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.
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.
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.
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
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.
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.
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.
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:
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.
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
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.
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
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.
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.
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.
Accredited by BCS, The Chartered Institute for IT for the purposes of fully meeting the further learning academic requirement for registration as a Chartered IT Professional, and on behalf of the Science Council for the purposes of partially meeting the academic requirement for registration as a Chartered Scientist and a Chartered Engineer.
MSc Data Science students can participate in our professional internships programme, which is supported by the Professional Liaison Unit. This will enable you to undertake your MSc project in an industrial or research internship over an extended period compared to regular projects. For example, the individual project can be carried out as a 6-month internship in one of the companies with which City has a long-standing relationship and history of collaboration in the big data and data science area.
Examples of company placements internships taken by our Data Science students in the recent past include: Google, SagePay, Reward, Black Swan.
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:
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.
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.
Career & Skills Development Service at City, University of London
After successful completion of the course you may wish to consider a PhD degree in Computing.
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.
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).
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.
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:
What are the potential careers of our graduates?
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.
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.
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.)
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
Gartner estimated that the total number of IoT devices will hit 26 billion units by 2020. Our MSc Internet of Things course is a postgraduate course focusing on teaching advanced IoT topics. As a student you will develop practical skills through a comprehensive understanding of fundamental knowledge and hands-on experience of IoT technologies within industry and academia.
Cisco forecasted that the IoT will become a £13 trillion market – approximately six times the growth rate of the overall information technology market. Choosing our Internet of Things course will enable you to gain the essential knowledge and skills to be placed in the internet technologies and telecommunications industries.
In the programme, unique and challenging modules are introduced for example Mobile networks and smartphone applications, Data mining and visualization, in addition to Ethics for IT professionals and Object oriented analysis and design that provide the basics for Internet of Things (IoT).
Advanced wireless networking technologies and Internet of Things are introduced to in depth knowledge of the field. In addition, two modules which focus on research and the latest trends in the field, namely, Research design and methods and Emerging topics in smart networks, help to define and complete the research project on time.
Modules you will study focus on:
All modules respect the themes of Internet of Things.
You will also be introduced to unique and challenging modules, for example:
Optional modules include:
Two of the modules you will study focus on research and the latest trends in the field, namely:
These modules will help to define and complete your research project on time.
Teaching & Assessment
Teaching takes the form of:
Our assessment methodology is influenced by the learning outcomes to be tested and employs a range of methods including:
Jobs
You will be prepared to enter research and developmental positions in academia. Other roles you will be able to apply for include:
Further Study
Successful completion of our course prepares you for advanced research studies in related technology areas. You will also have the priority to be admitted to the MPhil/PhD degree courses.
Remote surgery, driverless cars and smooth mobile HD streaming could all become a reality thanks to pioneering research taking place at UWS.
UWS computing researchers Jose Alcaraz-Calero and Qi Wang are the technical leads on the SELFNET project, which is developing a ‘self-healing’ mobile network. The new network is 1,000 times faster than 4G, delivering dramatic improvements to quality of user experience, reliability and security – and unlocking a wealth of new online opportunities.
”SELFNET will allow 5G networks to make possible things that would have been considered science fiction just a few years ago.” Dr. Alcaraz-Calero
As part of this course, you will hear from PhD students who are working on the 5G mobile project, and the course content will be updated to reflect the findings of this work.
