Enabled Services on Smartphones
-Agent simulation of large scale complex IT systems
-Do People Disclose their Passwords on Social Media?
-Dynamic Sound Generation for Computer Games
-Iterative linear programming as an optimisation method for buyer resources in online auctions evaluated using a Java-based Monte Carlo simulation
-Qchat (Web-based chat application for quantum physicists)
-Software for dyslexic readers: an empirical investigation of presentation attributes
-Web-based IQ Testing Application for Fluid Intelligence Analysis
-Agent simulation of large scale complex IT systems

Information for Students

Whilst the MSc in Information Technology does not require a formal qualification in computing, we do expect you to have some understanding of computer related issues.

As everyone arrives with different experience, we have put together the following summary of what we expect you to know, with some suggestions of how you can prepare before you arrive.

You'll start the course with a focus on writing and developing Java programs. We assume that you are familiar with programming concepts and terminology, so we advise you to review basic programming concepts, such as:
-Variables and their types
-Control structures (e.g. if-statements, loops)
-Subprograms (e.g. procedures, functions)
-Compilation and debugging.

If you have never used Java, you will benefit greatly from doing some reading and trying out Java programming before you arrive. We will teach you from first principles, but the pace will be fast and you will find it easier to keep up if you've practiced with the basics beforehand. Tutorials and practical exercises are the best way for you to prepare, and the Deitel and Deitel book below is a good source of these.

Careers

Here at York, we're really proud of the fact that more than 97% of our postgraduate students go on to employment or further study within six months of graduating from York. We think the reason for this is that our courses prepare our students for life in the workplace through our collaboration with industry to ensure that what we are teaching is useful for employers.

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We will provide you with an advanced and challenging study of the main management disciplines of finance, marketing, supply chain and human resources. Read more
We will provide you with an advanced and challenging study of the main management disciplines of finance, marketing, supply chain and human resources. You will apply modern business and management techniques to an organisation's problems in the context of the wider business world and global community.

This is your opportunity to improve your personal and interpersonal competencies, intellectual skills and self-motivation through problem-solving, mutual support, participative personal development planning and reflective learning.

This course provides an opportunity for graduates with a non-business degree background to gain knowledge of management principles and practice. It is also recommended if you are a graduate with a businessor management degree seeking to achieve a management-based masters.

Faculty of Business & Law website - hhttps://www.leedsmet.ac.uk/fbl/

January entrants please note: in order to complete 12 months of academic study delivered in University term time, the total length of your programme will be 18 months to include recognised University vacation periods.

- Research Excellence Framework 2014: twice as many of our staff - 220 - were entered into the research assessment for 2014 compared to the number entered in 2008

Visit the website http://courses.leedsbeckett.ac.uk/management_msc

Mature Applicants

Our University welcomes applications from mature applicants who demonstrate academic potential. We usually require some evidence of recent academic study, for example completion of an access course, however recent relevant work experience may also be considered. Please note that for some of our professional courses all applicants will need to meet the specified entry criteria and in these cases work experience cannot be considered in lieu.

If you wish to apply through this route you should refer to our University Recognition of Prior Learning policy that is available on our website (http://www.leedsbeckett.ac.uk/studenthub/recognition-of-prior-learning.htm).

Please note that all applicants to our University are required to meet our standard English language requirement of GCSE grade C or equivalent, variations to this will be listed on the individual course entry requirements.

Careers

Successful achievement of our MSc Management will enable you to apply for a general management role within a range of different businesses both in the public and private sector. The starting salaries will vary depending on your previous experience, but this qualification will add value to you by equipping you with the management skills to complement your previous area of study.

- Business Development Manager
- General Manager
- Project Manager
- Area Manager

Careers advice: The dedicated Jobs and Careers team offers expert advice and a host of resources to help you choose and gain employment. Whether you're in your first or final year, you can speak to members of staff from our Careers Office who can offer you advice from writing a CV to searching for jobs.

Visit the careers site - https://www.leedsbeckett.ac.uk/employability/jobs-careers-support.htm

Careers

If you wish to develop your career in general management, this course can help you develop the skills you'll need to progress in management. You will acquire the confidence and competence to address the demands placed upon managers, providing you with a recognised qualification and a platform to progress in your chosen field. As the course is open to both non-business and business graduates, there is a mix of skills and experience on the course which enables participants to enhance one another's learning experiences.

The teaching team consists of experienced deliverers of management education, both within higher education as well as for several professional bodies. They also possess many years of practical managerial experience, enabling them to relate theory to practice as well as bringing the latest industry issues and trends into the classroom.

At Leeds Business School we're dedicated to supporting your professional development - that's why we offer a guest lecture programme. Past speakers include the CEO of the London Stock Exchange, Shadow Chief Secretary to the Treasury, past Chair and President of the Academy of Marketing, Chief Executive of the British Bankers Association, the Chief Economist of Yorkshire Bank and the Editor of Cosmopolitan. To see our full programme and to register for a lecture click here (http://www.leedsmet.ac.uk/guestspeakers).

Core Modules

Business Data: Management & Analysis
Develop competences in data collection issues and decision analysis techniques. You will also gain an understanding of the use of linear programming in optimisation problems and the role of statistical inference in model building.

Corporate Strategy
Develop a strategic organisational perspective as well as a basis for progression and application of strategic level skills, competencies, and decision-making capability.

Global Supply Chain Management
You'll be introduced to the supply chain concept by observing a variety of companies and how they are changing their business practices to achieve corporate objectives in the current economic climate.

Management, People & Organisations
Develop functional knowledge and a critical understanding of key perspectives on human behaviour within an organisation and on the nature and processes of organising and managing human activity.

Managing Financial Resources
Gain a critical understanding of contemporary accounting and financing principles which support business decision-making and financial resourcing in both the private and public sectors.

Marketing
Develop your knowledge and understanding of the principles and theoretical foundations which govern the modern marketing environment, allowing you to progress in a specialised area of marketing such as international or services marketing.

Dissertation
You will carry out an in-depth research project in a subject area that is appropriate to the course and of particular interest to you.

Garry Carr

Senior Lecturer

"Teaching on the MSc Management course is an exciting prospect, as our students arrive from a variety of backgrounds, each with varying experiences, and this really enriches the classroom experience."

Garry has more than 20 years' experience teaching at both undergraduate and postgraduate level. He is a Senior Fellow of the Higher Education Academy and a member of the American Academy of Management. He has consultancy experience within the private and public sectors and has research interests in strategic management, the creative industries and organisational theory.

Facilities

- Library
Our libraries are two of the only university libraries in the UK open 24/7 every day of the year. However you like to study, the libraries have got you covered with group study, silent study, extensive e-learning resources and PC suites.

- The Rose Bowl
The Rose Bowl has impressive teaching spaces, auditoriums, conference facilities and an outstanding local reputation as a business hub. The Rose Bowl puts our students at the centre of a dynamic business community.

Find out how to apply here - http://www.leedsbeckett.ac.uk/postgraduate/how-to-apply/

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Designed for aspiring finance professionals who want to gain specialist knowledge, this course will equip you with the skills required for seeking employment in the increasingly complex and demanding financial services sector. Read more
Designed for aspiring finance professionals who want to gain specialist knowledge, this course will equip you with the skills required for seeking employment in the increasingly complex and demanding financial services sector.

You will explore the theories and current practice in the finance industry from both a national and international perspective. The course blends theory with practice to provide you with the applied vocational skills that potential employers require.

You'll study in the heart of Leeds, which is the largest hub of financial services in the UK outside London. Leeds is home to many leading financial organisations and large professional services firms. You'll be taught by a range of highly experienced tutors with industrial, professional and academic knowledge.

We include a strong international dimension in the course content and attract students from as far and wide as China, India, Pakistan and Vietnam.

Faculty of Business & Law website (https://www.leedsmet.ac.uk/fbl/)
Request a call back (http://www.leedsmet.ac.uk/study/postgraduate.htm)

January entrants please note: in order to complete 12 months of academic study delivered in University term time, the total length of your programme will be 18 months to include recognised University vacation periods.

- Research Excellence Framework 2014: twice as many of our staff - 220 - were entered into the research assessment for 2014 compared to the number entered in 2008.

Visit the website http://courses.leedsbeckett.ac.uk/finance_msc

Mature Applicants

Our University welcomes applications from mature applicants who demonstrate academic potential. We usually require some evidence of recent academic study, for example completion of an access course, however recent relevant work experience may also be considered. Please note that for some of our professional courses all applicants will need to meet the specified entry criteria and in these cases work experience cannot be considered in lieu.

If you wish to apply through this route you should refer to our University Recognition of Prior Learning policy that is available on our website (http://www.leedsbeckett.ac.uk/studenthub/recognition-of-prior-learning.htm).

Please note that all applicants to our University are required to meet our standard English language requirement of GCSE grade C or equivalent, variations to this will be listed on the individual course entry requirements.

Careers

This course has a proven track record of graduates gaining employment in the financial services sector, such as banking or insurance. Others have entered into their family business, taking on a variety of management level roles. A small number have remained in the education sector to study a PhD and have entered into the teaching profession.

- Financial Analyst
- Financial Advisor
- Director of Finance
- Chief Financial Officer

Careers advice:
The dedicated Jobs and Careers team offers expert advice and a host of resources to help you choose and gain employment. Whether you're in your first or final year, you can speak to members of staff from our Careers Office who can offer you advice from writing a CV to searching for jobs.

Visit our careers site - https://www.leedsbeckett.ac.uk/employability/jobs-careers-support.htm

Course Benefits

Our MSc Finance is delivered in the heart of Leeds, which is the largest hub of financial services in the UK outside London and which is home to many leading financial organisations and large professional services firms.

The course is delivered by a range of highly experienced tutors with industrial, professional and academic experience. The course emphasises blending theory with practice and thus provides students with the applied vocational skills that potential employers require. It is international both in terms of content and the student mix which provides a multicultural learning environment.

At Leeds Business School we're dedicated to supporting your professional development - that's why we offer a guest lecture programme. Past speakers include the CEO of the London Stock Exchange, Shadow Chief Secretary to the Treasury, past Chair and President of the Academy of Marketing, Chief Executive of the British Bankers Association, the Chief Economist of Yorkshire Bank and the Editor of Cosmopolitan. To see our full programme and to register for a lecture click here (http://www.leedsmet.ac.uk/guestspeakers).

Core Modules

Corporate Finance
Evaluate the fundamental concepts and theories of modern finance, identifying how these can be effectively applied in both national and multinational organisations.

Financial Decision Analysis
Cover topics on decision theory (decision trees and tables), linear programming, regression, time series, portfolio optimisation, discounted cash flow and finance.

Financial Economics
Gain a comprehensive economic analysis of the operation, efficiency and dependencies between financial markets and their associated institutions. You will also assess the impact upon the world economy of any failure of the financial sector.

Managing Financial Resources
Gain a critical understanding of contemporary accounting and financing principles which support business decision-making and financial resourcing in both the private and public sectors.

Understanding the Economy
Develop knowledge and a critical understanding of the workings of a major economy which is subject to a constantly changing global environment, de-regulated financial systems, modern mass communication and international monetary flows.

Dissertation
You will carry out an in-depth research project in a subject area that is appropriate to the course and of particular interest to you.

Option Modules

Forensic Accounting
Discover the need for and role of corporate governance in the business environment, the role of IT in forensic accounting and fraud detection and the types and incidences of fraud.

Investment Fund Management
You will identify, understand, evaluate and compare types of investment for the private investor, including tools, methods and strategies.

Management of International Finance
Gain a comprehensive understanding of the economics of the operation and organisation of national and international financial systems.

"We are proud of the success of our national and international graduates."
- Professor Christopher Prince
Dean and Pro Vice Chancellor of the Faculty of Business and Law

Facilities

- Library
Our libraries are two of the only university libraries in the UK open 24/7 every day of the year. However you like to study, the libraries have got you covered with group study, silent study, extensive e-learning resources and PC suites.

- The Rose Bowl
The Rose Bowl has impressive teaching spaces, auditoriums, conference facilities and an outstanding local reputation as a business hub. The Rose Bowl puts our students at the centre of a dynamic business community.

Find out how to apply here - http://www.leedsbeckett.ac.uk/postgraduate/how-to-apply/

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The MSc Civil Engineering programme is ideal if you would like to broaden and deepen your technical knowledge of specialised civil engineering areas and develop a wider perspective and understanding of the issues facing the civil engineering industries. Read more
The MSc Civil Engineering programme is ideal if you would like to broaden and deepen your technical knowledge of specialised civil engineering areas and develop a wider perspective and understanding of the issues facing the civil engineering industries. It provides a distinctive educational platform to encourage the development of articulate, numerate, literate, imaginative, versatile, confident and inquisitive postgraduates who are able to link the theoretical with the practical.

About the course

The course is designed for those who have already graduated with a civil engineering or engineering-related degree. Successful completion of the MSc is designed to provide the educational base for progression to Chartered Engineer (CEng) status.

You will obtain advanced analytical skills in your chosen subject areas. You will have the opportunity to learn to design steel and concrete framed structures using modern structural analysis software, use advanced theory for the design and implementation of geotechnical works, apply advanced hydraulic concepts and model hydraulic systems, learn about advanced materials technologies and use advanced techniques to model transport and other systems. You will develop skills in project management and can choose whether you want to learn about environmental management or construction law and sustainable procurement.

In structures, you will also learn to assess existing buildings and design adaptations and apply the stiffness matrix method to analyse two-dimensional structures. In geotechnical engineering you will design earthworks, and slope and retaining walls. In hydraulics you will study open channel and pipe flow and urban pollution management. In materials you will learn about special concretes and sustainability and materials repair and rehabilitation. In transport you will apply linear programming and queuing theory to practical problems.

For more information please visit http://www.bolton.ac.uk/postgrad

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Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Read more
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

Our Department of Mathematical is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

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The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Read more
The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Its more than 2,500 students are engaged in a wide variety of challenging courses and hands-on learning experiences that extend across all areas of the humanities and sciences – from the great philosophers and classic literature to the world economy and environmental sustainability.

At the core of each department are faculty members who have garnered national acclaim for their best-selling books, ground-breaking research and creative endeavors. Together, students and their professors explore globally significant subjects and work towards the goal of improving every aspect of the way in which human beings live. To learn more about a specific area of study, click on the left-hand navigation bar for a full listing of academic departments.

The department

The Department of Mathematics provides numerous undergraduate and graduate level courses that will enable you to master the mathematical methods and sophisticated reasoning and problem-solving skills essential to a wide variety of fields. In addition, the department offers a program to become an actuary.

The bachelor’s and master’s degree programs are designed to provide flexibility while emphasizing mathematical reasoning and problem solving, preparing the student for graduate school or a career in mathematics in secondary school teaching, business, industry, government or academia. In addition, a degree in mathematics is regarded as excellent preparation for entrance to professional schools of law, medicine or business.

M.S. in Applied Mathematics

The Master of Science degree program in Applied Mathematics offers specializations in either Classical Mathematics or Computer Mathematics. Classical Mathematics focuses on the foundations of modern mathematical theory, covering linear algebra, numerical methods and complex analysis. Computer Mathematics combines the fields of mathematics and technology through courses such as logic and information, applications of analysis, linear programming and statistics.

The faculty members in the Department of Mathematics are experts in areas such as topological groups, probability theory, differential geometry, number theory, dynamical systems and computer graphics, real analysis, numerical analysis, abstract algebra, combinatorics and history of mathematics.

Many of our graduates have gone on to receive Ph.D.’s from prestigious institutions. LIU Post graduates also are qualified for rewarding positions in actuarial science, insurance, finance, engineering, manufacturing and education.

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Who is this course for?. Recent graduates in Electrical or Electronic Engineering or Computer Science, who wish to develop their skills in the field of distributed computing systems. Read more
Who is this course for?
Recent graduates in Electrical or Electronic Engineering or Computer Science, who wish to develop their skills in the field of distributed computing systems.
Practicing engineers and computer professionals who wish to develop their knowledge in this area.
People with suitable mathematical, scientific or other engineering qualifications, usually with some relevant experience, who wish to enter this field.

Modules

Computer Networks, which aims to advance knowledge on computer networks. Topics to be covered in this module include OSI reference model, Physical and Data Link Layer Protocols, TCP/IP Networking, IPv6, Routing Protocols, Asynchronous Transfer Mode (ATM) Networks, Packet Delay and Queuing Analysis, IP Quality of Services (Integrated Service Model and Differentiated Service Model), Resource Reservation Protocol (RSVP), Multi-Protocol Label Switching (MPLS), IP Multicasting, Network Application Layer Protocols such as HTTP, DNS, SNMP.

Network Computing, which focuses on principles and techniques for network computing. Topics to be covered in this module include Object-Oriented Software Engineering, Object-Oriented Programming with Java, Network Computing Models such as Client/Server Model and Peer-to-Peer Model, Socket Programming, Remote Procedure Call (RPC), Java Remote Method Invocation (RMI), Common Object Request Broker Architecture (CORBA), Web Computing Technologies (Java Servlet, Java Server Pages), Message Exchanging with XML, Service Oriented Architecture (SOA), XML based Web Services (WSDL, SOAP, UDDI).

Network Security and Encryption, which introduces the fundamental theory that enables what is achievable through the use of Security Engineering to be determined, and presents the practical techniques and algorithms that are currently important for the efficient and secure use of distributed /Grid computing systems. Topics to be covered in this module include Introduction to Security Engineering, Classical Cryptography (Monoalphabetic and Polyalphabetic Ciphers, Transposition, Substitution, Linear Transformation), Computational Fundamentals of Cryptosystems (Computational Complexity and Intractability, Modular Arithmetic and Elementary Number Theory), Modern Symmetric Key Cryptography (Feistel Ciphers, DES, Triple-DES and AES),Public Key Cryptography (The Diffie-Hellman Key Exchange Algorithm, Public Key Infrastructures, X.509 Certificates, PK Systems such as RSA and Elliptic Curves), Multilevel Security (the Bell-LaPadula Security Policy Model, the Biba Model, the NRL Pump), Multilateral Security (Compartmentation and the Lattice Model, the Chinese Wall, the BMA Model), Protecting e-Commerce Systems.

Distributed Systems Architecture, which presents a comprehensive evaluation of the design philosophies, fundamental constructs, performance issues and operational principles of distributed systems architectures, covering applications, algorithms and software architecture, engineering issues and implementation technology. Topics to be covered in this module include System Architecture (Bus Systems, High Performance I/O, Memory Hierarchies, Memory Coherence and File Coherence), Distributed Database, Processor Architecture, File Services, Inter-Process Communication, Naming Services, Resource Allocation and Scheduling, Distributed System Case Studies.

Grid Middleware Technologies, which introduces the principle, concepts and practice of Grid middleware technologies, and provides a practical knowledge on developing Grid applications. Topics to be covered in this module include Parallel Computing Paradigms, Parallel Programming with MPI/PVM, Cluster Computing Principles (Condor, Sun Grid Engine), Grid Computing Middleware Components (Job Submission, Resource Management and Job Scheduling, Information Service, Grid Portal, Grid Security Infrastructure), Grid Standards (OGSA/WSRF), Grid Middleware Case Study with Globus.

Grid System Analysis and Design, which aims to analyse representative production Grid systems and gain knowledge on how to design and optimise large-scale Grid systems. Topics to be covered in this module include System Analysis Methodologies with UML, Model Construction (Process Modelling, Static Class Modelling, Dynamic Modelling, Interface Modelling), Management of Large-Scale Grid System (Portal, Concurrent Version System (CVS)/Wiki), Grid System Analysis Case Study (GridPP, LCG/EGEE), Grid System Design (Performance Consideration, Open Standards, Design Patterns, Usability Analysis), Grid System Programming Models, Testing (Unit Testing, Integration Testing, Regression Testing), Debugging, Risk Analysis, System Maintenance.

Project Management, which introduces a range of formal methods and skills necessary to equip the student to function effectively at the higher levels of project management. Covers the need for the development of project management skills in achieving practical business objectives.

Workshop involves practical work, which is an important component of the course and gives students experience with relevant techniques and tools. Assignments are of practical nature and involve laboratory work with relevant equipment, hardware and software systems, conducted in a hands-on workshop environment. Typical assignments are:
TCP/IP Network Layered Protocol Analysis
Object-Oriented Programming, Java Socket Programming
Network Security and Encryption
Java RMI Programming for Distributed Systems
Grid Programming with Globus Toolkit 4 (GT4)
Grid System Analysis/Simulation

Dissertation, which is a stimulating and challenging part of the MSc programme. It provides the opportunity to apply the knowledge learnt in the taught part of the programme and to specialise in one aspect, developing students’ deep understanding and expertise in Distributed Systems related area of their choice. Students may carry out their projects wholly within the University, but industrial based projects are encouraged.

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The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. Read more
The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

Visit the website: http://www.ucc.ie/en/ckr49/

Course Details

The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and Statistics; designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.

Format

A typical 5 credit module:
• 2 lecture hours per week
• 1–2 hours of practicals per week
• Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.

Structure

Students must attain 90 credits through a combination of:

- Core Modules (30 credits)
- Elective Modules (30 credits)
- Dissertation (30 credits)

Part 1 (60 credits)

- Core Modules (30 credits) -

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

- Database Modules -

Students who have adequate database experience take:

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen

- Students who have not studied databases take:

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits)

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

- Programming Modules -

Students who have adequate programming experience take:

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

- Students who have not studied programming take:

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)

Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)

Assessment

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016 - http://www.ucc.ie/modules/

Postgraduate Diploma in Data Science and Analytics

Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.

Careers

This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting Computer Science graduates in 2014-15 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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Master in BIG DATA. Read more
Master in BIG DATA : Data Analytics, Data Science, Data Architecture”, accredited by the French Ministry of Higher Education and Research, draws on the recognized excellence of our engineering school in business intelligence and has grown from the specializations in Decision Support, Business Intelligence and Business Analytics. The Master is primarily going to appeal to international students, "free movers" or those from our partner universities or for high-potential foreign engineers who are looking for an international career in the domain of Business Analytics.

This program leads to a Master degree and a Diplôma accredited by the French Ministry of Higher Education and research.

Objectives

Business Intelligence and now Business Analytics have become key elements of all companies.

The objective of this Master is to train specialists in information systems and decision support, holding a large range of mathematic- and computer-based tools which would allow them to deal with real problems, analyzing their complexity and bringing efficient algorithmic and architectural solutions. Big Data is going to be the Next Big Thing over the coming 10 years.

The targeted applications concern optimization in the processing of large amounts of data (known as Big Data), logistics, industrial automation, but above all it’s the development of BI systems architecture. These applications have a role in most business domains: logistics, production, finance, marketing, client relation management.

The need for trained engineering specialists in these domains is growing constantly: recent studies show a large demand of training in these areas.

Distinctive points of this course

• The triple skill-set with architecture (BI), data mining and business resource optimization.
• This master will be run by a multidisciplinary group: statistics, data mining, operational research, architecture.
• The undertaking of interdisciplinary projects.
• The methods and techniques taught in this program come from cutting-edge domains in industry and research, such as: opinion mining, social networks and big data, optimization, resource allocation and BI systems architecture.
• The Master is closely backed up by research: several students are completing their end-of-studies project on themes from the [email protected] laboratory, followed and supported by members from the laboratory (PhD students and researcher teachers).
• The training on the tools used in industry dedicated to data mining, operational research and Business Intelligence gives the students a plus in their employability after completion.
• Industrial partnerships with companies very involved in Big Data have been developed:
• SAS via the academic program and a ‘chaire d’entreprise’ (business chair), allowing our students access to Business Intelligence modules such as Enterprise Miner (data mining) and SAS-OR (in operational research).

Practical information

The Master’s degree counts for 120 ECTS (European Credit Transfer System) in total and lasts two years. The training lasts 1252 hours (611 hours in M1 and 641 hours in M2). The semesters are divided as follows:
• M1 courses take place from September until June and count for a total of 60 ECTS
• M2 courses take place from September until mid-April and count for a total of 42ECTS
• A five-month internship (in France) from mid- April until mid- September for 9 ECTS is required and a Master thesis for 9 ECTS.

Non-French speakers will be asked to participate to a one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions.

[[Organization ]]
M1 modules are taught from September to June (60 ECTS, 611 h)
• Data exploration
• Inferential Statistics (3 ECTS, 30h, 1 S*)
• Data Analysis (2 ECTS, 2h, 1 S)
• Mathematics for Computer science
• Partial Differential Equations and Finite Differences (3 ECTS, 30h, 1 S)
• Operational Research: Linear Optimization (2 ECTS, 20h, 1 S)
• Combinatory Optimization (2 ECTS, 18h, 1 S)
• Complexity theory (1 ECTS, 9h, 1 S)
• Simulation and Stochastic Process (3 ECTS, 30h, 2 S**)
• Introduction to Predictive Modelling (2ECTS, 21h, 2 S)
• Deterministic and Stochastic Optimization (3 ECTS, 30h, 2 S)
• Introduction to Data Mining (2 ECTS, 21h, 2 S)
• Software and Architecture
• Object-Oriented Modelling (OOM) with UML (3 ECTS, 30h, 1 S)
• Object-Oriented Design and Programming with Java (2 ECTS, 30h, 1 S)
• Relational Database: Modelling and Design (3ECTS, 30h, 1 S)
• PLSQL (2 ECTS, 21h, 2 S)
• Architecture and Network Programming (3 ECTS, 30h, 2 S)
• Parallel Programming (3 ECTS, 30h, 2 S)
• Engineering Science
• Signal and System (3 ECTS, 21 h, 1 S)
• Signal processing (3 ECTS, 30h, 1 S)

• Research Initiation
• Scientific Paper review (1 ECTS, 9h, 1 S)
• Final research project on BIG DATA (5 ECTS, 50h, 2 S)
• Project Management
• AGIL Methods & Transverse Project (2 ECTS, 21h, 2 S)
• Languages and workshops
• French and Foreign languages (6 ECTS, 61h, 1&2 S)
• Personal and Professional Project (1 ECTS, 15, 1 S)
*1 S= 1st semester, ** 2 S= 2nd semester

M2 Program: from September to September (60 ECTS, 641h)
M2 level is a collection of modules, giving in total 60 ECTS (42 ECTS for the modules taught from September to April, plus 9 ECTS for the internship and 9 ECTS for the Master thesis).

Computer technologies
• Web Services (3 ECTS, 24h, 1 S)
• NOSQL (2 ECTS, 20h, 1 S)
• Java EE (3 ECTS, 24, 1S)
Data exploration
• Semantic web and Ontology (2 ECTS, 20h, 1 S)
• Data mining: application (2 ECTS, 20h, 1S)
• Social Network Analysis (2ECTS, 18h, 1S)
• Collective intelligence: Web Mining and Multimedia indexation (2 ECTS, 20h, 2 S)
• Enterprise Miner SAS (2 ECTS, 20h, 2 S)
• Text Mining and natural language (2 ECTS, 20h, 2 S)
Operations Research
• Thorough operational research: modelling and business application (2 ECTS, 21h, 1 S)
• Game theory (1 ECTS, 10h, 1 S)
• Forecasting models (2 ECTS, 20h, 1 S)
• Constraint programming (2 ECTS, 20h, 2 S)
• Multi-objective and multi-criteria optimisation (2 ECTS, 20h, 2 S)
• SAS OR (2 ECTS, 20h, 2 S)
Research Initiation Initiative
• Scientific Paper review (1 ECTS, 10h, 1 S)
• Final research project on BIG DATA (2 ECTS, 39, 2 S)
BI Architecture
• BI Theory (2 ECTS, 20h, 2 S)
• BI Practice (2 ECTS, 20h, 2 S)
Languages and workshops (4 ECTS, 105h, 1&2 S)
• French as a Foreign language
• CV workshop
• Personal and Professional Project
Internship
• Internship (9 ECTS, 22 weeks minimum)
Thesis
• Master thesis (9 ECTS, 150h)

Teaching

Fourteen external teachers (lecturers from universities, teacher-researchers, professors etc.), supported by a piloting committee, will bring together the training given in Cergy.

All the classes will be taught in English, with the exception of:
• The class of FLE (French as a foreign language), where the objective is to teach the students how to understand and express themselves in French.
• Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.
The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:
• class documents, practical work and tutorials online
• questions and discussions between teachers and students, and among students
• a possibility of handing work in online

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

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The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more
The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

Degree information

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits. The programme consists of two core modules (30 credits), six optional modules (90 credits) and a research project (60 credits).

Core modules
-Supervised Learning
-Either Graphical Models
OR
-Probabilistic and Unsupervised Learning

Optional modules
-Machine Vision
-Bioinformatics
-Information Retrieval and Data Mining
-Advanced Topics in Machine Learning
-Inverse Problems in Imaging
-Affective Computing and Human-Robot Interaction
-Approximate Inference and Learning in Probabilistic Models
-Applied Machine Learning
-Computational Modelling for Biomedical Imaging
-Programming and Mathematical Methods for Machine Learning
-Statistical Natural Language Programming
-Numerical Optimisation

Dissertation/report
All MSc students undertake an independent research project which culminates in a dissertation ( maximum length of 120 pages) in the form of a project report.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have machine learning research degrees in domains as diverse as robotics, music, psychology, bioinformatics at the universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multi national companies such as BAE Systems and BAE Detica.

Top career destinations for this degree:
-Software Engineer, Bisual
-PhD Computer Programming, Newcastle University
-Software Developer, Total Gas & Power
-Risk Analyst, National Bank of Greece
-Research Engineer, Xerox Research Centre India

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. Machine Learning graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

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In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. Read more

Programme description

In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:

classical and Bayesian ideologies
linear and generalised linear models
computational statistics applied to a range of models and applications
regression
data analysis

Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.

Programme structure

To be awarded the MSc degree you need to obtain a total of 180 credits. All students take courses during semester 1 and 2 to the value of 120 credits of which compulsory course units comprise 60 credits. Successful performance in these courses (assessed via coursework or examinations or both) permits you to start work on your dissertation (60 credits) for the award of the MSc degree. The dissertation will generally take the form of two consultancy-style case projects or an externally supervised project.

Compulsory courses (60 credits):

Statistical Theory (10 credits, semester 1)
Statistical Regression Models (10 credits, semester 1)
Bayesian Theory (10 credits, semester 1)
Statistical Programming (10 credits, semester 1)
Bayesian Data Analysis (10 credits, semester 2)
Likelihood and Generalised Linear Models (10 credits, semester 2)

Optional courses (60 credits) include:

Data Analysis (20 credits, semester 1)
Introductory Applied Machine Learning (10 credits, semester 1)
Text Technologies for Data Science (10 credits, semester 1)
Fundamentals of Optimization (10 credits, semester 1)
The Analysis of Survival Data (10 credits, semester 2)
Stochastic Modelling (10 credits, semester 2)
Multilevel Modelling (20 credits, semester 2)
Large Scale Optimization for Data Science (10 credits, semester 2)
Modern Optimization Methods for Big Data Problems (10 credits, semester 2)
Time Series Analysis and Forecasting (5 credits, semester 2)
Combinatorial Optimization (5 credits, semester 2)
Probabilistic Modelling and Reasoning (10 credits, semester 2)

Learning outcomes

At the end of this programme you will have:

knowledge and understanding of statistical theory and its applications within data science
the ability to formulate suitable statistical models for new problems, fit these models to real data and correctly interpret the results
the ability to assess the validity of statistical models and their associated limitations
practical experience of implementing a range of computational techniques using statistical software R and BUGS/JAGS

Career opportunities

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science.

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Come to our Postgraduate Open Day on Friday 10 February to find out more!. By studying this Masters course you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry. Read more
Come to our Postgraduate Open Day on Friday 10 February to find out more!

By studying this Masters course you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry.

As a graduate of this course you will work at the top-end of the games industry and will develop computer graphics on high-performance platforms, or write engines for the next generation of games.

This course will build on your computer science knowledge to specialise in computer graphics, where games programmers must push computing resources to the limit, using deep understanding of architecture and high-performance programming to generate new levels of graphical realism and visual effects on cutting-edge hardware platforms

You can be sure that what you learn will be the technical skills required by industry as this course has been developed in collaboration with a prestigious steering group from industry comprising:

- Barog Game Labs
- Double Eleven
- Epic Games
- NVIDIA
- Team 17
- Sumo Digital
- Weaseltron

During this course you will develop a proficiency in low-level programming (C++, Graphic and Compute shaders), a thorough understanding of multi-core and many-core programming techniques, game engine and tool development techniques, and fundamental insight into graphics and the practical techniques used in games, including geometric models, animation and simulation, and advanced methods for visual realism.

Keywords: games development, gaming, games engineering, graphics, computing, computer science

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Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering. Read more

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Financial Engineering and Risk Management
-Introduction to Financial Market Analysis
-Learning and Computational Intelligence in Economics and Finance
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Big-Data for Computational Finance (optional)
-Industry Expert Lectures in Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Artificial Neural Networks (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-Machine Learning and Data Mining (optional)
-Trading Global Financial Markets (optional)
-Creating and Growing a New Business Venture (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Constraint Satisfaction for Decision Making (optional)

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