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Masters Degrees (Visualization)

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Description. This course aims at providing computer science graduates with the knowledge and skills to specialise in advanced computer graphics principles and practice, as well as gaining exposure to research activities in this field. Read more
Description

This course aims at providing computer science graduates with the knowledge and skills to specialise in advanced computer graphics principles and practice, as well as gaining exposure to research activities in this field. Students completing this course will have a firm grasp of the current practices and directions in computer graphics techniques and be able to apply them to scientific visualization, virtual environments, and computer animation.

Modules are:

* Computer Animation
* Java Programming
* Project Foundations
* Introduction to Computer Graphics
* Virtual Environments & Human Perception
* Scientific Visualization
* Computing Shape
* Sample Based Geometric Modelling
* MSc Project & Dissertation

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Parsons’ Master of Science in Data Visualization is a multidisciplinary program in which students develop skills bringing together visual design, computer science, statistical analysis, and ethical considerations of data analysis and representation. Read more

Parsons’ Master of Science in Data Visualization is a multidisciplinary program in which students develop skills bringing together visual design, computer science, statistical analysis, and ethical considerations of data analysis and representation. The presentation of data plays a critical role in the shaping of opinion, policy, and decision making in today’s increasingly global society. Giving students a competitive edge as they enter the field, the MS program responds to the increased demand for experts who can turn data into insight.

This program is part of Parsons' School of Art, Media, and Technology (AMT). Learn about the AMT community and explore our blog to see what students, faculty, and alumni are doing in NYC and around the world.

Theory and Practice

Housed within Parsons’ School of Art, Media, and Technology, the MS Data Visualization program can be completed in one or two years. The 30-credit curriculum integrates theory and studio practice, so students acquire the creative, quantitative, and coding tools needed to analyze and depict data, gaining a holistic understanding of context, audience, and objectives. With the MS in Data Visualization, students obtain the diverse skill set needed for success in a range of careers related to data interpretation. Students graduate with portfolios demonstrating their ability to create databases and Web-based software tools that reflect an understanding of data analysis and information visualization for varied applications.

Opportunities with Local Industry

The program’s setting in New York City, a technological hub and pioneer of open-source culture, offers invaluable industry access. Students intern with industry leaders and external partners from the government, nonprofit, and commercial sectors. Faculty invite guest lecturers and critics to share their insights and expose students to new possibilities in data visualization and related career paths.

Future Opportunities

Graduates find success in a wide variety of fields including data analysis, digital design, advertising and branding, journalism, business consulting and analytics strategy, management, strategic planning, entrepreneurship, social enterprise, public policy, trend forecasting, and business intelligence.

You can request more information about all possible future opportunities here: http://www.newschool.edu/m/data-visualization?utm_source=find_a_masters&utm_medium=hyperlink_listing&utm_campaign=pm_parsons_grad&utm_term=data_visualization

Financial Aid Deadline

All applicants selected for admission into our program are considered for a merit scholarship award that is determined by the strength of their application. Scholarship award notification is communicated at the same time as the admission decision. International students are eligible only for merit scholarships. If you are a U.S. citizen or eligible noncitizen, we encourage you to complete the Free Application for Federal Student Aid (FAFSA), which can be found on the Web at http://www.fafsa.gov. The FAFSA is available each year on October 1. You do not need to wait for an admission decision to apply for federal aid; we recommend submitting by our FAFSA priority deadline of February 1 for fall applicants. (The New School’s federal school code is 002780.)

You can request more information on available scholarships here: http://www.newschool.edu/m/data-visualization?utm_source=find_a_masters&utm_medium=hyperlink_listing&utm_campaign=pm_parsons_grad&utm_term=data_visualization



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This one year MSc Data Science degree prepares you to become a proficient data scientist, building core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to devising and applying sophisticated Big Data analytics techniques. Read more

This one year MSc Data Science degree prepares you to become a proficient data scientist, building core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to devising and applying sophisticated Big Data analytics techniques.

Introducing your degree

This MSc programme will train students to become proficient data scientists.

You will gain advanced knowledge in areas such as data mining, machine learning, and data visualization, including state of the art techniques, programming toolkit, and industrial and societal application scenarios.

Overview

This programme prepares you to become a proficient data scientist, developing your specialist knowledge in subjects that are crucial for mastering the vast and ever-so-complex information landscape that is characteristic to modern, digitally empowered organisations.

This is typically linked to a number of core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to the know-how that is required to devise and apply sophisticated Big Data analytics techniques, and the creativity involved in designing powerful visualizations.

In the first semester you start with a review of key topics in data science. The course will introduce the core theoretical and technology components required to design and use a data science application, using open-source tools and openly accessible data sets. You will also cover the most important machine learning techniques, which are at the core of any attempt to analyse and reason about data.

You will be exposed to more advanced topics in data mining in the second semester, including feature engineering, methods to manipulate text and multimedia data, topic modelling, social network analysis, and spectral analysis. A new module on data visualization will introduce the most common types of visualization techniques and state-of-the-art technology used to build graphic elements into data science applications to present analytics results.

Finally, during the summer the MSc project enables you will demonstrate your mastery of specialist techniques, relevant methods of enquiry, and your ability to design and deliver advanced application, systems and solutions to a tight deadline, including the production of a substantial dissertation.

Career Opportunities

Data scientists help organisations handle large amounts of data being produced thanks to digital technologies. Harvard Business Review described the role as 'The Sexiest Job of the 21st Century' due to the rare combination of skills that a trained data scientist possesses.

Data science has seen an unparalleled expansion as the data-driven economy grows. Increasingly organisations require skilled professionals who can handle large datasets and managers who can utilise the resulting analysis to make impactful decisions.

There is a range of potential jobs available; demand for big data staff is predicted to rise 92% over 5 years from Jan 2013. The programme provides an excellent opportunity for entry into data sciences or similar fields. Plus, big data positions offer a median salary of £55,000 – 24% higher than for IT staff in general (UK). There are also academic possibilities for doctoral study, as there are for entrepreneurial careers.

ECS runs a dedicated careers hub with is affiliated with more than 100 renowned companies such as IBM, Arm, Microsoft, Samsung, and Google. Visit our Careers Hub for more information.

Graduates from our MSc program can seek employment worldwide in:

  • established companies looking to spot trends in sales, marketing or operational data;
  • start-ups based around new opportunities in the booming data-driven economy;
  • government departments looking to utilise linked open data to gain insights to affect policy at the highest levels;
  • research/consultancy companies analysing data and feeding back to the wider community, with training and specialist services to clients.

Through an extensive blend of networks, mentors, societies and our on-campus startup incubator, we also support aspiring entrepreneurs looking to build their professional enterprise skills. Discover more about enterprise and entrepreneurship opportunities.



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This course is one of the premier international applied petroleum geoscience courses. Since the inception of the course in 1985 its graduates have an unparalleled employment record in the petroleum industry both in the UK and worldwide. Read more

This course is one of the premier international applied petroleum geoscience courses. Since the inception of the course in 1985 its graduates have an unparalleled employment record in the petroleum industry both in the UK and worldwide. In addition our graduates are highly sought after for further PhD research in the petroleum geosciences.

● Recognised by NERC - 5 MSc studentships each year covering fees, fieldwork and maintenance.

● Recognised by Industry - Industry scholarships

● We offer highly focused teaching and training by internationally recognised academic experts as well as by visiting staff from the petroleum industry.

The course covers the applications of basin dynamics and evolution to hydrocarbon exploration and production. The course is modular in form providing intensive learning and training in geophysics, tectonics and structural geology, sequence stratigraphy and sedimentology, hydrocarbon systems, reservoir geology, remote sensing and applied geological fieldwork.

The MSc course provides ‘state of the art’ training in -

● 3D seismic interpretation and 3D visualization;

● Fault analysis and fault-sealing;

● Seismic sequence stratigraphy;

● Applied sedimentology;

● Well log analysis;

● Remote sensing analysis of satellite and radar imagery;

● Analysis of gravity and magnetic data;

● Numerical modelling of sedimentation and tectonics;

● Applied structural geology;

● Geological Fieldwork.

● Transferable skills learned during the course include

project planning, presentation techniques, report writing and compilation, team working skills, spreadsheet and statistical analyses, GIS methods as well as graphics and visualization techniques.

● The full time MSc course runs for 50 weeks. The first half comprises one and two week course modules as well as group projects and fieldwork. The second half of the MSc course consists of an individual research project usually carried out in conjunction with the petroleum industry or related institutions such as international geological surveys.

● Part time study over 24 months is also available

● Each year independent projects are arranged with new data sets from industry – some students work in the offices of the company whereas other may use our excellent in-house facilities. All independent projects are supervised by faculty members with additional industry supervision where appropriate.

Facilities include –

● Dedicated Modern Teaching Laboratories

● 14 Dual Screen Unix Seismic Workstations

● PC and Macintosh Workstations

● Internationally Recognised Structural Modelling Laboratories

● Advanced Sedimentological Laboratories

The MSc course also greatly benefits from dynamic interaction with internationally recognised research groups within the Geology Department including –

● Project EAGLE – Evolution of the African and Arabian rift system – Professor Cindy Ebinger

● Southeast Asia Research Group – Tectonic Evolution and Basin Development in SE Asia – Professor Robert Hall

● Numerical Modelling Research Group – Numerical Modelling of Tectonics and Sedimentation – Dr Dave Waltham

● Fault Dynamics Research Group – Dynamics of Fault Systems in Sedimentary Basins – Professor Ken McClay

The 2005 MSc graduates went on to employment with Shell, BP, Amerada Hess, Gaz de France, OMV (Austria), Star Energy, First Africa Oil, Badley Ashton, ECL, PGS, Robertsons, PGL, Aceca, and to PhD research at Royal Holloway and Barcelona.

Since 2001, 85% of our graduates have gone in to work in the oil industry, 10% into geological research and 5% into environmental/engineering jobs.

Accommodation is available on campus in en-suite study bedrooms grouped in flats of eight, each with a communal kitchen and dining space.

Subsistence Costs ~£9,000 pa (including Hall of Residence fees of c. £4,500 for a full year)

APPLICATIONS can be made on line at http://www.rhul.ac.uk/Registry/Admissions/applyonline.html



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This is one of the premier international applied MSc courses with a focus on petroleum exploration and production. It is run in parallel with the Basin Evolution and Dynamics MSc in Petroleum Geocsience but with a greater emphasis on tectonics and structural geology. Read more
This is one of the premier international applied MSc courses with a focus on petroleum exploration and production. It is run in parallel with the Basin Evolution and Dynamics MSc in Petroleum Geocsience but with a greater emphasis on tectonics and structural geology. In addition to successful employment in the international petroleum industry graduates from this course are employed in the international mining industry as well as being highly sought after for further PhD research in the geosciences.

● Recognised by Industry - Industry scholarships

● We offer highly focused teaching and training by internationally recognised academic experts as well as by visiting staff from the petroleum and remote sensing industries.

The course covers the applications of tectonics and structural geology to hydrocarbon exploration and production as well as to applied structural geology research in different terranes. The course is modular in form providing intensive learning and training in tectonics, applied structural geology, seismic interpretation of structural styles, tectonostratigraphic analysis, section balancing and reconstruction, remote sensing, crustal fluids and hydrocarbon systems, reservoir geology, and applied geological fieldwork.

The MSc course provides ‘state of the art’ training in –
● Plate tectonics and terrane analysis;
● Applied structural analysis;
● 3D seismic interpretation and 3D visualization of structural styles;
● Fault analysis and fault-sealing;
● Tectonostratigraphic analysis;
● Scaled analogue modelling;
● Numerical modelling of structures;
● Remote sensing analysis of satellite and radar imagery;
● Analysis of gravity and magnetic data;
● Section balancing and reconstruction;
● Applied structural fieldwork.

● Transferable skills learned during the course include
project planning, presentation techniques, report writing and compilation, team working skills, spreadsheet and statistical analyses, GIS methods as well as graphics and visualization techniques.

● The full time MSc course runs for 50 weeks. The first half comprises one and two week course modules as well as group projects and fieldwork. The second half of the MSc course consists of an individual research project usually carried out in conjunction with the petroleum industry or related institutions such as international geological surveys.

● Part time study over 24 months is also available

● Each year independent projects are arranged with new data sets from industry – some students work in the offices of the company whereas other may use our excellent in-house facilities. All independent projects are supervised by faculty members with additional industry supervision where appropriate.

Facilities include –
● Dedicated Modern Teaching Laboratories
● Internationally Recognised Structural Modelling Laboratories
● 14 Dual Screen Unix Seismic Workstations
● PC and Macintosh Workstations
● Advanced Sedimentological Laboratories

The MSc course also greatly benefits from dynamic interaction with internationally recognised research groups within the Geology Department including –

● Project EAGLE – Evolution of the African and Arabian rift system – Professor Cindy Ebinger
● Southeast Asia Research Group – tectonic evolution and basin development in SE Asia – Professor Robert Hall
● Numerical Modelling Research Group – Numerical modelling of tectonics and sedimentation – Dr Dave Waltham
● Fault Dynamics Research Group – Dynamics of Fault Systems in Sedimentary Basins – Professor Ken McClay

Our Tectonics MSc graduates have gained employment with Shell, BP, ECL, PGS, Sipetrol, PGL, Codelco, and to PhD research in a range of universities including Trieste, Barcelona, and Ulster universities.
Since 2001, 85% of our Petroleum Geosciences MSc graduates have gone in to work in the oil industry, 10% into geological research and 5% into environmental/engineering jobs.

Accommodation is available on campus in en-suite study bedrooms grouped in flats of eight, each with a communal kitchen and dining space.

Subsistence Costs ~£9,000 pa (including Hall of Residence fees of c. £4,500 for a full year)

APPLICATIONS can be made on line at http://www.rhul.ac.uk/Registry/Admissions/applyonline.html

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

The MSc in High Performance and Scientific Computing is for you if you are a graduate in a scientific or engineering discipline and want to specialise in applications of High Performance computing in your chosen scientific area. During your studies in High Performance and Scientific Computing you will develop your computational and scientific knowledge and skills in tandem helping emphasise their inter-dependence.

On the course in High Performance and Scientific Computing you will develop a solid knowledge base of high performance computing tools and concepts with a flexibility in terms of techniques and applications. As s student of the MSc High Performance and Scientific Computing you will take core computational modules in addition to specialising in high performance computing applications in a scientific discipline that defines the route you have chosen (Biosciences, Computer Science, Geography or Physics). You will also be encouraged to take at least one module in a related discipline.

Modules of High Performance and Scientific Computing MSc

The modules you study on the High Performance and Scientific Computing MSc depend on the route you choose and routes are as follows:

Biosciences route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Conservation of Aquatic Resources or Environmental Impact Assessment

Ecosystems

Research Project in Environmental Biology

+ 10 credits from optional modules

Computer Science route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Software Engineering

Data Visualization

MSc Project

+ 30 credits from optional modules

Geography route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Modelling Earth Systems or Satellite Remote Sensing or Climate Change – Past, Present and Future or Geographical Information Systems

Research Project

+ 10 credits from optional modules

Physics route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Physics Project

+ 20 credits from optional modules

Optional Modules (High Performance and Scientific Computing MSc):

Software Engineering

Data Visualization

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Modelling Earth Systems

Satellite Remote Sensing

Climate Change – Past, Present and Future

Geographical Information Systems

Conservation of Aquatic Resources

Environmental Impact Assessment

Ecosystems

Facilities

Students of the High Performance and Scientific Computing programme will benefit from the Department that is well-resourced to support research. Swansea physics graduates are more fortunate than most, gaining unique insights into exciting cutting-edge areas of physics due to the specialized research interests of all the teaching staff. This combined with a great staff-student ratio enables individual supervision in advanced final year research projects. Projects range from superconductivity and nano-technology to superstring theory and anti-matter. The success of this programme is apparent in the large proportion of our M.Phys. students who seek to continue with postgraduate programmes in research.

Specialist equipment includes:

a low-energy positron beam with a highfield superconducting magnet for the study of positronium

a number of CW and pulsed laser systems

scanning tunnelling electron and nearfield optical microscopes

a Raman microscope

a 72 CPU parallel cluster

access to the IBM-built ‘Blue C’ Supercomputer at Swansea University and is part of the shared use of the teraflop QCDOC facility based in Edinburgh

The Physics laboratories and teaching rooms were refurbished during 2012 and were officially opened by Professor Lyn Evans, Project Leader of the Large Hadron Collider at CERN. This major refurbishment was made possible through the University’s capital programme, the College of Science, and a generous bequest made to the Physics Department by Dr Gething Morgan Lewis FRSE, an eminent physicist who grew up in Ystalyfera in the Swansea Valley and was educated at Brecon College.



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Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights. Read more
Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights.

Who is it for?

This programme is for students who have a numerate first degree or can demonstrate numerate skills. Students are often at the early stages of their careers in diverse professions including economics, statistics and computer science.

Students will have a curiosity about data, and will want to learn new techniques to boost their career and be part of exciting current industry developments. The MSc in Data Science includes some complex programming tasks because of the applied nature of the course, so many students have a mathematics or statistics background and enjoy working with algorithms.

Objectives

The demand for data scientists in the UK has grown more than ten-fold in the past five years *. The amount of data in the world is growing exponentially. From analysing tyre performance to detecting problem gamblers, wherever data exists, there are opportunities to apply it.

City’s MSc Data Science programme covers the intersection of computer science and statistics, machine learning and practical applications. We explore areas such as visualisation because we believe that data science is about generating insight into data as well as its communication in practice.

The programme focuses on machine learning as the most exciting technology for data and we have learned from our own graduates that this is of high value when it comes to employment within the field. At City, we have excellent expertise in machine learning and the facilities students need to learn the technical aspects of data analysis. We also have a world-leading centre for data visualisation, where students get exposed to the latest developments on presenting and communicating their results – a highly sought after skill.

Placements

There is the opportunity to do an internship as part of the programme. The final project, which is normally three months for a full-time student, can be extended to six months if you want to study within a specific organisation. When it comes to the big data and data science area, we have established relationships with organisations including the BBC, Microsoft and The British Library so you can be confident that with City, your access to professional experience is unparalleled. One recent student undertook an internship with Google and has since secured a job within the company.

Academic facilities

The School's computer science laboratories are equipped with the latest up-to-date hardware and software. From Oracle’s leading commercial object-relational database server to PCs with state-of-the-art NVidia GPUs for computer graphics, you will have access to an array of tools to support your learning.

The MSc Data Science programme offers two (three by mid 2016) dedicated computer servers for the Big Data module, which you can also use for your final project to analyse large data sets. We give you the opportunity to undertake training in MATLAB, the most popular numerical and technical programming environment, while you study.

Scholarships

A scholarship for the full fees of the MSc will be offered to an outstanding applicant. The scholarship is available to UK/EU and overseas students, studying full-time. To be considered for the scholarship, please include with your full application a one-page essay with your answer to the question:

'What are the challenges that Data Science faces and how would you address those challenges?'

The submission deadline for anyone wishing to be considered for the scholarship is: 1 MAY 2017

Teaching and learning

The teaching and learning methods we use mean that students’ specialist knowledge and autonomy increase as they progress through each module. Active researchers guide your progress in the areas of machine learning, data visualization, and high-performance computing, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.

Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:
-Present and exemplify the concepts underpinning a particular subject.
-Highlight the most significant aspects of the syllabus.
-Indicate additional topics and resources for private study.

Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.

Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.

In addition to lectures, laboratory sessions and tutorial support, you also have access to a personal tutor. This is an academic member of staff from whom you can gain learning support throughout your degree. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.

We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Each module is assessed through a combination of written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply data science methods and techniques.

The individual project is a substantial task. It is your opportunity to develop a research-related topic under the supervision of an academic member of staff. This is the moment when you can apply what you have learnt to solve a real-world problem using large datasets from industry, academia or government and use your knowledge of collecting and processing real data, designing and implementing big data methods and applying and evaluating data analysis, visualisation and prediction techniques. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.

Course content

Data science is the area of study concerned with the extraction of insight from large collections of data.

The course covers the study, integration and application of advanced methods and techniques from:
-Data analysis and machine learning
-Data visualisation and visual analytics
-High-performance, parallel and distributed computing
-Knowledge representation and reasoning
-Neural computation
-Signal processing
-Data management and information retrieval.

It gives you the opportunity to specialise so, once you graduate, you can apply data science to any sector from health to retail. By engaging with researchers and industrial partners during the programme, you can develop your knowledge and skills within a real-world context in each of the above areas.

Core modules
-Principles of data science (15 credits)
-Machine learning (15 credits)
-Big Data (15 credits)
-Neural computing (15 credits)
-Visual analytics (15 credits)
-Research methods and professional issues (15 credits)

Elective modules
-Advanced programming: concurrency (15 credits)
-Readings in computer science (15 credits)
-Advanced databases (15 credits)
-Information retrieval (15 credits)
-Data visualisation (15 credits)
-Digital signal processing and audio programming (15 credits)
-Cloud computing (15 credits)
-Computer vision (15 credits)
-Software agents (15 credits)

Individual project - (60 credits)

Career prospects

From health to retail, and from the IT industry to government, the Data Science MSc will prepare you for a successful career as a data scientist. You will graduate with specialist skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction and explanation, which are in high demand.

City's unique internships, our emphasis on machine learning and visual analytics, together with our links with the industry and Tech City, should help you gain employment as a specialist in data analysis and visualization. Graduates starting a new business can benefit from City's London City Incubator and City's links with Tech City, providing support for start-up businesses.

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By 2050, 2/3rd of the population will live in cities and 2 Bn new urban citizens will reside in cities that do not exist yet. Those Smart Cities needs hands-on though visionary designers to create better lives conditions and to reinvent citizenship for every stakeholder. Read more
By 2050, 2/3rd of the population will live in cities and 2 Bn new urban citizens will reside in cities that do not exist yet. Those Smart Cities needs hands-on though visionary designers to create better lives conditions and to reinvent citizenship for every stakeholder: younger/elder, families/professionals, tourists/dwellers, and by giving meaning to the best technologies.
During this 2 year program, including a final 3 to 6 month internship, students become strong professionals thanks to an intensive project-based pedagogy, and a strong connection with the industry.

Run from fall 2017, both in Paris and Singapore (subject to final endorsement), the programme is recognised by the French State through its registration by the National Council of Professional Certification (CNCP) at Level 1.


Pedagogy:

1st Year
Design Projects and Methodology
Design Culture 1
General Culture 1
Representation & Visualization 1
Industry sponsored project
Design Culture 2
General Culture 2
Representation & Visualization 2
Thesis 1

2nd Year
Thesis 2
Inter-disciplinary industry sponsored project
Humanities
Professionalization
Preparation of oral defense
Degree Project follow up
Internship

Job opportunities

When you Graduate from Master in Design for Smart Cities you'll have a wide range of jobs opportunities, such as : Interaction Designer, Intelligent Objects Designer, Design Consultant, User Experience Designer, Interface Designer, Design Manager, Service Designer, Motion Designer

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The growing availability of huge amounts of data in business and industry is generating a high demand for graduates able to handle and exploit big data. Read more
The growing availability of huge amounts of data in business and industry is generating a high demand for graduates able to handle and exploit big data. Using sophisticated analytics techniques, including social network visualization and sentiment analysis, and professional software packages, including R dplyr and ggplot2, you will gain the skills and knowledge to transform data into commercial value and boost your employability.

Key features

-Equipping applicants from almost all undergraduate degrees with broad professional competence in one of the world economy’s most sought-after postgraduate subject areas.
-Offering an equal number of taught credits in the three areas of data modelling, computing and business, with a wide choice of available business modules.
-Providing a flexible individual project in one or more of the three taught areas supervised by world-leading subject experts.
-Establishing high proficiency in the use and application of state-of-the-art programming languages including R.
-Developing modern analytics expertise for obtaining business, scientific and social insights from Big Data sources and social networks such as Facebook and Twitter.
-Consult eBooks to support your learning and receive a free Apple iPad mini to stay-up-to date, wherever you are.
-Enjoy teaching from leading academics: for example, in the UK 2014 Research Excellence Framework 68 per cent of our mathematics and statistics research papers were classified as World Leading or Internationally Excellent.

Course details

Year 1
Throughout the programme you will learn how to master sophisticated analytics techniques and professional software, including R, to handle and exploit big data, and to work as part of a project team. You will also develop practical and professional competence in data science and business analytics, and will be able to make strategic decisions in a broad range of business related practical situations.

In semester two you will select optional modules to suit your interests and career aspirations and have the opportunity to boost your employability with an optional industrial placement.

An optional placement year is available after Semester 2.

Core modules
-ISAD515 Computational Problem Solving and Computer Systems
-BPIE500 Masters Stage 1 Placement Preparation
-MATH500 Big Data and Social Network Visualization
-PROJ516 MSc Project
-SOFT562 Software Development and Databases
-MATH501 Modelling and Analytics for Data Science

Optional modules
-STO702 Global Supply Chain Management
-ACF717 Econometrics and Financial Modelling
-MKT704 Branding and Marketing Communications
-STO703 International Strategic Management
-MKT714 Social Media Practice
-MKT715 Relationship Marketing and CRM
-STO700B International Business Environment
-ACF719 Financial Management

Final year
Optional modules
-BPIE503 Mathematics Masters Industrial Placement

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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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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The master of fine arts degree in industrial design is for career enhancement or redirection. The educational experience is project-oriented, requiring research into design methods and technologies. Read more
The master of fine arts degree in industrial design is for career enhancement or redirection. The educational experience is project-oriented, requiring research into design methods and technologies. Cross-disciplinary collaboratives provide an experiential dimension.

The first year of study includes seminar courses in design history and research, which are common to all graduate students in the School of Design. In addition, studio courses involve extensive design work with respect to sustainability, design process, the meaning of artifacts, and critical analysis. Additional course work using three-dimensional software for modeling and fabrication fills out the program.

In the second year students conduct research and develop a thesis project, which is presented in a graduate thesis exhibition or presentation, and is documented in a written thesis report.

Curriculum

- First Year

Design Laboratory I
Function of Form
2D Ideation and Visualization
Design History Seminar
Design Laboratory II
Form of Function
Integrated Design Visualization
Design Research and Proposal

- Second Year

Free Electives
Art History Elective
Thesis: Research and Planning
Thesis: Implementation and Evaluation

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This programme provides students with the knowledge of cutting-edge methodologies, approaches and skills in the emerging field of data science and big data applications, including advanced software development, systems for big data analytics, statistical data analysis data mining, distributed systems, data privacy and security, and data visualization and exploration. Read more
This programme provides students with the knowledge of cutting-edge methodologies, approaches and skills in the emerging field of data science and big data applications, including advanced software development, systems for big data analytics, statistical data analysis data mining, distributed systems, data privacy and security, and data visualization and exploration.

The programme of study culminates in a dissertation, enabling you to bring what you have learnt together in a significant piece of project work.

In summary, the MSc Big Data Science and Technology offers you the opportunity to build your own path of study - from the advanced computing modules, the extended list of optional modules available, as well as the dissertation - so as to match your specific career aspirations in the area of big data and data science.

For more information on the part time version of this course, please view this web-page: http://www.brad.ac.uk/study/courses/info/big-data-science-and-technology-msc-part-time

Why Bradford?

This programme intends to equip graduates with the cutting-edge knowledge and skills to work in the industry as a Data Scientist, Big Data Architect, or Big Data Analyst.

MSc Big Data Science and Technology provides industry with graduates that are ready and able to develop solutions to address challenges for big data analytics and developing big data systems.

Modules

-Software Development
-Big Data Systems and Analytics
-Information Theory and Data Communication
-Security, Privacy and Data Protection
-Mobile Applications
-Statistical Data Analysis
-Data Mining
-Concurrent and Distributed Systems
-Data visualization
-Dissertation

Career support and prospects

The University is committed to helping students develop and enhance employability and this is an integral part of many programmes. Specialist support is available throughout the course from Career and Employability Services including help to find part-time work while studying, placements, vacation work and graduate vacancies. Students are encouraged to access this support at an early stage and to use the extensive resources on the Careers website.

Discussing options with specialist advisers helps to clarify plans through exploring options and refining skills of job-hunting. In most of our programmes there is direct input by Career Development Advisers into the curriculum or through specially arranged workshops.

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Why choose the MSc in Business Analytics?. Do you want to be a professional analyst who understand both the technologies and the business?. Read more

Why choose the MSc in Business Analytics?

  • Do you want to be a professional analyst who understand both the technologies and the business?
  • Do you want to master the skills in making data-driven business decisions?
  • Do you want to learn the practical use of data visualization tools, statistical analysis tools, and big data technologies?

What is business analytics?

Business Analytics is the intersection of management science and machine learning in real world applications.

It offers new potential to improve financial performance, strategic management and operational efficiency.

Business Analytics is an increasingly critical component in preparing organizations to solve 21st-century business challenges and support data driven decision making.

Programme overview

Our MSc Business Analytics programme is a one year, full-time programme consisting of 6 core modules, and 2 elective modules from a choice of 7 elective modules.

The core modules are conducted via lectures, tutorials, and computer laboratory sessions. Students undertake the dissertation project in Business Analytics in collaboration with one of our international industrial partners.

Graduates of the programme will have gained the necessary skills and knowledge in a range of fields, including business operation, database, statistics, informatics, data analytics, machine learning and big data technologies in real-world business contexts.

Applicants for this programme are required to have at least a second class honours in the first division or international equivalent in any discipline, including business and management, and at least 10 credits equivalent value with significant mathematical/statistical content (However, this course is not suitable for students who have previously studied a significant amount of business analytics).

Teaching and Learning

Our learning environment is highly interactive and innovative with student-centred learning activities.

Other than examinations, our students will be assessed via essays writing, practical exercises, group and individual projects, and oral presentations.

The dissertation focuses on developing students’ skills in applying analytic techniques, communicating and solving the data analytics problem.

Career options for this degree

The area of business analytics is growing in financial sectors, customer services, enterprise optimization, and consumer marketing.

When our students graduate, they will be able to:

  • Find a job in the business firms that require the knowledge of big data and advanced analytic techniques.
  • Study the organisations, management, and international external environments.
  • Gain business insights and professional skills in data mining, data visualization, data management, process modeling, predictive and advanced analytics.
  • Develop the ability to optimize the business processes and management practice.
  • Contribute to business and society at large.

What are the potential careers of our graduates?

  • Business intelligence analytics,
  • Marketing analyst
  • Business systems analyst
  • Data scientist
  • Business consultant
  • Solution Architects


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Design for the Digital Age. The program is tailored to practicing designers seeking to enhance their digital skills and leadership potential as well as professionals with relevant design experience who want to enter the field. Read more

Design for the Digital Age

The program is tailored to practicing designers seeking to enhance their digital skills and leadership potential as well as professionals with relevant design experience who want to enter the field. It encompasses the full product development cycle in communication design — from idea conception to prototyping to feedback-based refinements — and familiarizes you with business strategy.

In this one-year, 30-credit curriculum, you develop creative problem-solving strategies to relay and translate messages, information, and ideas. Your full-time course of study is built on four components: instruction in advanced core design competencies, practices and methods courses, external partnerships, and the core studio sequence. Parsons faculty — skilled at bringing together design thinking, aesthetics, and technology—guide you to explore innovative composition and visualization methods, interaction design, typography, and industry best practices.

Industry Ready

You graduate from the program with your own unique, forward-looking aesthetic anchored in professional skills acquired throughout the program, which include entrepreneurship, strategic working methodologies, and contemporary prototyping. You are prepared for digital design work settings, with competence in various industry-standard technologies, including front-end development skills (HTML, CSS, and JavaScript), and experience navigating professional partnerships with teams and clients.

Future Opportunities

Graduates pursue careers in Interaction Design, User Experience (UX) Design, Digital Product Design, and Product Management.

Financial Aid Deadline

All applicants selected for admission into our program are considered for a merit scholarship award that is determined by the strength of their application. Scholarship award notification is communicated at the same time as the admission decision. If you are a U.S. citizen or permanent resident, we encourage you to complete the Free Application for Federal Student Aid (FAFSA), which can be found on the Web at http://www.fafsa.gov. The FAFSA is available each year on October 1. You do not need to wait for an admission decision to apply for federal aid; we recommend submitting by our FAFSA priority deadline of February 1 for fall applicants. (The New School’s federal school code is 002780.)

Creating Collaboratively, from Concept to Product

The specialized course of study provides coding experience and engages the iterative process and a range of collaboration and teamwork strategies. You work from design conception and pitching through post-launch critical analyses of user experience (UX) and interaction (UI). The New York City location enables you to take advantage of the city’s diverse technology and design resources while learning alongside like-minded designers in the Parsons community. You can supplement core courses with a related university-sponsored public program and an elective offered at Parsons or another school or college of The New School, such as a class in psychology, marketing, data visualization, or another field. This program is offered by Parsons' School of Art, Media, and Technology (AMT). You can learn about the AMT community and explore the blog to see what students, faculty, and alumni are doing in NYC and around the world.

You can request more information here: http://www.newschool.edu/m/commdesign?utm_source=find_a_masters&utm_medium=hyperlink_listing&utm_campaign=pm_parsons_grad&utm_term=communication_design



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At the frontier of natural and social science where economic, ethical and political issues converge this programme helps you explore the many dimensions of sustainability and the environment. Read more
At the frontier of natural and social science where economic, ethical and political issues converge this programme helps you explore the many dimensions of sustainability and the environment. From the classroom to the field, our practical teaching provides a strong foundation for you to investigate your specific interests and gain hands-on experience. Led by renowned experts, as part of a multidisciplinary research community, you’ll develop the skills and knowledge to build a successful career.

Key features

-Work side by side with experts from across the Faculty of Science and Engineering and Plymouth Business School – schools which were rated as ‘internationally excellent’ in the latest Research Assessment Exercise (RAE) 2008.
-Carry out an extended dissertation project - designed to benefit those who intend to undertake further study or a research-based career.
-Tailor your studies for the career you want – from environmental agencies and consultancies to local or central government and research – and take your place shaping the pioneering policy and projects of the future.
-Focus on the aspects of sustainable environmental management that you feel most strongly about, with an individual research project and accompanying dissertation.
-Benefit from our local, national and international sector connections as part of a respected and active research community that includes groups such as the Marine Institute – the first and largest of its kind in the UK – and the Centre for Sustainable Transport.
-Add value to your qualification by studying on a programme accredited by the Institute of Environmental Management and Assessment (IEMA) – the benchmark for high-quality programmes recognised internationally by learners and employers.
-Balance your work commitments and further education with the opportunity to study part time for a masters-level qualification.

Course details

Exploring topics that span the natural and social sciences, you’ll gain vital insight into the whole spectrum of environmental management issues – from law and ethics to impact assessments and data analysis, river basin plans to marine regulations. We’ve designed the programme flexibly to equip you with an in-depth understanding of the essential theories, as well as practical fieldwork and industry experience.

During the first two terms of this one-year programme, you’ll study a range of core and optional taught modules – from international environmental policymaking to options like climate change: science and policy or economics and the environment. In the final term you’ll complete an independent dissertation project.

Throughout your studies, we’ll support you in gaining the research and professional skills to help you get the most from the programme – and launch a successful career.

Core modules
-GEES521 MRes Dissertation

Optional modules
-MAR515 Management of Coastal Environments
-MATH500 Big Data and Social Network Visualization
-ENVS5003 Ecological Survey Evaluation and Mitigation
-GEES515 Professional Practice in the Environmental Sector
-GEES516 Science, Society and Environmental Governance
-GEES519 Environmental Knowledge: From Field to Stakeholder
-GEOL5006 Sustainable Geoscience: Research and Communication
-CHM5002 Analytical Chemistry Principles

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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