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Masters Degrees (Algorithms)

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Goal of the pro­gramme. Computer science has a brilliant future! You could help to create new network solutions, build the future digital society, develop secure digital services, or be involved in a ground-breaking international software project. Read more

Goal of the pro­gramme

Computer science has a brilliant future! You could help to create new network solutions, build the future digital society, develop secure digital services, or be involved in a ground-breaking international software project. Perhaps you will develop algorithms for utilising genome data in medicine or optimise bus routes using positioning data. Do you wonder about all the things that can be automated? Or would you like to dig deeper and become a researcher?

In the Master’s programme in computer science you can become an expert in a wide range of fields. You will have access to the focus areas of research in computer science at the University of Helsinki: algorithms, distributed or networked systems, and software engineering. You will gain lasting professional skills for specialist, design, or managerial posts in the corporate world, or for research and doctoral education, since the Master’s programme in computer science gives you the aptitude for both independent working and multidisciplinary teamwork.

This education will give you:

  • The ability to advance your knowledge in the different areas of computer science
  • The skill to seek, assess, and analyse scientific information in your own area of expertise, and apply the methods of the field in an ethical and sustainable way
  • The ability to act as expert in the field, and to develop the practices and methods of your field in cooperation with specialists from other fields
  • Oral and written communication skills in an international work environment

The quality teaching within the computer science programme at the University of Helsinki has been highlighted repeatedly in national and international teaching assessments. The student-centred, in-depth learning gives you a solid basis for life-long learning. Studying at the leading research unit for computer science in Finland offers you constant interaction with current research and insight into the development patterns in the field.

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

In future, we will increasingly be using intelligent tools, consisting of networked hardware, software, services, and data. They will work based on intelligent, learning algorithms, data streams carried by communication protocols, and global infrastructures.

Within the Algorithms sub-programme, you will study effective algorithms and their application within other disciplines and in corporate life. Future IT systems will contain more and more intelligent components, the function of which will be based on complex mathematical models created automatically with the aid of machine-learning methods. The problems to be solved are computationally challenging, and the ever increasing amounts of data will create their own challenges when it comes to the efficiency of the algorithms needed.

The Networking and services sub-programme educates you to become an expert and strategic leader in the design and management of new global infrastructures. The infrastructures include Internet technologies in fixed networks and mobile environments, as well as the information and service networks built on top of them. Focus areas include the theory, data security, and trust within distributed systems, interactive systems, and the adaptability of services in a changing environment.

The Software systems sub-programme introduces you to the design and implementation of advanced software. The development of a shared software framework or platform for several software products is very demanding both technically and from the development project viewpoint. Developing such software requires technical skills, but also team- and project work, quality assurance, and communication. Within this sub-programme, you can specialise in software engineering, software technology, or information management, and study the current research questions in these areas in depth.



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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. Read more
This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

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

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This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications. Read more
This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications.

You will explore the mathematical techniques that are commonly used to solve problems in the real world, in particular in communication theory and in physics. As part of the course you will carry out an independent research investigation under the supervision of a member of staff. Popular dissertation topics chosen by students include projects in the areas of communication theory, mathematical physics, and financial mathematics.

The transferable skills gained on this course will open you up to a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsforapplications.aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and knowledge and understanding of the subjects of cryptography and communications, preparing you for research or professional employment in this area.

- The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography. The academics who teach on this course include several leading researchers in these areas.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses and complete a main project under the supervision of a member of staff.

Core courses:
Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed, as well as methods for obtaining confidentiality and authentication.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- knowledge and understanding of: the principles of communication through noisy channels using coding theory; the principles of cryptography as a tool for securing data; and the role and limitations of mathematics in the solution of problems arising in the real world

- a high level of ability in subject-specific skills, such as algebra and number theory

- developed the capacity to synthesise information from a number of sources with critical awareness

- critically analysed the strengths and weaknesses of solutions to problems in applications of mathematics

- the ability to clearly formulate problems and express technical content and conclusions in written form

- personal skills of time management, self-motivation, flexibility and adaptability.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security Manager at London Underground.

How to apply

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

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Our Advanced Computing MSc programme will provide you with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. Read more

Our Advanced Computing MSc programme will provide you with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. Built around modules such as Algorithm Design and Analysis, Data Structures and their Implementation in C++, and Parallel and Distributed Algorithms, and offering a broad range of optional modules, the course will enhance your abilities to solve advanced computational problems and implement algorithms.

Key benefits

  • Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
  • You will learn advanced practical techniques and implementation skills for solving complex computational problems.
  • You will develop critical awareness and appreciation of the changing role of computing in society and motivating you to pursue further professional development and research.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in advanced computing and related fields.
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

Rooted in the renowned research strengths of the Department of Informatics, this programme introduces core topics such as systems programming and algorithms before allowing you to specialise through your choice of modules. The course comprises of optional and required modules, and you will complete the course in one year, studying September to September. You must take modules totalling 180 credits to meet the requirements of the qualification, 60 of which will come from an individual project of around 15,000 words.

Course purpose

For graduates in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will enhance your ability to solve advanced computational problems and impart skills necessary for algorithm implementation. Research for your individual project will provide valuable preparation for a career in research or industry.

Course format and assessment

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project and dissertation will be assessed on one 15,000-word extended piece of writing. 

Career prospects

Our graduates have continued into very successful careers in general software consultancy companies, in specialised software development companies and IT departments of large institutions (financial, telecommunications and public sector). Their jobs involve specialist programming and problem-solving as well more conventional software development, maintenance and project management roles. Some of our graduates have chosen to persue academic and industrial research in software engineering, bio-informatics, algorithms and computer networks.



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The field of algorithms is today an extremely important enabling technology. Web search-engines, routing in the internet, genome analysis, cryptography and image analysis are just a few examples of applications that depend critically on suitable choices of algorithms and. Read more
The field of algorithms is today an extremely important enabling technology. Web search-engines, routing in the internet, genome analysis, cryptography and image analysis are just a few examples of applications that depend critically on suitable choices of algorithms and
data structures. The focus of this MSc is on the design, analysis and engineering of algorithms, covering their use for modelling real-world problems.

Start Dates
October and January each year.

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Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment. Read more

Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment.

Taught jointly by the School of Computing and the School of Electronic and Electrical Engineering, this course will give you a grasp of all layers needed for mobile communication and computation, from the physical network layer through to the applications that run on mobile devices.

You’ll gain a full understanding of the web and cloud computing infrastructure, as core modules give you a foundation in key topics like systems programming and data communications. A range of optional modules will then allow you to focus on topics that suit your interests and career plans, from cloud computing to embedded systems design and high speed web architecture.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

You’ll take two core modules in Semester 1 that introduce you to fundamental topics like systems programming and network security. With this foundation, you’ll be able to gain high-level specialist knowledge through your choice of optional modules taught by the School of Computing and the School of Electronic and Electrical Engineering.

The optional modules you choose will enable you to direct your studies towards topics that suit your personal interests and career ambitions such as mobile app development, digital media engineering, big data, cloud computing and embedded systems design, among others.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Data Communications and Network Security 15 credits

Optional modules

  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Functional Programming 10 credits
  • Big Data Systems 15 credits
  • Mobile Applications Development 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Cloud Computing 15 credits
  • Graph Theory: Structure and Algorithms 15 credits
  • Communication Network Design 15 credits
  • Optical Communications Networks 15 credits
  • High Speed Internet Architecture 15 credits
  • Digital Media Engineering 15 credits

For more information on typical modules, read Mobile Computing and Communication Networks MSc in the course catalogue

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.Most projects are experimentally based and linked with companies within the oil and gas industry to ensure the topic of research is relevant to the field whilst also addressing a real-world problem.

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Career opportunities are extremely broad, covering jobs in the design of embedded software running on multi-core devices through to jobs involving the design and implementation of new mobile-applications centric systems for business. In the application of mobile computing skills, job opportunities span every area, from the automotive sector through to retail and banking.

You could launch a career in fields such as mobile app development, mobile systems architecture, project management, network consultancy. You could also work as an engineer in embedded mobile communications, network security or research and development among many others – and you’ll even be well-prepared for PhD study.

Careers support

You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UK’s leading employers.

The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



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Computer Science is one of the drivers of technological progress in all economic and social spheres. Those graduating with an M.Sc. Read more

About Computer Science

Computer Science is one of the drivers of technological progress in all economic and social spheres. Those graduating with an M.Sc. in Computer Science are specialists in at least one field of computer science who have wide-ranging science-based methodological expertise.
Graduates are able to define, autonomously and comprehensively, computer science problems and their applications, structure them and build abstract models. Moreover, they are able to define and implement solutions that are at the state of the art of technology and science.

Features

– A broad, international and relevant selection of courses
– As a student, you will work on cutting-edge research projects
– Individual guidance in small learning groups
– Excellent enterprise relations maintained by the chairs and institutes
– Numerous partnerships with universities throughout the world, including a double degree programme with the Institut national des sciences appliquées de Lyon (INSA)

Syllabus

The programme offers the following five focus modules:
1) Algorithms and Mathematical Modelling
2) Programming and Software Systems
3) Information and Communication Systems
4) Intelligent Technical Systems
5) IT Security and Reliability
1) Algorithms and Mathematical Modelling: This module teaches you about determinstic and stochastic algorithms, their implementation, evaluation and optimisation. You will acquire advanced knowledge of computer-based mathematical methods – particularly in the areas of algorithmic algebra and computational stochastics – as well as developing an in-depth expertise in mathematical modelling and complexity analysis of discrete and continuous problems.
2) Programming and Software Systems: This module imparts modern methods for constructing large-scale software systems, as well as creating and using software authoring, analysis and optimisation tools. In this module you will consolidate your knowledge of the various programming paradigms and languages, the structure of language processing systems, and learn to deal with parallelism in program procedures.
3) Information and Communication Systems: In this module you will study the interactions of the classic computer science areas of information systems and computer networks. This focus area represents an answer to the problem of increasing volume and complexity of worldwide information distribution and networks, and for the growing requirements on quality and performance of computer communication. Additionally, you will learn to transfer database results to multimedia data.
4) Intelligent Technical Systems: In this module you are acquainted with digital image and signal processing, embedded systems and applications of intelligent technical systems in industrial and assistance systems, which are necessary for production automation and process control, traffic control, medical and building technology. You will learn to develop complex applications using computer systems and deal with topics such as image reconstruction, camera calibration, sensor data fusion and optical measurement technology.
5) IT Security and Reliability: This module group is concerned with security and reliability of IT systems, e.g. in hardware circuitry and communication protocols, as well as complex, networked application systems. To ensure the secure operation of these systems you will learn design methodology, secure architectures and technical implementation of the underlying components.

Language requirements

Unless English is your native language or the language of your secondary or undergraduate education, you should provide an English language certificate at level B2 CEFR, e.g. TOEFL with a minimum score of 567 PBT, 87 iBT or ITP 543 (silver); IELTS starting from 5.5; or an equivalent language certificate.

To facilitate daily life in Germany, it would be beneficial for you to have German language skills at level A1 CEFR (beginner’s level). If you do not have any German skills when starting out on the programme, you will complete a compulsory beginner’s German course during your first year of study.

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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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This MSc programme focuses on the development of sophisticated computer graphics applications and on the development of tools commonly used in the creation of content for these applications. Read more
This MSc programme focuses on the development of sophisticated computer graphics applications and on the development of tools commonly used in the creation of content for these applications. It provides students with opportunity to develop important skills necessary for employment in this sector. They will use their expertise to, for example, develop interactive graphical scenes and deploy up to date techniques to implement real-time and offline visual effects.

Course Overview

This programme will equip students with skills at a high academic level and also crucially enable them to practically implement their knowledge because of the ‘hands-on’ emphasis of the programme.

The main themes of the programme are:
-Current and emerging algorithms and techniques used in film visual effects and games programming
-Approaches used to generate off-line visual effects
-Approaches used to generate real-time interactive games

The first theme develops in the student the necessary skills required to implement algorithms and techniques used to generate realistic scenes. These concepts will be explored in detail.

The second theme addresses the need for students to identify, evaluate and implement suitable methods to solve specific problems related to creating off-line visual effects.

The third theme recognises the need to solve these problems using approaches optimised for real-time computer games development and develops in the student the requisite skills.

Modules

-Animation Systems Development (20 credits)
-Artificial Intelligence for Games & VFX (20 credits)
-GPU Shader Development (20 credits)
-Leadership and Management (20 credits)
-Research Methods and Data Analysis (20 credits)
-Visual Simulation (20 credits)
-Major Project (60 credits)

Key Features

Applicants for this programme will have an interest in computer graphics and Computer Generated Imagery (CGI). The main themes of the programme are current and emerging algorithms and techniques used in film visual effects and games programming, approaches used to generate off-line visual effects and approaches used to generate real-time interactive games. This also includes the development/enhancement of tools used in the CGI and animation industry. Graduates will be concerned with the discipline of developing software and applications using high level programming languages. They will also be experienced in creating custom animated scenes using the powerful scripting languages of industry standard applications such as Maya and Houdini software. Graduates will have an advanced understanding of computer graphics, GPU shader development, and visual simulation methods making use of modern artificial intelligence and simulation techniques. Graduated are likely to find employment either within the film VFX industry, computer games or traditional software engineering sectors.

Assessment

An Honours Degree (2.2 or above) or advanced qualification in Computer Science or cognate discipline from a UK University or recognised overseas institution, or industrial experience in Computer Networking and an Honours Degree.

Where English is not your first language, we ask that you hold an Academic IELTS test with a score of at least 6.0 (no element less than 5.5) or TOEFL with a minimum score of 550 (213 for computer based test).

Career Opportunities

It is expected that graduates would seek positions such as:
-Software Engineers
-Senior Software Engineers
-App Developers
-CGI Special Effects Programmers
-Games Programmers
-Lead Programmers
-Render Manager
-VFX Programmer
-VFX Technical Directors

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From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. Read more

From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science.

Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development.

You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.




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Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Read more
Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Your research will be supported by an experienced computer scientist within a research group and with the support of a team of advisers.

Research supervision is available under our six research areas, reflecting our strengths, capabilities and critical mass.

Advanced Model-Based Engineering and Reasoning (AMBER)

The AMBER group aims to equip systems and software engineering practitioners with effective methods and tools for developing the most demanding computer systems. We do this by means of models with well-founded semantics. Such model-based engineering can help to detect optimal, or defective, designs long before commitment is made to implementations on real hardware.

Digital Interaction Group (DIG)

The Digital Interaction Group (DIG) is the leading academic research centre for human-computer interaction (HCI) and ubiquitous computing (Ubicomp) research outside of the USA. The group conducts research across a wide range of fundamental topics in HCI and Ubicomp, including:
-Interaction design methods, eg experience-centred and participatory design methods
-Interaction techniques and technologies
-Mobile and social computing
-Wearable computing
-Media computing
-Context-aware interaction
-Computational behaviour analysis

Applied research is conducted in partnership with the DIG’s many collaborators in domains including technology-enhanced learning, digital health, creative industries and sustainability. The group also hosts Newcastle University's cross-disciplinary EPSRC Centre for Doctoral Training in Digital Civics, which focusses on the use of digital technologies for innovation and delivery of community driven services. Each year the Centre awards 11 fully-funded four-year doctoral training studentships to Home/EU students.

Interdisciplinary Computing and Complex BioSystems (ICOS)

ICOS carries out research at the interface of computing science and complex biological systems. We seek to create the next generation of algorithms that provide innovative solutions to problems arising in natural or synthetic systems. We do this by leveraging our interdisciplinary expertise in machine intelligence, complex systems and computational biology and pursue collaborative activities with relevant stakeholders.

Scalable Computing

The Scalable Systems Group creates the enabling technology we need to deliver tomorrow's large-scale services. This includes work on:
-Scalable cloud computing
-Big data analytics
-Distributed algorithms
-Stochastic modelling
-Performance analysis
-Data provenance
-Concurrency
-Real-time simulation
-Video game technologies
-Green computing

Secure and Resilient Systems

The Secure and Resilient Systems group investigates fundamental concepts, development techniques, models, architectures and mechanisms that directly contribute to creating dependable and secure information systems, networks and infrastructures. We aim to target real-world challenges to the dependability and security of the next generation information systems, cyber-physical systems and critical infrastructures.

Teaching Innovation Group

The Teaching Innovation Group focusses on encouraging, fostering and pursuing innovation in teaching computing science. Through this group, your research will focus on pedagogy and you will apply your research to maximising the impact of innovative teaching practices, programmes and curricula in the School. Examples of innovation work within the group include:
-Teacher training and the national Computing at School initiative
-Outreach activities including visits to schools and hosting visits by schools
-Participation in national fora for teaching innovation
-Market research for new degree programmes
-Review of existing degree programmes
-Developing employability skills
-Maintaining links with industry
-Establishing teaching requirements for the move to Science Central

Research Excellence

Our research excellence in the School of Computing Science has been widely recognised through awards of large research grants. Recent examples include:
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Cloud Computing for Big Data Doctoral Training Centre
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Digital Civics
-Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC) Research Grant: a £10m project to look at novel treatment for epilepsy, confirming our track record in Systems Neuroscience and Neuroinformatics.

Accreditation

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

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Geographical Information Systems (GIS) has grown rapidly to become a major component of information technology, creating distinctive methods of data analysis, algorithms and software tools. Read more

Why take this course?

Geographical Information Systems (GIS) has grown rapidly to become a major component of information technology, creating distinctive methods of data analysis, algorithms and software tools.

This course emphasises the acquisition of practical GIS skills. We use a wide range of industry-standard software tools and a structured approach to the analysis of spatial data through project work.

What will I experience?

On this course you can:

Get hands-on experience of using instruments such as GPS, Total Stations and 3D laser scanners
Be taught by experts, who have extensive industrial and consultancy experience and strong research portfolios
Practise your GIS data collection skills in a range of environments

What opportunities might it lead to?

The wide range of career opportunities across public and private sectors and in university-based research, coupled with the rapid rate of technological change, mean that major organisations and industrial firms are finding it essential to update their skills through advanced study. We therefore aim to meet this demand by tailoring our course to the needs of both regional and national markets.

Here are some routes our graduates have pursued:

Environmental consultancies
Geographical information science specialists
Working for the Environmental Agency
Working for the Ordnance Survey

Module Details

The academic year is divided into two parts. The first part comprises the lecture, workshop, practical and field work elements of the course, followed by a dissertation which will take approximately five months to complete.

Here are the units you will study:

Principles of Geographic Information Science: Beginning with an overview of the development of GIS, the first part of this unit examines data sources and data capture, as well as hardware and software tools. The second part deals with vector-based data structures and data management, followed by vector GIS operations, such as overlay and buffering. You will undertake a project to create a GIS of your own, which may be presented as a seminar session. Practical exercises are undertaken using MapInfo. You will then go on to develop an understanding of raster-based approaches to GIS, cartographic modelling and related areas of image processing which are often applied in remote sensing. Topics include raster data models and data compression techniques, raster GIS and cartographic modelling, imaging systems and image processing, geometric correction techniques and GIS/remote sensing integration in the raster domain. Practical work uses MapInfo, ArcGIS - ArcMap and ERDAS Imagine.

GIS and Database Management Systems: Your major focus on this unit will be the use of industry-standard methods and tools to develop competence in the successive stages of database design, development and implementation. You will have an introduction to data analysis techniques, followed by an examination of alternative types of database system and the rules of relational database design. There is extensive treatment of the SQL query language in standard databases and for attribute query within a GIS. You will be introduced to advanced topics including database programming and computer-aided database design. You will also consider the Object-Relational databases and spatial data types, explore the use of spatial queries using the ORACLE relational database management system and examine procedural database programming and web database connectivity. Practical work for this unit uses the ORACLE relational database management system, running in full client-server mode.

Applied Geographic Information Systems: On this unit you will develop a general, inferential, model-based approach to the analysis of quantitative data within a geographical framework. You will examine a range of underlying concepts including model specification, bias, linearity, robustness and spatial autocorrelation. You will subsequently develop these in the context of a unified framework for analysis. Practical work is based on ArcGIS - ArcMap.

Research Methods and Design: This unit will introduce you to the basic principles of research design and methodology, enabling you to develop a critical approach to the selection and evaluation of appropriate methods for different types of research problem.

Modelling and Analysis and the Web: This unit gives you the chance to consider the use of GIS technology for creating terrain models and explore the basics of photogrammetry, as well as analytical and digital techniques for photogrammetric data capture. You will also look at Orthophotography, LiDAR and RADAR systems. ArcGIS is used for spatial analysis, such as buffering and overlay techniques. You will also explore and exemplify data transfer between GIS software systems and technologies for internet-based GIS.

Dissertation: This provides an opportunity for you to pursue a particular topic to a greater depth than is possible within the taught syllabus. It can take a variety of forms, for example GIS-based analysis of original data sources and digital datasets, case studies of GIS adoption in public or private sector organisations, the development of new software tools/applications or the design of GIS algorithms. The final submission takes the form of an extended written report or dissertation of a maximum of 15,000 words.

Programme Assessment

The course provides a balanced structure of lectures, seminars, tutorials and workshops. You will learn through hands-on practical sessions designed to give you the skills in laboratory, computer and field techniques. The course also includes extensive field work designed to provide field mapping and data collection skills.

The majority of assessment takes the form of practical exercises and project-based activity. This enables you to become familiar with industry-standard software systems and develop your skills by applying your newfound expertise in areas that particularly interest you.

Student Destinations

GIS technology is now very widely deployed in many organisations ranging from utility companies, telecommunications networks, civil engineering, retailing, local and national government, international charities and NGOs, the National Health Service, environmental organisations, banking and finance, and insurance. GIS has become an essential part of the world's information infrastructure.

You can expect to go on to find work in organisations such as local authorities, health authorities, conservation organisations, banks and insurance companies, amongst others. Many of our previous graduates are now employed all over the world, working on a whole variety of GIS-related projects in a very wide range of different organisations and industries.

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This course takes an immersive approach to learning both the principles and practices of computer systems with much of the material based around examples and practical exercises. Read more
This course takes an immersive approach to learning both the principles and practices of computer systems with much of the material based around examples and practical exercises. Students completing this course will have a firm grasp of the current practices and directions in computer systems and will be able to design and build for example, distributed systems for the Web using Internet, Intranet and other technologies.

Programme Objectives
To provide the foundations for understanding of core ideas, methods and technologies in computer science.
To provide the technical skills and background material so that the postgraduate will be able to conduct a near state-of-the-art research or development project;
To provide the graduate with a range of specialist and transferable skills;
To provide the educational base for further professional development and lifelong learning.
Course Topics
Data networks and communications, project foundations and management tools, broadband communication systems, technologies for Internet systems, agent technologies and Artificial Intelligence, introduction to distributed systems and mobile systems, project and dissertation.

Taught Modules:

Java programming: This module provides students with an in-depth understanding of current and emerging Java programming concepts and programming variations. The module teaches the basic and advanced structures of Java and makes use of the object-oriented approach to software implementation. It also gives an in-depth understanding of advanced Java concepts in the area of user interfaces and will enable students to apply the theoretical knowledge of the Java language onto a test-case software development scenario.

Introduction to distributed systems: This module will introduce key ideas in distributed Systems and its role and application in operating systems and middleware. On completion of this module students will have an understanding of the key issues for distributed systems at OS level or as middleware, they will understand core concepts of concurrency, be able to program multithreaded and distributed applications and understand the issues and use of algorithms for transactional systems.

Data networks and communications: This module will provide an in-depth understanding of how real communication networks are structured and the protocols that make them work. It will give the students an ability to understand in detail the process required to provide an end-to-end connection.

Technologies for Internet Systems: In this module, students will be introduced to state of the art technologies and tools for Internet Systems and in particular e-commerce systems.

Agent Technologies: This module provides an in-depth understanding of technologies from Artificial Intelligence research such as machine learning, data mining, information retrieval, natural language processing, and evolutionary programming. It will look at the application of agent-oriented technologies for Artificial Life, for building Web search engines, for use in computer games and in film (such as the MASSIVE software developed for the Lord of the Rings movies), and for robotics. It will also provide an introduction to agent-oriented programming using the NetLogo programming language.

Foundations of computer graphics: This module will teach techniques, algorithms and representations for modelling computer graphics and enable students to code 2D and 3D objects and animations.

Database systems: Students completing this module will gain an in depth understanding of DBMS/Distributed DBMS architecture, functionality, recovery and data storage techniques. Students will also have a full understanding of how queries are processed and the importance of database maintenance. This module is designed to enable students to perform research into one or two areas of databases; for example, object oriented databases and deductive databases.

Project foundations and management tools: This module prepares students for their MSc research project, including reference search and survey preparation and familiarisation with project management tools.

MSc Research project: After the successful completion of the taught component of the MSc programme, students will spend the remainder of the time undertaking a research project and producing an MSc Dissertation. During this process, students will conduct project work at state-of-the-art research level and to present this work as a written dissertation. Completing a project and dissertation at this level will train students in: problem solving; researching new topics; organizing knowledge; exercising elementary time and project management skills; reporting and writing skills.

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The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. Read more
The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. It prepares students for technical and analytical GIS roles and is in high demand; we have very close links with industry and the majority of our students find employment prior to contemplating their degree.

Degree information

Students gain a solid grounding in the scientific principles underpinning the computational and analytical foundations of GISc. Our staff are world-leading experts in the areas of programming location-enabled Apps, spatial and 3D databases, big spatio-temporal analytics, citizen science and and human computer interaction, and the MSc therefore is able to offer a wide range of options and specialisations.

Students undertake modules to the value of 180 credits. The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). A Postgraduate Diploma, four core modules (60 credits), four optional modules (60 credits), full-time nine months is offered.

Core modules - core modules introduce the theory underpinning GIS, along with programming skills (python) and the basics of spatial analysis and statistcs. You'll learn to critically engage with GIS rather than just pushing buttons - how does the way data is captured and modelled influence the results of your analysis? Do you get the same results from two different GIS packages? Knowing what is inside the 'black box' means you understand analytical results and their limitations.
-GIS Principles and Technology
-Principles of Spatial Analysis
-Mapping Science
-Representations, Structures and Algorithms

Optional modules - term two is where you start to specialise, chosing modules that fit your interests, intended career choice and/or prepare you for your dissertation. At this point you can chose a heavilty technical route (e.g. databases, programming, human computer interaction) a more analytical route (spatio-temporal data mining, network and locational analysis, databases) or a mixture of the two routes. You will need to chose four modules in total. At least 30 credits of optional modules selected from :
-Geographical Information System Design
-Spatio-Temporal Analysis and Data Mining
-Web and Mobile GIS – Apps and Programming
-Spatial Databases and Data Management

Plus no more than 30 credits of optional modules (all term two) selected from :
-Airborne Data Acquisition
-Applied Building Information Modelling
-Network and Locational Analysis
-Image Understanding
-Ocean and Coastal Zone Management
-Positioning
-Research Methods
-Terrestrial Data Acquisition

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 10,000–15,000 words. Where appropriate, this may be undertaken in conjunction with one of our many industrial partners, including Arup, Joint Research Centre, British Red Cross, Transport for London.

Teaching and learning
The programme is delivered through lectures, practical classes, demonstrations and tutorials, and is supported by a series of external speakers from industry and visits to industrial who give weekly seminars describing how GIS is used in their field as well as what they are looking for when recruiting graduate GIS students. Assessment is through unseen examinations, group and individual coursework, formal and oral presentations, and the dissertation.

Careers

There are excellent employment prospects for our graduates, with starting salaries of around £25,000. Recent GIS graduates have found openings with large engineering design firms (such as Arup or WSP), specialist consultancy firms such as Deloitte or Informed Solutions, in leading professional software companies (such as ESRI or Google), with local authorities, for organisations such as Shell, Tesco, the Environment Agency, Transport for London, NHS and the Ordnance Survey.

Employability
Students will develop specific skills including a fundamental understanding of GIS and its application to real-world problems, through theoretical lectures covering the foundations of the science – how data is captured, map creation, generalisation, spatial data management, spatial analysis, data quality and error, and spatial algorithms. Students will develop strong technical (python, R, Java, HTML, Javascript, SQL) and analytical skills (data mining, human computer interaction and usability), and in order to fully understand the principles behind GIS will make use of multiple GIS packages, both proprietary and free/open source (ArcGIS, QGIS).

Why study this degree at UCL?

This highly regarded MSc has been running for nearly 30 years and is taught by internationally recognised academics. Our specialist GIS laboratory offers the latest open source and proprietary software and our unique dual focus on the computer science and analytical aspects of GIS means that you will be able to develop your skills in multiple directions.

Our close links with industry (a strong alumni group and weekly industrial seminars) mean that you will be able to directly link your classroom learning with your future career as a GIS professional; you can also undertake your dissertation with an industrial partner.

As well as weekly industrial seminars, you will have the option to do an industry-linked project, and you will be able to attend our annual GIS careers event, which is co-organized with the UK Assocation of Geographic Infrormation.

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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.

About this degree

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 one core module (15 credits), five to seven optional modules (75 to 105 credits), up to two modules (30 credits) from electives, and a research project (60 credits).

Core modules

  • Supervised Learning (15 credits)

Optional modules

Students must choose 15 credits from Option Group One and a minimum of 60 credits from Option Group Two. Students must choose a further 30 credits from either Option Group Two or approved electives.

Option Group One (choose 15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Option Group Two (choose 60 to 90 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Bioinformatics (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Programming and Mathematical Methods for Machine Learning (15 credits)
  • Statistical Natural Language Programming (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

Students may select up to 30 credits from elective modules

A list of acceptable elective modules is available on the departmental website.

Dissertation/report

All MSc students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words 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.

Further information on modules and degree structure is available on the department website: Machine Learning MSc

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

Recent career destinations for this degree

  • Computer Vision Engineer, ZVR
  • Data Analyst / Data Scientist, Deloitte Data Analytics Group
  • Programmatic Yield Manager and Data Analyst, eBay
  • Data Scientist, dunnhumby
  • PhD in Computer Science, UCL

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 Germany, Iceland, France and the US, amongst other places, in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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