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Masters Degrees (Pattern Recognition)

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The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC. Read more
The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC.

Develop your knowledge and understanding of the animation process, software tools, techniques and packages, and the technical aspects of working in a professional animation environment. The MSc programme offers invaluable experience of working to professional briefs and under expert supervision of professional animators to prepare you for a career in industry.

Competition is fierce in animation and visual effects and success depends on your concentration levels, constant practise and ability to grasp the essence and modern techniques of animation. Successful former students are now working in animation and animation layout roles for companies such as Sony Games and Framestore CFC on major titles in games, television and film.

Visit the website https://www.kent.ac.uk/courses/postgraduate/248/computer-animation

About the School of Engineering and Digital Arts

The School of Engineering and Digital Arts successfully combines modern engineering and technology with the exciting field of digital media. The School, which was established over 40 years ago, has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. We have a thriving student population studying for postgraduate degrees in a friendly, supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

This intensively taught postgraduate course lasts a full year. It takes place in a dedicated computer laboratory where you have your own seat and computer for the duration of the course. The course lectures and workshops, whether led by visiting professionals or staff, are all held in this room. Demonstrations and showing of films are by means of an HD projector. By the end of the year, the lab will be where you live as much as your accommodation.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

EL831 - Digital Visual Art set-up (15 credits)
EL832 - Animation Principles (15 credits)
EL833 - Visual Training (15 credits)
EL837 - Professional Group Work (15 credits)
EL863 - Advanced 3D Modelling (15 credits)
EL864 - Pre-Visualisation (15 credits)
EL865 - Action in Animation (15 credits)
EL866 - Acting in Animation (15 credits)
EL830 - Computer Animation Project (60 credits)

Assessment

Each module is assessed by practical assignments. The project work is assessed on the outcome of the project itself.

Programme aims

This programme aims to:

- enable you to develop your knowledge and understanding within the field of 3D computer animation, which will equip you to become a professional in the animation and visual effects industry

- produce professionally-trained animators who are highly skilled in using state-of-the-art 3D animation software for producing animated films

- provide you with proper academic guidance and welfare support

- create an atmosphere of co-operation and partnership between staff and students, and offer you an environment where you can develop your potential

- strengthen and expand opportunities for industrial collaboration with the School of Engineering and Digital Arts.

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed the programme with a number of industrial organisations, which means that successful students will be in a strong position to build a long-term career in this important discipline.

The School of Engineering and Digital Arts (http://www.eda.kent.ac.uk/) has an excellent record of student employability (http://www.eda.kent.ac.uk/school/employability.aspx). We are committed to enhancing the employability of all our students, to equip you with the skills and knowledge to succeed in a competitive, fast-moving, knowledge-based economy.

Graduates who can show that they have developed transferable skills and valuable experience are better prepared to start their careers and are more attractive to potential employers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. Read more
The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. The School enjoys an international reputation for its work and prides itself in allowing students the freedom to realise their maximum potential.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

We undertake high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Visit the website https://www.kent.ac.uk/courses/postgraduate/262/electronic-engineering

Project opportunities

Some projects available for postgraduate research degrees (http://www.eda.kent.ac.uk/postgraduate/projects_funding/pgr_projects.aspx).

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries. Read more

Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries.

This programme delivers the expertise you'll need to forge a career in medical imaging, including radiation physics, image processing, biology, computer vision, pattern recognition, artificial intelligence and machine learning.

Programme structure

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and an extended project.

Example module listing

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.

Facilities, equipment and support

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab.

The Department’s student common room is also covered by the university’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices. There is also a Faculty quiet room for individual study.

We pride ourselves on the many opportunities that we provide to visit collaborating hospitals. These enable you to see first-hand demonstrations of medical imaging facilities and to benefit from lectures by professional practitioners.

To support material presented during the programme, you will also undertake a selection of ultrasound and radiation detection experiments, hosted by our sister MSc programme in Medical Physics.

Educational aims of the programme

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).

To fulfil these objectives, the programme aims to:

  • Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
  • Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
  • Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
  • Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
  • Provide a high level of flexibility in programme pattern and exit point
  • Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Technical characteristics of the pathway

Medical Imaging is a rapidly growing discipline within the healthcare sector, incorporating engineers, physicists, computer scientists and clinicians. It is driven by the recent rapid development of 3-D Medical Imaging Systems, fuelled by an exponential rise in computing power.

New methods have been developed for the acquisition, reconstruction, processing and display of digital medical-image data with unprecedented speed, resolution and contrast.

This programme in Medical Imaging is aimed at training graduates for careers in this exciting multi-disciplinary area, and our graduates can expect to find employment in the medical imaging industry or the public health care sector.

It represents a blend of fundamental medical physics topics concerned with image acquisition and reconstruction coupled with imaging science and image engineering topics such that graduates understand how images are formed and how advanced machine-based methods can be bought to bare to provide new diagnostic information.

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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The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. Read more
The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. The digital media group has interests in many areas of interactive multimedia and digital film and animation.

Visit the website https://www.kent.ac.uk/courses/postgraduate/264/digital-arts

About the School of Engineering and Digital Arts

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research (http://www.eda.kent.ac.uk/research/default.aspx) that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

The digital media group has interests in many areas of interactive multimedia and digital film and animation.

There is particular strength in web design and development, including e-commerce, e-learning, e-health; and the group has substantial experience in interaction design (eg, Usability and accessibility), social computing (eg, Social networking, computer mediated communication), mobile technology (eg, iPhone), virtual worlds (eg, Second Life) and video games. In the area of time-based media, the group has substantial interest in digital film capture and editing, and manipulation on to fully animated 3D modelling techniques as used in games and feature films.

Research Themes:
- E-Learning Technology (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=1)

- Medical Multimedia Applications and Telemedicine (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=2)

- Human Computer Interaction and Social Computing (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=3)

- Computer Animation and Digital Visual Effects (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=4)

- Mobile Application Design and Development (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=25)

- Digital Arts (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=26)

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Our MSc in Data Science and Analytics aims to provide you with a comprehensive set of skills needed to handle, collect, store and analyse large and complex sets of data. Read more
Our MSc in Data Science and Analytics aims to provide you with a comprehensive set of skills needed to handle, collect, store and analyse large and complex sets of data. You will be taught by subject experts from both the School of Mathematics and the School of Computer Science and Informatics, which will allow you to see the topic from different perspectives and provides access to a wide range of modules across both Schools.

Throughout the course you will develop data handling and extraction skills, programming skills, machine learning and informatics skills, and problem solving and modelling skills. You will undertake case studies and project work which will give you the opportunity to put your skills into practice and provides valuable experience of working in the field. The dissertation project, typically undertaken with an industrial partner, will allow you to work with complex data in a creative manner and a problem-solving environment, as well as to communicate your ideas and findings effectively.

This programme is available on a one year full-time basis or a three-year part-time basis.

Distinctive features:

• A three-stage degree with exit points at PG Certificate, PG Diploma and Master’s level, allowing you to go into as much depth as you like.

• Acquire transferable data science and analytics skills that are highly sought after in a broad range of sectors.

• Learn from experts across the Schools of Mathematics and Computer Science and Informatics, and related University research groups specialising in various applications of data science and analytics, for example the Data Innovation Research Institute, Social Data Science Lab, and Health Modelling Centre Cymru.

• Gain valuable work experience; we have some placement opportunities available with industrial partners in the UK and abroad.

Structure

There are three stages to this programme. During the first stage, you will study a number of core modules covering fundamental subjects such as statistics, pattern recognition, data mining and optimisation. You may choose to exit after this first stage, at which point you may be able to obtain a PG Certificate qualification.

The second stage consists of a range of optional modules where you can explore subjects of interest to you and relevant your potential career path, for example web and social computing, time series and forecasting, supply chain modelling and visual communication and information design. You may choose to exit after the second stage, at which point you may be able to obtain a PG Diploma qualification.

The third and final stage consists of a three-month dissertation project, which will typically involve working with a company on a real problem of importance. Following successful completion of all modules and the dissertation, you may be able to obtain a Master’s qualification.

As a full-time student, you will complete all modules and your dissertation project in year one.

Part-time students will typically only need to be in the University for lectures and workshops for the equivalent of one day per week over 24 weeks for years 1 and 2. The dissertation project is undertaken during year 3.

Core modules:

Pattern Recognition and Data Mining
Statistical Methods
Optimisation Methods
Dissertation

Optional modules:

Information Processing in Python
Computer Science Topic 1: Web and Social Computing
Web Application Development
Distributed and Cloud Computing
Informatics
Visual Communication and Information Design
Time Series and Forecasting
Supply Chain Modelling
Statistics and Operational Research in Government
Credit Risk Scoring

Teaching

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

Programming skills and the use of relevant software packages will be taught in our dedicated computer suites. We often invite industry experts to give presentations, which our students are welcome to attend.

We will allocate three supervisors to you for your dissertation project. Usually your supervisors will be two members of academic staff with an interest or specialism in your field of research and a sponsor supervisor from the organisation you will work with during your project. You should meet regularly with your supervisor throughout your project.

Support

All of our students are allocated a personal tutor when they enrol on the course. A personal tutor is there to support you during your studies, and can advise you on academic and personal matters that may be affecting you. You should have regular meetings with your personal tutor to ensure that you are fully supported.

You will have access to the Trevithick Library, which holds our collection of mathematical and computer science-related resources, as well as to the other Cardiff University Libraries.

We will provide you with a copy of the Student Handbook, which contains details of each School’s policies and procedures. We also support students through the University’s virtual learning environment, Learning Central, where you can ask questions in a forum or find course-related documents.

Cardiff University also offers a wide range of support services which are open to our students, such as the Graduate Centre, counselling and wellbeing, financial and careers advisors, the international office and the Student Union.

Feedback:

We offer written and oral feedback, depending on the coursework or assessment you have undertaken. You will usually receive your feedback from the module leader. If you have questions regarding your feedback, module leaders are usually happy to give advice and guidance on your progress. We aim to provide you with feedback in a timely manner after you have submitted an assessment.

Assessment

We will assess your progress throughout the course. These assessments may take the form of written exam papers, in-module assignments, and the project dissertation, where knowledge and technical competence will be appraised. We may also use group work, oral presentations and poster displays to test communication, critical thinking and problem solving skills.

Career prospects

Data is increasingly cheap and ubiquitous, and is being collected on a massive scale. There is a significant and growing demand for professionals who can work efficiently and effectively with handling such complex and sizeable data and to extract insights to help inform decision-making. The skills you gain during the programme will equip you for graduate roles in this field. This new MSc programme enhances the already well-established related postgraduate taught programmes that the School of Mathematics offers, and is expected to be as successful in the recruiting of our graduates. Previous postgraduates have gone on to work with a variety of companies and Government organisations including the Office for National Statistics, Lloyds Banking Group, Nationwide, British Airways, Network Rail, UK Government, The Financial Times, Virgin Media, Welsh Water and Admiral Insurance.

If you prefer to continue on a more academic career pathway, you may choose to continue your studies with a PhD.

Placement

You will undertake a three-month placement for your dissertation project, based with one of our industrial partners in the UK or abroad.

We employ a dedicated Knowledge Exchange Officer who will work with you to obtain a placement and support you throughout your project.

Past placements achieved by our students have been with companies such as Admiral, British Airways, Lloyds Banking Group, Welsh Water, Office for National Statistics, Sainsbury’s, Virgin Media, Transport for London, and Deloitte.

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The computer science program is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business. Read more

Program overview

The computer science program is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business.

The degree is offered on a full- or part-time basis. Courses are generally offered in the afternoons and evenings to accommodate part-time students. Full-time students take three or four courses per semester and may be able to complete the course work in three semesters. Full-time students who are required to take additional bridge courses may be able to complete the course work in four semesters. Part-time students take one or two courses per semester and may be able to complete the course work in four to five semesters. The time required to complete a master's project is one semester, but can vary according to the student and the scope of the topic. Two semesters is typical.

Plan of study

The program consists of 30 credit hours of course work, which includes either a thesis or a project. Students complete one core course, three courses in a cluster, four electives, and a thesis. For those choosing to complete a project in place of a thesis, students complete one additional elective.

Clusters

Students select three cluster courses from the following areas (see website for individual area information):
-Computer graphics and visualization
-Data management
-Distributed systems
-Intelligent systems
-Languages and tools
-Security
-Theory

Electives

Electives provide breadth of experience in computer science and applications areas. Students who wish to include courses from departments outside of computer science need prior approval from the graduate program director. Refer to the course descriptions in the departments of computer science, engineering, mathematical sciences, and imaging science for possible elective courses.

Master's thesis/project

Students may choose the thesis or project option as the capstone to the program. Students who choose the project option must register for the Project course (CSCI-788). Students participate in required in-class presentations that are critiqued. A summary project report and public presentation of the student's project (in poster form) occurs at the end of the semester.

Curriculum

Thesis/project options differ in course sequence, see the website for a particular option's modules and a particular cluster's modules.

Other admission requirements

-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Submit scores from the Graduate Record Exam.
-Have a minimum grade point average of 3.0 (B), and complete a graduate application.
-International applicants, whose native language is not English, must submit scores from the Test of English as a Foreign Language. A minimum score of 570 (paper-based) or 88 (Internet-based) is required.
-Applicants must satisfy prerequisite requirements in mathematics (differential and integral calculus, probability and statistics, discrete mathematics, and computer science theory) and computing (experience with a modern high-level language [e.g., C++, Java], data structures, software design methodology, introductory computer architecture, operating systems, and programming language concepts).

Additional information

Bridge courses:
If an applicant lacks any prerequisites, bridge courses may be recommended to provide students with the required knowledge and skills needed for the program. If any bridge courses are indicated in a student's plan of study, the student may be admitted to the program on the condition that they successfully complete the recommended bridge courses with a grade of B (3.0) or better (courses with lower grades must be repeated). Generally, formal acceptance into the program is deferred until the applicant has made significant progress in this additional course work. Bridge program courses are not counted as part of the 30 credit hours required for the master's degree. During orientation, bridge exams are conducted. These exams are the equivalent to the finals of the bridge courses. Bridge courses will be waived if the exams are passed.

Faculty:
Faculty members in the department are actively engaged in research in the areas of artificial intelligence, computer networking, pattern recognition, computer vision, graphics, visualization, data management, theory, and distributed computing systems. There are many opportunities for graduate students to participate in these activities toward thesis or project work and independent study.

Facilities:
The computer science department provides extensive facilities that represent current technology, including:
-A graduate lab with more than 15 Mac’s and a graduate library.
-Specialized labs in graphics, computer vision, pattern recognition, security, database, and robotics.
-Six general purpose computing labs with more than 100 workstations running Linux, Windows, and OS X; plus campus-wide wireless access.

Maximum time limit:
University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Read more

This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Drawing from our cutting-edge research, the programme’s content covers all areas of speech and language processing, from phonetics, speech synthesis and speech recognition to natural language generation and machine translation.

This flexible programme provides research or vocational training and can be either freestanding or lead to PhD study. The modular nature of the programme allows you to tailor it to your own interests.

Taught by leading researchers from Linguistics & English Language, the Centre for Speech Technology Research and the School of Informatics, this programme combines elements of linguistics, computer science, engineering and psychology.

You will develop up-to-date knowledge of a broad range of areas in speech and language processing and gain the technical expertise and hands-on skills required to carry out research and development in this challenging interdisciplinary area.

Programme structure

You study two semesters of taught courses, followed by a dissertation.

Most core compulsory courses have both computational and mathematical content. A few optional courses need a stronger mathematical background. Courses in the second semester can be tailored to your own interests and abilities.

Compulsory courses:

  • Accelerated Natural Language Processing
  • Computer Programming for Speech and Language Processing
  • Speech Processing
  • Univariate Statistics and Methodology Using R

Option courses may include:

  • Introduction to Phonology and Phonetics
  • Automatic Speech Recognition
  • Machine Learning and Pattern Recognition
  • Machine Translation
  • Natural Language Understanding
  • Simulating Language
  • Speech Synthesis

Learning outcomes

This programme aims to equip you with the technical knowledge and practical skills required to carry out research and development in the challenging interdisciplinary arena of speech and language technology.

You will learn about state-of-the-art techniques in speech synthesis, speech recognition, natural language processing, dialogue, language generation and machine translation.

You will also learn the theory behind such technologies and gain the practical experience of working with and developing real systems based on these technologies. This programme is ideal preparation for a PhD or working in industry.

Career opportunities

This programme will provide you with the specialised skills you need to perform research or develop technology in speech and language processing. It will also serve as a solid basis for doctoral study.



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This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. Read more

This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a standard project.

Example module listing

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.

Facilities, equipment and support

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.

Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by CVSSP.

Educational aims of the programme

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).

To fulfil these objectives, the programme aims to:

  • Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
  • Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
  • Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
  • Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
  • Provide a high level of flexibility in programme pattern and exit point
  • Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Intended capabilities for MSc graduates:

  • Underpinning learning– know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin mobile media communications
  • Engineering problem solving - be able to analyse problems within the field of mobile media communications and more broadly in electronic engineering and find solutions
  • Engineering tools - be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
  • Technical expertise - know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within mobile and media communications
  • Societal and environmental context - be aware of the societal and environmental context of his/her engineering activities
  • Employment context - be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
  • Research & development investigations - be able to carry out research-and- development investigations
  • Design - where relevant, be able to design electronic circuits and electronic/software products and systems

Technical characteristics of the pathway

This programme in Mobile Media Communications aims to provide a high-quality advanced training in aspects of multimedia signal processing for audio and video content production, processing and transmission.

The programme examines ways that relevant digital data can be captured or generated, and the digital streams processed, compressed, analysed and communicated over broadcast channels, mobile networks or internet.

Along with a basis of image, video and audio processing, it provides a grounding in communications related elements that include, for example, coding, networking and data transmission. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspiration.

Key to the programme is cross-linking between signals, and delivery of audio and video content. The Programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.

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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This specialist option of the . MSc Computational and Software Techniques in Engineering. Read more

This specialist option of the MSc Computational and Software Techniques in Engineering has been developed to deliver qualified engineers to the highest standard into the emerging field of digital signal and image processing who are capable of contributing significantly to this increased demand for both real-time and off-line systems operating over a range of mobile, embedded and workstation platforms.

Who is it for?

Developed for students interested in software development within the wide spectrum of industries in which digital signal processing and/or digital image processing plays a significant role. Suitable for candidates from a broad range of engineering backgrounds, including aeronautical, automotive, mechanical and electrical engineering in addition to the more traditional computational sciences background, who wish to both develop and complement their existing skill-set in this new area. Part-time students have a flexible commencement date.

Why this course?

This option of the MSc in Computational and Software Techniques in Engineering aims to develop your skill-base for the rapidly expanding engineering IT industry sector, not only in the UK but all over the world. Graduates in this option have the opportunity to pursue a wide range of careers embracing telecommunications, the automotive industry, medical imaging, software houses and industrial research where demand for skills is high.

This course additionally forms part of the ESTIA (Ecole Supérieure des Technologies Industrielles Avancées) Cranfield MSc programme which gives ESTIA students the opportunity to study this degree based either at Cranfield University or ESTIA in Bidart, South-West France.

Cranfield University is very well located for visiting part-time students from all over the world, and offers a range of library and support facilities to support your studies. This enables students from all over the world to complete this qualification whilst balancing work/life commitments.

Informed by Industry

The course is directed by an industrial advisory panel who meet twice a year to ensure that it provides the right mix of hands-on skills and up-to-date knowledge suitable for the wide variety of applications that this field addresses.

A number of members also attend the annual student thesis presentations which take place at the end of July. This provides a good opportunity for students to meet key employers.

Course details

The course consists of 12 core modules, including a group design project, plus an individual research project. 

The course is delivered via a combination of structured lectures, tutorial sessions and computer based workshops. Mathematical and computational methods form the basis of the specialist modules, covering the theory and application of DSIP algorithms for the analysis, interpretation and processing of data in diverse fields such as computer vision, robotics, vibro-acoustic condition monitoring, medical diagnosis, remote sensing and data visualisation. This set of specialist modules are designed to provide students with the programming techniques necessary to develop, maintain and use core DSIP solution software over a wide range of industrial settings.

Group project

The group project which takes place in the spring is designed to provide you with invaluable experience of delivering a project within an industry structured team. The project allows you to develop a range of skills including learning how to establish team member roles and responsibilities, project management, delivering technical presentations and gaining experience of working in teams that include members with a variety of expertise and often with members who are based remotely.

Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.

Recent Group Projects include:

  • Real-time Robotic Sensing
  • Automatic Video Surveillance
  • Face Recognition Systems
  • Applied Digital Signal Processing for Gear Box Analysis
  • Vibro-acoustic Analysis of Turbine Blades.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. It is very common for industrial partners to put forward real world problems or areas of development as potential research project topics. In general you will begin to consider the research project after completing 3-4 modules - it then runs concurrently with the rest of your work.

For part-time students it is common that their research thesis is undertaken in collaboration with their place of work.

Recent Individual Research Projects include:

  • Vision Systems for Real Time Driver Assistance
  • Pattern Recognition for Vibration Analysis
  • Image Stabilisation for UAV Video Footage
  • Presenting Driver Assistance Information Using Augmented Reality
  • Real-time Object Tracking for Intelligent Surveillance Systems
  • 3D Stereo Vision Systems for Robotics and Vehicles.

Assessment

Taught modules 45%, Group project 5%, Individual research project 50%

Your career

The MSc in Computer and Machine Vision attracts enquiries from companies all over the world who wish to recruit high quality graduates. There is considerable demand for students with expertise in engineering software development and for those who have strong technical programming skills in industry standard languages and tools. Graduates of this course will be in demand by commercial engineering software developers, automotive, telecommunications, medical and other industries and research organisations, and have been particularly successful in finding long-term employment.

Some students may go onto degrees, on the basis of their MSc research project. Thesis topics are most often supplied by individual companies on in-company problems with a view to employment after graduation - an approach that is being actively encouraged by a growing number of industries.

A selection of companies that have recruited our graduates include:

  • BAE Systems
  • European Aeronautic Defence and Space Company (EADS)
  • Defence, Science and Technology Laboratory (Dstl)
  • Orange France
  • Microsoft
  • EDS Unigraphics
  • Delcam
  • GKN Technology
  • Logica
  • Oracle Consulting Services
  • National Power
  • Altran Technologies
  • Earth Observation Sciences Ltd
  • Oracle Consulting Services
  • Easams Defence Consultancy
  • Xyratex.


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Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms. Data plays a role in almost every scientific discipline, business industry or social organisation. Read more

Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms.

Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. There is therefore an urgent need for data scientists in whole array of fields. In the Master’s specialisation in Data Science you’ll learn how to turn data into knowledge with the help of computers and how to translate that knowledge into solutions.

Although this Master’s is an excellent stepping-stone for students with ambitions in research, most of our graduates work as data consultants and data analysts for commercial companies and governmental organisations.

Why study Data Science at Radboud University?

- This specialisation builds on the strong international reputation of the Institute for Computing and Information Sciences (iCIS) in areas such as machine learning, probabilistic modelling, and information retrieval.

- We’re leading in research on legal and privacy aspects of data science and on the impact of data science on society and policy.

- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.

- Because of its relevance to all kinds of different disciplines, we offer our students the chance to take related courses at other departments like at language studies (information retrieval and natural language processing), artificial intelligence (machine learning for cognitive neuroscience), chemistry (pattern recognition and chemometrics) and biophysics (machine learning and optimal control).

- The job opportunities are excellent: some of our students get offered jobs before they’ve even graduated and almost all of our graduates have positions within six months after graduating.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

See the website http://www.ru.nl/masters/datascience

Admission requirements for international students

- A proficiency in English

In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:

- TOEFL score of >575(paper based) or >90 (internet based)

- IELTS score of >6.5

- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data:

- To come up with a creative and useful solution.

- To find or program the right tool to turn the data into knowledge.

- To communicate the obtained findings to others.

By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

The job perspective for our graduates is excellent. Industry desperately needs data science specialists at an academic level, and thus our graduates have no difficulty in find an interesting and challenging job. A few of our graduates decide to go for a PhD and stay at the university, but most of our students go for a career in industry. They then typically either find a job at a larger company as consultant or data analysis, or start up their own company in data analytics.

Examples of companies where our graduates end up include SMEs like Orikami, Media11 and FlexOne, and multinationals like ING Bank, Philips, ASML, Capgemini, Booking.com and perhaps even Google.

Our approach to this field

Data nowadays plays a role in almost every scientific discipline as well as industry and is rapidly becoming a key driver of scientific discoveries, business innovation, and solutions for societal challenges such as better healthcare. Medical scientists are sequencing and analysing human genomes to uncover clues to infections, cancer, and other diseases. With huge telescopes, astronomers generate terabytes of data per hour to study the formation of galaxies and the evolution of quasars. Businesses like Google and Amazon are sifting social networking and user preference data to fulfill desires we don't even know we have. Police employing seismology-like data models can predict where crimes will occur and prevent them from happening.

It is then with good reason that data science has been called the sexiest job of the 21st century. Many companies complain about the difficulty to find skilled data scientists and predict this to be even harder in the future. A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data, to come up with a creative and useful solution, to find or program the right tool to turn the data into knowledge, and to communicate the obtained findings to others. By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

See the website http://www.ru.nl/masters/datascience

Radboud University Master's Open Day 10 March 2018



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Today’s society operates on large amounts of data. Industry, governments and academia are asked to provide insight into these data. Read more
Today’s society operates on large amounts of data. Industry, governments and academia are asked to provide insight into these data.
•But how do we deal with such large amounts of data?
•What techniques do we use to mine the data?
•What are the legal and ethical aspects regarding these data sets?
•And what economic value can be found in big data?

The MSc specialization Data Science: Business and Governance trains students to become Data Scientists that can address these questions. The Harvard Business Review calls the job of Data Scientist "the sexiest job of the 21st century"!

Why Data Science: Business and Governance in Tilburg?
•Tilburg University offers a wide range of complementary expertise, including techniques for data mining, pattern recognition, business analytics, visualization and process analytics; as well as knowledge on law, regulation, ethics and entrepreneurship.
•The MSc specialization consists of courses in methods of analysis, together with economic and management as well as legal, ethical and methodological perspectives on data, all of them taught by experts in these fields.
•The Master’s specialization Data Science: Business and Governance offers (constitutes/ consists of) a well-balanced mixture of theoretical and practical (elective) courses.

These elements combine to make this specialization unique in Europe and possibly even in the world: Four schools (Tilburg School of Economics and Management, Tilburg School of Law, Tilburg School of Social and Behavioral Sciences, and the Tilburg School of Humanities) work together in offering the best possible training for the job of the future, that of Data Scientist.

Career Prospects

Data Science: Business and Governance graduates will not only have knowledge and expertise in the area of data analysis and data mining, but also in economic, management and legal perspectives on big data.

Growing need for Data Scientists

There is a growing need in government organizations, in companies and in academia for employees with the analytical skills needed to analyze large datasets, recognize patterns, and visualize data, and combining these skills with interdisciplinary knowledge of perspectives on Data Science.

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We offer Industrial Experience options on all our full-time taught MSc programmes, which combine academic study with a one-year industrial placement between your taught modules and summer project. Read more
We offer Industrial Experience options on all our full-time taught MSc programmes, which combine academic study with a one-year industrial placement between your taught modules and summer project. Taking the Industrial Experience option as part of your degree gives you a route to develop real-world, practical problem-solving skills gained through your programme of study in a professional context.

This can give you an important edge in the graduate job market. As a leading research School, we have excellent links with industry. We also employ dedicated staff to help you arrange your year in industry. The Industrial Experience programmes are highly competitive and attract the best students given the limited availability of placements. We are unable to guarantee all students secure an industrial placement, as our industrial partners conduct their own employment application and interview processes.

This programme is designed for those who want to pursue a career as data scientists, deriving valuable insights and business relevant information from large amounts of data. You will cover the fundamental statistical (eg machine learning) and technological tools (eg cloud platforms, Hadoop) for large-scale data analysis.

The course leverages the world-leading expertise in research at Queen Mary with our strategic partnership with IBM and other leading IT sector companies to offer to students a foundational MSc on the field of Data Science. The MSc modules cover the following aspects:

-Statistical Data Modelling, data visualization and prediction
-Machine Learning techniques for cluster detection, and automated classification
-Big Data Processing techniques for processing massive amounts of data
-Domain-specific techniques for applying Data Science to different domains: Computer Vision, Social Network Analysis, Bio Engineering, Intelligent Sensing and Internet of Things
-Use case-based projects that show the practical application of the skills in real industrial and research scenarios.

Students will be offered lectures that explain the core concepts, techniques and tools required for large-scale data analysis. Laboratory sessions and tutorials will put these elements to practice through the execution of use cases extracted from real domains. Students will also undertake a large project where they will demonstrate the application of Data Science skills in a complex scenario.

The programme is offered by academics from the Networks, Centre for Intelligent Sensing, Risk and Information Management, Computer Vision and Cognitive Science research groups from the School of Electronic Engineering and Computer Science. This is a team of more than 100 researchers (academics, post-docs, research fellows and PhD students), performing world leading research in the fields of Intelligent Sensing, Network Analytics, Big Data Processing platforms, Machine Learning for Multimedia Pattern Recognition, Social Network Analysis, and Multimedia Indexing.

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The programme aims at preparing engineers to develop and use information technology tools so as to satisfy the widest variety of applications. Read more

Mission and Goals

The programme aims at preparing engineers to develop and use information technology tools so as to satisfy the widest variety of applications. Compared to the Bachelor of Science, Master of Science students acquire greater ability to model and solve complex problems, integrating different advanced skills and technologies. The programme comprises three tracks: Communication and Society Engineering, Sound and Music Engineering, Data Engineering.

The teaching language is English.

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

Career Opportunities

The information technology engineer operates mainly in companies manufacturing and distributing information technology and robotics equipment and systems, companies providing products and services with a high information technology content, private organisations and public administration using information technology to plan, design, manage, decide, produce and administrate.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Computer_science_and_engineering_CO_01.pdf
The Master of Science programme in Computer Science and Engineering aims at training engineers able to develop and use information technology tools so as to satisfy the widest variety of applications. Four tracks are available, corresponding to four main cultural areas. The “Communication and Society Engineering” track focuses on the integration of computer science and communication skills, for designing, implementing, presenting and evaluating innovative multimedia applications. The methodologies for the management of data, such as data mining, pattern recognition, information retrieval, constitute the core of the “Data Engineering” track. The “ICT Engineering, Business and Innovation” track aims at building professional profiles that combine a solid computer science background with managerial capabilities, through a selection of computer science and management courses, integrated with a broad cross-disciplinary project, carried out in collaboration with companies and Management Engineering students and professors. Finally, the “Sound and Music Engineering” track (in collaboration with the “Giuseppe Verdi” Music Conservatory of Como) focuses on the concepts and processes that are behind generation, analysis, manipulation/ processing, transport, access, coding and rendering of audio and musical signals. The programme is taught in English.

Subjects

Key subjects available:
Multimedia Interactive Applications for Web and Mobile Devices, Computer Graphics and Applications, Advanced Software Engineering, Advanced Computer Architectures, Performance Evaluation of Computer Systems, Multimedia Information Retrieval, Multimedia Signal Processing, Sound Analysis, Synthesis and Processing, Electronics and Electroacoustic.

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

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

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

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