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Masters Degrees (Computational Science)

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The MSc in Data and Computational Science is designed for students from highly quantitative disciplines who wish to work in data analytics or computational science. Read more
The MSc in Data and Computational Science is designed for students from highly quantitative disciplines who wish to work in data analytics or computational science.

Computational science is at the crossroads between modern applied mathematics and statistics, and our programme recognizes this fact by combining aspects of both in a unique set of tailored modules including scientific computing, mathematical modelling, and data analytics.

- The programme will equip you to solve complex scientific problems and analyse large data sets using a range of theoretical tools, from deterministic mathematical modelling to Bayesian analysis.

- The intensive programming modules will allow you develop a range of sought-after skills in practical programming and data analytics, including applications in high-performance computing.

- Topical application areas are offered each year, including cryptography, numerical weather prediction, and financial mathematics. The dissertation will give you further hands-on experience in computational science and will allow you to apply the key theoretical and practical skills by working on a challenging research topic.

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Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Read more
Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.

In the Data Science master’s programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master’s programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.

Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to:
-Understand the general computational and probabilistic principles underlying modern machine learning and data mining algorithms.
-Apply various computational and statistical methods to analyse scientific and business data.
-Assess the suitability of each method for the purpose of data collection and use.
-Implement state-of-the-art machine learning solutions efficiently using high-performance computing platforms.
-Undertake creative work, making systematic use of investigation or experimentation, to discover new knowledge.
-Report results in a clear and understandable manner.
-Analyse scientific and industrial data to devise new applications and support decision making.

The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through minor studies in the MSc programme, or it might already be part of your bachelor-level degree.

Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.

Minor studies give you a wider perspective of Data Science. Your minor subject can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).

Selection of the Major

You can specialise either in the core areas of data science -- algorithms, infrastructure and statistics -- or in its applications. This means that you can focus on the development of new models and methods in data science, supported by the data science research carried out at the University of Helsinki; or you can become a data science specialist in an application field by incorporating studies in another subject. In addition to mainstream data science topics, the programme offers two largely unique opportunities for specialisation: the data science computing environment and infrastructure, and data science in natural sciences, especially physics.

Programme Structure

You should be able to complete the MSc Programme in Data Science of 120 credits (ECTS) in two years of full-time study. The programme consists of:
-Common core studies of basic data science courses.
-Several modules on specific topics within data science algorithms, data science infrastructures and statistical data science, and on data science tools.
-Seminars and colloquia.
-Courses on academic skills and tools.
-Possibly an internship in a research group or company.
-Studies in an application domain.
-Master’s thesis (30 credits).

Career Prospects

Industry and science are flooded with data and are struggling to make sense of it. There is urgent demand for individuals trained to analyse data, including massive and heterogeneous data. For this reason, the opportunities are expected to grow dramatically. The interdisciplinary Data Science MSc programme will train you to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.

If you are focusing on the core areas of data science, you will typically find employment as a researcher or consultant, sometimes after taking a PhD in Computer Science or Statistics to deepen your knowledge of the field and research methods. If your focus is on the use of data science for specific applications, you will typically find work in industry or in other fields of science such as physics, digital humanities, biology or medicine.

Internationalization

The Data Science MSc is an international programme, with students from around the world and an international research environment. All of the departments taking part in the programme are internationally recognised for their research and a significant fraction of the teaching and research staff come from abroad.

The departments participate in international student exchange programmes and offer you the chance to include international experience as part of your degree. Data Science itself is an international field, so once you graduate you can apply for jobs in any country.

In the programme, all courses are in English. Although the Helsinki area is quite cosmopolitan and English is widely spoken, you can also take courses to learn Finnish at the University of Helsinki Language Centre. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning other languages.

Research Focus

The MSc programme in Data Science is offered jointly by three departments and two research institutes. Their research covers a wide spectrum of the many aspects of data science. At a very general level, the focal areas are:
-Machine learning and data mining
-Distributed computation and computational infrastructures
-Statistical modelling and analysis
-Studies in the programme are tightly connected to research carried out in the participating departments and institutes.

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Our highly sought-after graduates benefit from a programme that integrates training in identifying, framing and effectively researching social problems with a leading computational approach to social science. Read more
Our highly sought-after graduates benefit from a programme that integrates training in identifying, framing and effectively researching social problems with a leading computational approach to social science.

Furthermore, we are home to the Centre for Research in Social Simulation (CRESS) and its world-leading expertise in agent-based modelling.

PROGRAMME OVERVIEW

Interest in simulation has grown rapidly in the social sciences. New methods have been developed to tackle this complexity. This programme will integrate traditional and new methods, to model complexity, evolution and the adaptation of social systems.

These new methods are having an increasing influence on policy research through a growing recognition that many social problems are insufficiently served by traditional policy modelling approaches.

The Masters in Social Science and Complexity will equip you to develop expertise in the methods necessary to tackle complex, policy-relevant, real-world social problems through a combination of traditional and computational social science methods, and with a particular focus on policy relevance.

PROGRAMME STRUCTURE

This programme is studied full-time over one academic year and part-time over two academic years. It consists of eight taught modules and a dissertation. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Data Analysis
-Field Methods
-Computational Modelling
-Theory Model Data
-Modelling the Complex World
-Policy Modelling
-Theory and Method
-Statistical Modelling
-Evaluation Research
-Dissertation

EDUCATIONAL AIMS OF THE PROGRAMME

The main aims of the programme are to:
-Provide an appropriate training for students preparing MPhil/PhD theses, or for 
 students going on to employment involving the use of social science and policy research
-Provide training that fully integrates social science, policy modelling and computational methodologies to a high standard
-Provide training resulting in students with high quality analytic, methodological, computational and communication skills

PROGRAMME LEARNING OUTCOMES
The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:
-Develop skills in tackling real world policy problems with creativity and sound methodological judgment
-Cover the principles of research design and strategy, including formulating research 
questions or hypotheses and translating these into practicable research designs and models
-Introduce students to the methodological and epistemological issues surrounding research in the social sciences in general and computational modelling in particular
-Develop skills in programming in NetLogo for the implementation of agent-based models for the modelling of social phenomena
-Develop skills in the acquisition and analysis of social science data
-Make students aware of the range of secondary data available and equip them to evaluate its utility for their research
-Develop skills in searching for and retrieving information, using library and Internet resources
-Develop skills in the use of SPSS, and in the main statistical techniques of data analysis, including multivariate analysis
-Develop skills in the use of CAQDAS software for the analysis of qualitative data
-Develop skills in writing, in the preparation of a research proposal, in the presentation ofresearch results and in verbal communication
-Help students to prepare their research results for wider dissemination, in the form of seminar papers, conference presentations, reports and publications, in a form suitable for a range of audiences, including academics, stakeholders, policy makers, professionals, service users and the general public

Knowledge and understanding
-Show advanced knowledge of qualitative, quantitative and computational methodologies in the social science
-Show advanced knowledge of modelling methodologies, model construction and analysis
-Show critical understanding of methodological and epistemological challenges of social science and computer modelling
-Show critical awareness and understanding of the methodological implications of a range of sociological theories and approaches
-Show understanding the use and value of a wide range of different research approaches across the quantitative and qualitative spectra
-Show advanced knowledge in data collection, analysis and data driven modelling
-Show advanced knowledge of policy relevant social science research and modelling
-Show advanced understanding of the policy process and the role of social science and modelling therein
-Show advanced knowledge of statistical modelling

Intellectual / cognitive skills
-Systematically formulate researchable problems; analyse and conceptualise issues; critically appreciate alternative approaches to research; report to a range of audiences
-Conceptual development of Social Science and Complexity models to creatively enhance the understanding of social phenomena
-Integration of qualitative, quantitative and computational data
-Judgement of problem-methodology match
-Analyse qualitative and quantitative data drawn both from ‘real world’ and ‘virtual world’ environments, using basic and more advanced techniques, and draw warranted conclusions
-Develop original insights, questions, analyses and interpretations in respect of research questions
-Critically evaluate the range of approaches to research

Professional practical skills
-Formulate, design, plan, carry out and report on a complete research project
-Use the range of traditional and computational techniques employed in sociological research
-Ability to produce well founded, data driven and validated computational models
-Generate both quantitative and qualitative data through an array of techniques, and select techniques of data generation on appropriate methodological bases
-Employ a quantitative (SPSS) and qualitative software package to manage and analyse data
-Plan, manage and execute research as part of a team and as a sole researcher
-Ability to communicate research findings models in social science and policy relevant ways
-Ability to manage independent research

Key / transferable skills
-Communicate complex ideas, principles and theories by oral, written and visual means
-Apply computational modelling methodology to complex social issues in appropriate ways
-Creativity in approaching complex problems and a the ability of communicating and justifying problem solutions
-Apply computing skills for computational modelling, research instrument design, data analysis, and report writing and presentation
-Work to deadlines and within work schedules
-Work independently or as part of a team
-Demonstrate experience of a work environment

PLACEMENTS

On the MSc Social Science and Complexity, we offer the opportunity to take a research placement during the Easter vacation. This will provide you with first-hand experience of real-life policy research in action.

Organisations in which placements might be possible are a number of consultancies (e.g. Sandtable), government departments (e.g. Defra) and academic research centres (e.g. Centre for Policy Modelling at Manchester).

CAREER OPPORTUNITIES

Computational methods and especially computer-based simulations, are becoming increasingly important in academic social science and policy making.

Graduates might find career opportunities in government departments, consultancies, government departments, consultancies, NGOs and academia.

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

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Take advantage of one of our 100 Master’s Scholarships to study Computational Mechanics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Computational Mechanics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Swansea University has gained a significant international profile as one of the key international centres for research and training in computational mechanics and engineering. As a student on the Master's course in Erasmus Mundus Computational Mechanics, you will be provided with in-depth, multidisciplinary training in the application of the finite element method and related state-of-the-art numerical and computational techniques to the solution and simulation of highly challenging problems in engineering analysis and design.

Key Features of Erasmus Mundus Computational Mechanics MSc

The Zienkiewicz Centre for Computational Engineering is acknowledged internationally as the leading UK centre for computational engineering research. It represents an interdisciplinary group of researchers who are active in computational or applied mechanics. It is unrivalled concentration of knowledge and expertise in this field. Many numerical techniques currently in use in commercial simulation software have originated from Swansea University.

The Erasmus Mundus MSc Computational Mechanics course is a two-year postgraduate programme run by an international consortium of four leading European Universities, namely Swansea University, Universitat Politècnica de Catalunya (Spain), École Centrale de Nantes (France) and University of Stuttgart (Germany) in cooperation with the International Centre for Numerical Methods in Engineering (CIMNE, Spain).

As a student on the Erasmus Mundus MSc Computational Mechanics course, you will gain a general knowledge of the theory of computational mechanics, including the strengths and weaknesses of the approach, appreciate the worth of undertaking a computational simulation in an industrial context, and be provided with training in the development of new software for the improved simulation of current engineering problems.

In the first year of the Erasmus Mundus MSc Computational Mechanics course, you will follow an agreed common set of core modules leading to common examinations in Swansea or Barcelona. In addition, an industrial placement will take place during this year, where you will have the opportunity to be exposed to the use of computational mechanics within an industrial context. For the second year of the Erasmus Mundus MSc Computational Mechanics, you will move to one of the other Universities, depending upon your preferred specialisation, to complete a series of taught modules and the research thesis. There will be a wide choice of specialisation areas (i.e. fluids, structures, aerospace, biomedical) by incorporating modules from the four Universities. This allows you to experience postgraduate education in more than one European institution.

Modules

Modules on the Erasmus Mundus MSc Computational Mechanics course can vary each year but you could expect to study the following core modules (together with elective modules):

Numerical Methods for Partial Differential Equations
Continuum Mechanics
Advanced Fluid Mechanics
Industrial Project
Finite Element Computational Analysis
Entrepreneurship for Engineers
Finite Element in Fluids
Computational Plasticity
Fluid-Structure Interaction
Nonlinear Continuum Mechanics
Computational Fluid Dynamics
Dynamics and Transient Analysis
Reservoir Modelling and Simulation

Accreditation

The Erasmus Mundus Computational Mechanics course is accredited by the Joint Board of Moderators (JBM).

The Joint Board of Moderators (JBM) is composed of the Institution of Civil Engineers (ICE), the Institution of Structural Engineers (IStructE), the Chartered Institution of Highways and Transportation (CIHT), and the Institute of Highway Engineers (IHE).

This degree is accredited as meeting the requirements for Further Learning for a Chartered Engineer (CEng) for candidates who have already acquired an Accredited CEng (Partial) BEng(Hons) or an Accredited IEng (Full) BEng/BSc (Hons) undergraduate first degree.

See http://www.jbm.org.uk for further information.

This degree has been accredited by the JBM under licence from the UK regulator, the Engineering Council.

Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Links with Industry

On the Erasmus Mundus MSc Computational Mechanics course, you will have the opportunity to apply your skills and knowledge in computational mechanics in an industrial context.

As a student on the Erasmus Mundus MSc Computational Mechanics course you will be placed in engineering industries, consultancies or research institutions that have an interest and expertise in computational mechanics. Typically, you will be trained by the relevant industry in the use of their in-house or commercial computational mechanics software.

You will also gain knowledge and expertise on the use of the particular range of commercial software used in the industry where you are placed.

Careers

The next decade will experience an explosive growth in the demand for accurate and reliable numerical simulation and optimisation of engineering systems.

Computational mechanics will become even more multidisciplinary than in the past and many technological tools will be, for instance, integrated to explore biological systems and submicron devices. This will have a major impact in our everyday lives.

Employment can be found in a broad range of engineering industries as this course provides the skills for the modelling, formulation, analysis and implementation of simulation tools for advanced engineering problems.



Student Quotes

“I gained immensely from the high quality coursework, extensive research support, confluence of cultures and unforgettable friendship.”

Prabhu Muthuganeisan, MSc Computational Mechanics

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.

Key Features of the MSc Data Science

The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.

The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.

Modules

Modules for the MSc Data Science programme include:

- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Career Destinations

- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MSc in Computer Science course is for you if you are a graduate from one of a wide range of disciplines and are looking to change direction or because of the needs of your chosen career, require a solid foundation in Computer Science.

As the use of computers and computer based systems continues to grow in all aspects of life, at home and at work, it is apparent that there will be for years to come a need for many people who can combine a knowledge of Computer Science, the discipline that underlies Information Technology, and degree level knowledge in a wide variety of other disciplines.

Over the duration of the MSc Computer Science course you will study a variety of modules taught by academic staff that are part of internationally renowned research groups. The course is also regularly updated to ensure that it keeps pace with the rapid developments in Computer Science.

Key Features of Computer Science MSc

• We are top in the UK for career prospects*
• We are 3rd in the UK for teaching quality**
• 5th in the UK overall*
• 7th in the UK for student satisfaction with 98% [National Student Survey 2016]
• 7th in the UK overall and Top in Wales*
• High employability prospects - we are 8th in the UK for graduate prospects*
• 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
• UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
• Our Project Fair allows students to present their work to local industry
• Strong links with industry
• £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)

*Guardian University Guide 2017
**Times & Sunday Times University Guide 2016

Modules of Computer Science MSc

Modules for the MSc in Computer Science include Computer Science Project Research Methods but please visit our course page for more information.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Graduates of Computer Science were in professional level work or study [DLHE 14/15].

Student Profile

“I chose the MSc Computer Science as a conversion from my previous War and Society degree, primarily employment opportunities. The course was by no means easy for me coming from an arts background, and the first few weeks I felt a little over my head, but thanks to the truly stimulating content from the syllabus and the high quality of the teaching within the department I soon caught up and began to thrive on the course. My project revolved around a comparative study of the Haskell Web-Framework Yesod and ASP.NET. During the completion of this I picked up many of the skills that I now use on an everyday basis in my role at Kinspeed (A Sheffield based Software House). Since starting work I have been able to apply many of the skills I obtained during my time at Swansea and have no doubt that choosing to study the MSc Computer Science at Swansea was one of the better decisions of my life.”

Chris Swires

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

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Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains. Read more
Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains.

We offer a two-year Master of Science in Computer Science centered on this emerging field. The backbone of the program is constituted by three core units on advanced data management, machine learning, and high performance computing. Leveraging on the expertise of our faculty, the rest of the program is organised in four tracks, Business Intelligence, Health & Life Sciences, Pervasive Computing, and Visual Computing, each providing a solid grounding in data science and engineering as well as a firm grasp of the domain of interest.

By blending standard classes with recitations and lab sessions our program ensures that each student masters the theoretical foundations and acquires hands-on experience in each subject. In most units credit is obtained by working on a final project. Additional credit is also gained through short-term internship in the industry or in a research lab. The master thesis is worth 25% of the total credit.

TRACKS

• Business Intelligence. This track builds on first hand knowledge of business management and fundamentals of data warehousing, and focuses on data mining, graph analytics, information visualisation, and issues related to data protection and privacy.
• Health & Life Sciences. Starting from core knowledge of signal and image processing, bioinformatics and computational biology, this track covers methods for biomedical image reconstruction, computational neuroengineering, well-being technologies and data protection and privacy.
• Pervasive Computing. Security and ubiquitous computing set the scene for this track which deals with data semantics, large scale software engineering, graph analytics and data protection and privacy.
• Visual Computing. This track lays the basics of signal & image processing and of computer graphics & augmented reality, and covers human computer interaction, computational vision, data visualisation, and computer games.

PROSPECTIVE CAREER

Senior expert in Data Science and Engineering. You will be at the forefront of the high-tech job market since all big companies are investing on data driven approaches for decision making and planning. The Business Intelligence area is highly regarded by consulting companies and large enterprises, while the Health and Life Sciences track is mainly oriented toward biomedical industry and research institutes. Both the Pervasive and the Visual Computing tracks are close to the interests of software companies. For all tracks a job in a start-up company or a career on your own are always in order.

Senior computer scientist.. By personalizing your plan of study you can keep open all the highly qualified job options in software companies.

Further graduate studies.. In all cases, you will be fully qualified to pursue your graduate studies toward a PhD in Computer Science.

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Computer science has an ever-greater influence on our lives, and the technological breakthroughs of today shape the way we live tomorrow. Read more

Overview

Computer science has an ever-greater influence on our lives, and the technological breakthroughs of today shape the way we live tomorrow. Opportunities continue to grow for highly skilled practitioners, and the taught Masters course allows you to make great advancements on your existing skills and knowledge. By the end of the programme you will be equipped to thrive in one of the fastest moving industries in the world.

Industrial Placement Trimester

There is the option to take an Industrial Experience variant, with the opportunity to extend the period of study by a trimester, to gain experience of working alongside commercial software developers within a commercial software development facility on site (SEED), promoting real-world applications of the advanced concepts met in the course.

You will learn specialist computer science techniques and fundamental theories, but you’ll also have the opportunity to put this knowledge into practice by developing applications and working with real software. We cover a range of topics, including real time graphics and computational science, and you can choose from options including artificial intelligence, robotics and visualisation – built upon a solid foundation of good programming skills.

The course begins each September each year and lasts twelve months. There are two trimesters of taught modules, followed by an individual dissertation project during the third trimester. There is an option to take an extra trimester – either immediately before or after the dissertation – gaining industrial experience through a module based in SEED, our software development unit working with commercial clients and software. This is unique to Hull.

The Department of Computer Science creates an excellent experience for students, with a supportive student community. We have an international reputation for our research activities, with a strong record of industrial and public grant funding. We are also affiliated with Microsoft’s DreamSpark programme, which allows you to access the latest Microsoft operating systems and development software for home use. Once registered with the department, you can download the software free of charge.

Study

The MSc programme is designed to support students with various levels of computing and programming practice experience. However, this programme is particularly suited to those with significant experience of writing code. There is a focus on the transition to postgraduate study, with suitable content on professional skills and the importance of ethics for practising computer scientists.
In lectures you’ll benefit from a range of techniques, from interpreting complex ideas through interactive discussions, to live programming or other problem-solving demonstrations.

Core modules

• C++ Programming and Design
• Real Time Graphics
• Advanced Computational Science
• Development Project

Optional modules

• Game Development Architecture
• Simulation and Concurrency
• Visualization
• Advanced Rendering and Artificial Intelligence for Games
• Trustworthy Computing
• Dissertation (There is the option of taking this module either in trimester 3 or trimester 4, depending on whether you take the Industrial Experience module.)
• The Industrial Experience optional 60-credit single trimester module allows students to gain significant commercial experience.

Teaching and learning

We place a strong emphasis on practical laboratory sessions. This will significantly develop your core computer science skills, and enhance your employability through exposure to commercial projects.
As teamwork plays a key role in commercial software development and has great value as an employable skill, group work is used in a number of modules.

Assessment

Practical coursework is the main form of assessment, and you will design, build and test software solutions to a variety of problems.
Written coursework is used to assess your descriptive and critical skills, as well as verify the methodology used to complete your practical coursework. The largest assessment is the dissertation, which is based on the work done in the third trimester (or fourth, depending on your option choices) and documented in a report of up to 20,000 words.

Careers

The MSc Advanced Computer Science programme is designed to open up pathways to postgraduate research, as well as a wide range of careers. The computational science module introduces concepts and ideas which will help prepare you for postgraduate study; the industrial placement option, meanwhile, will enable you to practise your skills and knowledge of computer science ‘in situ’, giving you a useful insight and advantage when it comes to starting your career.
We have a range of inspirational extra-curricular activities including the Three Thing Game, Imagine Cup Worldwide Software Development Challenge, Really Useful Seminars and Global Game Jam. They are designed to boost your CV and employability, and taking part costs very little.

Our MSc graduates typically gain roles including: Applications Developer, Business Systems Analyst, Computer Analyst, Computer Programmer, Computer Operations Manager, Data Management Analyst, Database Assistant, Developer Support Engineer, Games Programmer, Games Programmer (Engine design), Information Manager, IT Design, IT Systems Manager, IT Technician, IT user Support, Mobile Developer, Operations Director, Software Designer, Software Developer, Software Engineer, Solutions Developer, Systems Engineer, Technical Sales, Technical Specialist, Web Developer.

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Advanced Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Advanced Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

On the MSc in Advanced Computer Science course you will be thoroughly prepared for a career in IT or related industries. The Advanced Computer Science course is for you if you are a Computer Science graduate or if you have gained experience of computing and programming in a different first degree. Willingness to work hard and an ability to problem solve are equally important for this MSc in Advanced Computer Science. The MSc in Advanced Computer Science course will develop the skills and knowledge you have gained from your first degree by broadening and deepening your knowledge of Computer Science through a variety of advanced modules and material. The MSc in Advanced Computer Science is accredited by the British Computer Society.

Key Features of Advanced Computer Science MSc

• We are top in the UK for career prospects*
• We are 3rd in the UK for teaching quality**
• 5th in the UK overall*
• 7th in the UK for student satisfaction with 98% [National Student Survey 2016]
• 7th in the UK overall and Top in Wales*
• High employability prospects - we are 8th in the UK for graduate prospects*
• 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
• UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
• Our Project Fair allows students to present their work to local industry
• Strong links with industry
• £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)

*Guardian University Guide 2017
**Times & Sunday Times University Guide 2016

Modules of Advanced Computer Science MSc

Modules for the MSc in Advanced Computer Science include Computer Science Project Research Methods but please visit our course page for more information.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Graduates of Computer Science were in professional level work or study [DLHE 14/15]

Student Profile

Francesca Madeddu, originally from Italy, completed an outstanding Master’s thesis (which earned her a distinction) investigating interaction with augmented reality on mobile devices. More specifically, she investigated how to interact with virtual Egyptian artefacts placed in real scenes. The final game was deployed at Swansea's Egypt Centre last year and was evaluated by volunteers working at the museum. A Master’s thesis does not often lead to a publication. However, part of Francesca's research was written up as an extended abstract and presented at Computer Graphics and Visual Computing (CGVC), a Eurographics UK conference for visual computing last year. An exceptional achievement!

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Take advantage of one of our 100 Master’s Scholarships to study Theoretical Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Theoretical Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Computer Science is at the cutting edge of modern technology, is developing rapidly, and Swansea Computer Science graduates enjoy excellent employment prospects.

Computer Science now plays a part in almost every aspect of our lives - science, engineering, the media, entertainment, travel, commerce and industry, public services and the home.

The MSc by Research Theoretical Computer Science enables students to pursue a one year individual programme of research. The
Theoretical Computer Science programme would normally terminate after a year. However, under appropriate circumstances, this first year of research can also be used in a progression to Year 2 of a PhD degree.

As a student of the Theoretical Computer Science MSc by Research programme, you will be fully integrated into one of our established computer science research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Key Features of Theoretical Computer Science

The Department of Computer Science is amongst the top 25 in the UK, with a growing reputation in research both nationally and internationally in computer science. It is home to world class researchers, excellent teaching programmes and fine laboratory facilities.

All postgraduate Computer Science programmes will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Research

The results of the Research Excellence Framework (REF) 2014 show that we lead Wales in the field of Computer Science and are in the UK Top 20.

We are ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

Links with Industry

Each spring, Computer Science students prepare and present a poster about their project at a project fair – usually together with a system or software demonstration. The Department of Computer Science also strongly encourages students to create CVs and business cards to take along to the fair, as businesses and employers visit to view the range of projects and make contact with the graduating students.

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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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Computer science has an ever-greater influence on our lives, and the technological breakthroughs of today shape the way we live tomorrow. Read more

Overview

Computer science has an ever-greater influence on our lives, and the technological breakthroughs of today shape the way we live tomorrow. Opportunities continue to grow for highly skilled practitioners, and the taught Masters course allows you to make great advancements on your existing skills and knowledge. By the end of the programme you will be equipped to thrive in one of the fastest moving industries in the world.

Industrial Placement Trimester

This degree comprises of 4 trimesters - including Industrial Experience to benefit from working alongside commercial software developers within a commercial software development facility on site (SEED), promoting real-world applications of the advanced concepts met in the course.

You will learn specialist computer science techniques and fundamental theories, but you’ll also have the opportunity to put this knowledge into practice by developing applications and working with real software. We cover a range of topics, including real time graphics and computational science, and you can choose from options including artificial intelligence, robotics and visualisation – built upon a solid foundation of good programming skills.

The course begins each September each year and lasts twelve months. There are two trimesters of taught modules, followed by
industrial experience through a module based in SEED, our software development unit working with commercial clients and software. This is unique to Hull. The degree ends with an individual dissertation project during the fourth trimester.

The Department of Computer Science creates an excellent experience for students, with a supportive student community. We have an international reputation for our research activities, with a strong record of industrial and public grant funding. We are also affiliated with Microsoft’s DreamSpark programme, which allows you to access the latest Microsoft operating systems and development software for home use. Once registered with the department, you can download the software free of charge.

Study

The MSc programme is designed to support students with various levels of computing and programming practice experience. However, this programme is particularly suited to those with significant experience of writing code. There is a focus on the transition to postgraduate study, with suitable content on professional skills and the importance of ethics for practising computer scientists.
In lectures you’ll benefit from a range of techniques, from interpreting complex ideas through interactive discussions, to live programming or other problem-solving demonstrations.

Core modules

• C++ Programming and Design
• Real Time Graphics
• Advanced Computational Science
• The Industrial Experience single trimester module allows students to gain significant commercial experience
.• Development Project

Optional modules

• Game Development Architecture
• Simulation and Concurrency
• Visualization
• Advanced Rendering and Artificial Intelligence for Games
• Trustworthy Computing
For details see https://www.courses.hull.ac.uk/programmes/1617/081671.html

Teaching and learning

We place a strong emphasis on practical laboratory sessions. This will significantly develop your core computer science skills, and enhance your employability through exposure to commercial projects.
As teamwork plays a key role in commercial software development and has great value as an employable skill, group work is used in a number of modules.

Assessment

Practical coursework is the main form of assessment, and you will design, build and test software solutions to a variety of problems.
Written coursework is used to assess your descriptive and critical skills, as well as verify the methodology used to complete your practical coursework. The largest assessment is the dissertation, which is based on the work done in the third trimester (or fourth, depending on your option choices) and documented in a report of up to 20,000 words.

Careers

The MSc Advanced Computer Science programme is designed to open up pathways to postgraduate research, as well as a wide range of careers. The computational science module introduces concepts and ideas which will help prepare you for postgraduate study; the industrial placement option, meanwhile, will enable you to practise your skills and knowledge of computer science ‘in situ’, giving you a useful insight and advantage when it comes to starting your career.
We have a range of inspirational extra-curricular activities including the Three Thing Game, Imagine Cup Worldwide Software Development Challenge, Really Useful Seminars and Global Game Jam. They are designed to boost your CV and employability, and taking part costs very little.

Our MSc graduates typically gain roles including: Applications Developer, Business Systems Analyst, Computer Analyst, Computer Programmer, Computer Operations Manager, Data Management Analyst, Database Assistant, Developer Support Engineer, Games Programmer, Games Programmer (Engine design), Information Manager, IT Design, IT Systems Manager, IT Technician, IT user Support, Mobile Developer, Operations Director, Software Designer, Software Developer, Software Engineer, Solutions Developer, Systems Engineer, Technical Sales, Technical Specialist, Web Developer.

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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
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.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

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.

Selection of the Major

The sub-programmes in the Master’s programme for computer science are:
-Algorithms
-Networking and services
-Software systems

You can select any of these programmes according to your preferences at the beginning of your studies. The sub-programme determines which courses you should take.

Programme Structure

The Master’s programme comprises 120 credits, which can be completed in two years, in accordance with an approved personal study plan. The degree includes:
-80 credits of advanced courses, including shared courses within the programme, courses within the programme which support the thesis topic, the Master’s thesis (Pro gradu), 30 credits.
-40 credits of other courses from your own or other programmes. The other courses can include a work-orientation period.

Career Prospects

The employment outlook within the field is excellent. Masters of computer science find varied positions within the ICT field, both as employees and entrepreneurs. The nature of the education is also geared towards giving you an aptitude for managerial posts. All the sub-programmes provide the qualifications to find employment in a wide variety of jobs.

Software-system graduates often start their careers as software developers and designers, while network graduates often start with software at the infrastructure level (such as data communications, computation, or data entry). The skills learned in the algorithms sub-programme enable you to work on challenging tasks in various fields.

As a graduate you can find employment within small or large corporations as well as organisations in the private, public, or third sector. Due to the global nature of the field, you can find employment anywhere in the world. Taking modules from other education programmes will help you apply your computer science skills in other areas. Many jobs are based on these combinations.

Thanks to its strong scientific basis, the degree is also an excellent springboard to a doctoral programme.

Internationalization

There is a very international atmosphere within the programme, as nearly a third of the students come from abroad, and the advanced courses are instructed by international researchers.

In addition, the University of Helsinki and the Faculty of Science offer you many opportunities for international activities:
-Instruction in English within other education programmes.
-International tasks within the students’ organisations or union.
-Language courses at the Language Centre of the University of Helsinki.

You can also get information and counselling about independent international experience, such as:
-Student exchange in one of the exchange locations of the faculty or university.
-Traineeships abroad.

Computer science at the University of Helsinki is a popular exchange location, especially from Germany. Some 5-10 students come annually; exchange students have come from 14 countries in recent years. The students in the department have taken exchange periods in 16 countries in the past few years.

Research Focus

There are several multidisciplinary research projects under way at the Faculty of Science, which are being carried out in cooperation with the research institutes on the science campus and with other faculties, universities, and corporations. The role of computer science within these projects is to develop the basic methods of the discipline in strategic areas and to collaborate in depth with other disciplines.

The sub-programmes within the Master’s programme cover a considerable part of the strategic focus areas of computer science research at the University of Helsinki: algorithms, data analysis and machine learning, networking and services, software systems, bioinformatics, and data science.

Computer science is part of three Finnish Academy centres of excellence: for computational inference, inversion problems, and cancer genetics. These units represent the collaboration between computer science and other disciplines.

Computer science has coordinated the long-lived Algodan centre of excellence, which has been the basis for many current research groups.

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Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. Read more
Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

Degree information

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules from computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

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 dissertation/report (60 credits).

Core modules
-Introduction to Statistical Data Science
-Introduction to Supervised Learning
-Statistical Design of Investigations
-Statistical Computing

Optional modules - st least two from a choice of Statistical Science modules including:
-Applied Bayesian Methods
-Decision & Risk
-Factorial Experimentation
-Forecasting
-Quantitative Modelling of Operational Risk and Insurance Analytics
-Selected Topics in Statistics
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Stochastic Systems

Up to two from a choice of Computer Science modules including:
-Affective Computing and Human-Robot Interaction
-Graphical Models
-Statistical Natural Language Processing
-Information Retrieval & Data Mining

Dissertation/report
All students undertake an independent research project, culminating in a dissertation usually comprising 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Careers

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study.

The Data Science MSc is a new programme with the first cohort of students due to graduate in 2017. Recent career destinations for graduates of the related Statistics MSc include:
-Towers Watson, Actuary Analyst
-Proctor & Gamble, Statistician
-Ernst & Young, Audit Associate
-Collinson Group, Insurance Analyst
-UCL, PhD Statistical Science

Employability
Data science professionals will be highly sought after as the integration of statistical and computational analytical tools becomes increasingly essential in all kinds of organisations and enterprises. A solid understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should go along with statistical expertise as graduate level. Data scientists should have a broad background so that they will be able to adapt themselves to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

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Take advantage of one of our 100 Master’s Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

As an MSc by Research Computer Science student you will be guided by internationally leading researchers in the field of computer science and will carry out a large individual research project. Computer Science is at the cutting edge of modern technology, and is developing rapidly and Swansea Computer Science graduates enjoy excellent employment prospects.

Computer Science now plays a part in almost every aspect of our lives - science, engineering, the media, entertainment, travel, commerce and industry, public services and the home.

The MSc by Research Computer Science degree enables you to pursue a one year individual programme of research in the field of computer science and would normally terminate after a year. However, under appropriate circumstances, this first year of research can also be used in a progression to Year 2 of a PhD degree.

The MSc by Research programmes including Computer Science MSc by Research all have a recommended initial research training module (Science Skills & Research Methods), but otherwise has no taught element and is most suitable for you if you have an existing background in biosciences or cognate discipline and are looking to pursue a wholly research-based programme of study.

As a student of the MSc by Research Computer Science programme you will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Research

The results of the Research Excellence Framework (REF) 2014 show that we lead Wales in the field of Computer Science and are in the UK Top 20.

We are ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

Links with Industry

Each spring, Computer Science students prepare and present a poster about their project at a project fair – usually together with a system or software demonstration. We also strongly encourage students to create CVs and business cards to take along to the fair, as businesses and employers visit to view the range of projects and make contact with the graduating students.

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