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Masters Degrees (Information Visualization)

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With City’s MSc in Information systems and technology you will develop the skills to manage an organisation's IT infrastructure. This postgraduate Information Systems and Technology course is for students who have a keen interest in both information system development and information management. Read more
With City’s MSc in Information systems and technology you will develop the skills to manage an organisation's IT infrastructure.

Who is it for?

This postgraduate Information Systems and Technology course is for students who have a keen interest in both information system development and information management. Students are either in the early stages of their career or have significant work experience in the area and wish to formalise their knowledge.

Students will have curiosity about information and knowledge and will want to learn about managing them in organisations, together with the requisite design and technical skills to meet business requirements.

Objectives

Information systems are a key part of an organisation's IT infrastructure. IT professionals who can manage a business's information resources, and understand the technologies and systems that enable this are key to a modern enterprise's success.

Our postgraduate Information Systems and Technology degree will equip you with the skills to develop and maintain information systems that align with the strategic needs of any organisation.

Rather than focusing on technical issues only, the course combines technological fundamentals with a systematic understanding of IT's broader business contexts, including human and organisational factors. The course exploits City's research expertise in both computing and information management to produce effective professionals with a broad understanding of IT underpinned by a firm grasp of key technical concerns.

Placements

The School of Mathematics, Computer Science& Engineering has been delivering placements in the IT industry for over 20 years.

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, Microsoft Dynamics, SAP etc you will have access to an array of tools to support your learning.

Teaching and learning

The teaching and learning methods we use mean that your specialist knowledge and autonomy increase as you progress through each module. Active researchers and professionals guide your progress in the areas of information systems and management, project management and business processes.

Taught modules are delivered through a series of lectures together with either tutorials or laboratory sessions. 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 or case studies. Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.

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.

Assessment

We expect you to study independently and complete coursework for each module. Modules are assessed through a combination of written examinations, coursework, group work and presentations.

The individual project is a substantial task. It is your opportunity to develop an autonomous research-related topic under the supervision of an academic member of staff. This is the moment when you can apply your learning to solve a real-world information system or information management problem. 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.

Students successfully completing eight modules and the dissertation will be awarded 180 credits and a masters level qualification. Alternatively, students who do not complete the dissertation but have successfully completed eight modules will be awarded 120 credits and a postgraduate diploma. Successful completion of four modules (60 credits) will lead to the award of a postgraduate certificate.

Modules

The postgraduate Information Systems and Technology programme is made up of five core modules, three elective modules and a final project. All the electives are studied in the second term. You will take core and elective modules in three main streams: information, systems and technology. The third term is reserved for the project.

Modules include hands-on lab-based tutorials, group work seminars and presentations. We teach technical skills in SQL, JavaScript and PhP, as well as design skills using UML. You can pursue a practical MSc project in an application area of your choice.

With respect to hours please consult the SMCSE programmes office.

Core Modules
-Systems Specification INM312 (15 credits)
-Databases INM343 (15 credits)
-Information and Knowledge Management INM351 (15 credits)
-Research Methods and Professional Issues INM373 (15 credits)
-Information Architecture INM401 (15 credits)

Elective Modules - you may choose three elective modules from the following:
-Information Retrieval INM305 (15 credits)
-Web Applications Development INM316 (15 credits)
-Business Engineering with ERP Solutions INM342 (15 credits)
-Information Law and Policy INM361 (15 credits)
-Project Management INM372 (15 credits)
-Data Visualization INM402 (15 credits) *
-Libraries and publishing in the information society INM380 (15 credits)
-Information Organisation INM303 (15 credits) +
-Business Intelligence and Analytics INM451 (15 credits)

+ Students who take INM303 must also take INM305 as an option.
* Students may only take one of INM402 or INM451 as an option.

Career prospects

City’s Information Systems and Technology MSc graduates are prepared for employment in information systems management roles within large and small organisations including banks, consultancies, the pharmaceutical and IT industries, central and local government and the education and health sectors.

Previous graduates have secured employment in some of the most prestigious companies in the world including Merrill Lynch, Deutsche Bank, Virgin Atlantic, Barclays Capital and the Royal Bank of Scotland.

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The increasing complexity of our society demands for specialists who can collect, manage, analyse and present spatial data using state-of-the-art methods and tools. Read more

MSc Geo-Information Science

The increasing complexity of our society demands for specialists who can collect, manage, analyse and present spatial data using state-of-the-art methods and tools. At Wageningen University we offer a unique, top-quality programme that blends geo-information science methods, technologies and applications within environmental and life sciences for a changing world. Our Geo-information Science graduates usually have a job waiting for them on graduation.

[[Programme summary]
Geo-information has become increasingly important to society as the number of environmental issues continue to rise: Geo-information provides the data we need to manage both the natural and social environment. It is indispensable for a broad range of domains like spatial planning, water management, nature conservation, environment management, agriculture, energy supply, disaster management and traffic and safety. The MSc GIS programme at Wageningen University offers you a blend of geo-information science methods, technologies and applications. The combined use of earth observation techniques (Remote Sensing) and Geographic Information Systems for problem-solving within the environmental and social disciplines is a unique feature of the Wageningen Approach. During your study, you take courses on the acquisition, storage, analysis and visualisation of spatial data. You learn to recognise, describe and analyse problems in relevant environmental application fields; this includes training in the development of prototypes. You also learn about the technical and organisational role of geo-information in institutes and companies: how to communicate well, keep abreast of GI scientific and technical developments, and how to apply these developments in specific fields. Depending on your background, research topics and previous education, you can also choose relevant courses in application domains or ICT.

Specialisations

The Geo-Information Science programme is an intensive programme offering students opportunities to specialise by taking advanced courses in GIS and/or Remote Sensing, and by selecting courses in a range of application fields or geo-information technology. Furthermore, you develop your GIS profile by completing a Master’s research thesis in one of the following research fields:
• sensing and measuring
• modelling and visualization
• integrated land monitoring
• human-space interactions
• empowering and engaging communities
Your choice of internship location is another factor in developing your profile and specialisation.

Your future career

Graduates in Geo-Information Science have excellent career prospects; most have job offers before they graduate. Many of our graduates work in research, either in PhD programmes or for research institutes all over the world; Wageningen UR, including Alterra, has the largest group of GI-scientists in the Netherlands. Many others are employed as technical specialists, consultants or project leaders for global companies like Royal Haskoning, Arcadis and Grontmij. And lastly, others work for local or central government agencies and NGOs, including environmental assessment programmes. Would you like to generate and use geo-information to solve global problems like flooding, planning, or the migration of wild animals? Or do you want to provide geo-information to the public or government? Then join the two-year Geo-information Science Master programme at Wageningen University. You have a Bachelor degree in the field of environmental sciences, geography and planning, landscape architecture, food and agricultural sciences, (geo)- information sciences or even social sciences.

Alumnus Frank Salet.
During his career, Frank worked within fields where the use of GIS is unique, challenging or still developing. After a few GIS positions at mostly commercial companies, he is now working at an NGO in Nigeria on the eradication of polio. For the project he has temporarily moved to Nigeria to set up the GIS work, together with a team of 20 Nigerian GIS specialists. He is now working in a multicultural environment just like during his master in Wageningen. Frank is very positive about the connection between the master and his professional career: “All courses within the master programme have formed the tools that I still use for each job I take on.”

Related programmes:
MSc Geographical Information Management and Applications
MSc Forest and Nature Conservation
MSc Landscape Architecture and Planning
MSc Environmental Sciences
MSc Biosystems Engineering.

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Spatial data play an increasingly important role in many areas of our lives. environmental protection, forecasting, agriculture, and local and regional planning. Read more
Spatial data play an increasingly important role in many areas of our lives: environmental protection, forecasting, agriculture, and local and regional planning. Understanding Geographical Information Systems and GI science is essential for effective management and analysis of spatial data.

Core
• Introduction to GIS
• Spatial Information Science
• Earth Observation and Remote Sensing
• GIS Research Methods Field Trip
• Dissertation tutorial
• Geographical Visualization
• Programming for Spatial Scientists
• Plus a 60 credit master’s dissertation

We recognise the need for challenging and diverse methods of assessment. Our methods vary from traditional examinations, individual oral presentations, reports, web pages, research proposals, literature reviews and posters. We also include an amount of field-based teaching and computer practical sessions in our courses. As well as being taught subject knowledge, you will also receive training on how to plan, develop and execute a programme of individual research. We feel that the development of group skills is very important and a number of pieces of coursework involve a team of people. Coursework feedback is given
promptly and in considerable detail, enabling you to improve continuously.

• The MSc in Geographical Information Science at the University of Leicester is the longest running MSc in GIS in England and offers comprehensive training in GI Science and Systems.
• The MSc in GIS has been recently been accredited by the Royal Institution of Chartered Surveyors (RICS).
• The course is overseen by an employer panel of representatives from industry, government, research and environmental agencies in order to maintain the relevancy of the course content and direction.

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Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers. Read more

Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers.

Rooted in the established research strengths of the School of Computing, the programme will introduce topics like systems programming and algorithms before allowing you to specialise through your choice of modules.

You could look at emerging approaches to human interaction with computational systems, novel architectures such as clouds, or the rigorous engineering needed to develop cutting-edge applications such as large-scale data mining and social networks.

Building on your existing knowledge of computer science, you’ll develop the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

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

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

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as cloud computing, image analysis, machine learning, semantic technologies and developing mobile apps.

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

Want to find out more about your modules?

Take a look at the Advanced Computer Science module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Foundations of Modelling and Rendering 15 credits
  • Games Engines and Workflow 15 credits
  • Geometric Processing 15 credits
  • High-Performance Graphics 15 credits
  • Animation and Simulation 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

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

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

Assessment

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

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • iPad interaction for wall-sized displays
  • Modelling the effects of feature-based attention in the visual cortex
  • Relevance and trust in social computing for decision making
  • Energy-efficient cloud computing
  • Smart personal assistant - Ontology-enriched access to digital repositories

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

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science. Read more

Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as specialist modules in advanced distributed systems – especially cloud techniques, technologies and applications.

Building on your existing knowledge of computer science, you’ll also choose from optional modules in topics across computer science. You could look at emerging approaches to human interaction with computational systems, data mining and functional programming among others.

The programme will give you the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

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

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

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming. Throughout the year you’ll also take modules developing your understanding of cloud computing itself, from designing the high-level framework of a distributed system to big data and the “internet of things”.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, machine learning, semantic technologies and developing mobile apps.

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

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Cloud Computing) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Cloud Computing 15 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

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

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

Assessment

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

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science (Cloud Computing) students have included:

  • Intelligent services to support sensemaking
  • Google cloud data analysis
  • Hadoop for large image management
  • Evaluating web service agreement in a cloud environment

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

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science. Read more

Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics, or broaden your approach with topics like cloud computing.

As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics which is at the forefront of big data research.

Specialist facilities

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

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

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, semantic technologies and developing mobile apps.

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

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Data Analytics) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • Machine Learning 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

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

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

Assessment

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

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • Text mining of e-health patient records
  • Java-based visualization on ultra-high resolution displays
  • Data mining of sports performance data
  • Contour topology
  • Efficient computation for simulating tumour growths

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

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Columbia University’s new Master of Science in Applied Analytics empowers you to assess the application of an organization’s data and analytics. Read more
Columbia University’s new Master of Science in Applied Analytics empowers you to assess the application of an organization’s data and analytics. You will learn how to define and frame analytical problems, how to decide which data are collected and what analyses should be performed, and how to communicate and work with analysts on solutions that are technically sound as well as valuable to the organization. Available part-time and full-time, the program is anchored by three week-long courses on Columbia’s campus in New York City that feature networking, group exercises, and guest lecturers. Between these courses, you will complete additional coursework on campus or online through a networked learning platform. For your final capstone project, you will apply your knowledge to develop a real-world analytics project sponsored by a leading organization.

Program Structure

The program consists of required courses in two core areas. The Leadership, Management, and Communication Core develops an enterprise-wide perspective on data and the knowledge, skills, and abilities needed to inspire, create, and foster an analytical culture within an organization. The Applied Analytics Core develops a broad understanding of the frameworks for the use of data to inform real-life business problems from data collection to application in decision-making. This core introduces you to the methods and range of tools and systems that organizations use to conceptualize, collect, manage, and analyze data to produce information to make it actionable across their enterprise.
For your elective study, you will align the foundational skills you've developed in the two core areas with three courses you choose that are pertinent to your academic and professional goals. Elective courses in a wide range of subjects, including business, finance, marketing, information visualization, collaboration, communication, and negotiation, let you obtain in-depth knowledge in a particular industry or functional area within an organization.
Completing your Integrated Capstone Project, you will apply what you have learned in the two core components to a real-world analytics project sponsored by a leading organization.
Students requiring an F1 visa must enroll full-time (12 credits) and study on campus. Students on an F1 visa are permitted to complete no more than one online class each semester. Students not on an F1 visa have the flexibility to enroll in courses online or on-campus. For these students, if desired, 68% of the coursework can be completed online. The program offers one core course each semester in a block week format at a Columbia University location in New York City which reduces the amount of time on campus for students located outside the New York metropolitan area.

For more information on the program structure please visit the website: http://sps.columbia.edu/applied-analytics/master-of-science-in-applied-analytics/curriculum

Funding and Financial Resources

We want to make sure that the cost of your continuing education and professional studies do not stand in the way of your goals.
Most students at the School of Professional Studies use a combination of savings, scholarships, loans, outside grants, sponsors, or employer tuition benefits to cover the cost of attendance. However you choose to finance your education, consider it an investment in your future, and know that we, in conjunction with the Office of Student Financial Planning, are here to help and advise you along the way.

For more information on available funding please visit the website: http://sps.columbia.edu/applied-analytics/master-of-science-in-applied-analytics/tuition-and-financing/financial-resources

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Drive growth, productivity, and societal impact through information management and collaboration. Columbia University’s Master of Science in Information and Knowledge Strategy (IKNS) is for individuals who are invested in the strategic potential of information management and collaboration. Read more
Drive growth, productivity, and societal impact through information management and collaboration.

Columbia University’s Master of Science in Information and Knowledge Strategy (IKNS) is for individuals who are invested in the strategic potential of information management and collaboration. Graduates go on to become knowledge and analytics leaders, consultants, and entrepreneurs of digital products.

Program Benefits

Develop
essential skills in strategy, business analytics, findability, law, entrepreneurship, and change management to plan and lead knowledge and information products and services, improve collaboration and networks, and create innovative knowledge products.

Shape
your career as an in-house knowledge practitioner, consultant, or knowledge product entrepreneur in nearly any industry, including financial services, advertising, education, logistics, healthcare, international development, manufacturing, and technology.

Specialize
your study by choosing electives in social media/mass collaboration, information visualization, change leadership, or knowledge-driven digital product innovation.

Balance
your career and academic life over 16 months with online coursework once a weeknight per course, virtual collaboration and discussions, and three five-day residencies on Columbia’s campus in New York City.

Connect
with faculty who have held leadership positions in information, knowledge, IT, or law at organizations such as Accenture, Pfizer, Fidelity Investments, NASA, Bain & Company, and The World Bank.

Apply
your skills and knowledge through a group capstone project for a leading global for-profit or nonprofit business, such as Motorola Solutions, ConocoPhillips, HSBC, Women’s World Banking, German Aerospace Center, or the World Wildlife Fund.

Join
an elite Ivy League network of your global cohort and more than 250 alumni who have advanced in their careers or responsibilities with their IKNS degree at places like ADP, Hilton Hotels, Pfizer, Publicis, United Nations, USAID, and Thomson Reuters.

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The graduate program in Digital Futures responds to the increasingly important and sophisticated role of digital technology as a catalyst for change. Read more
The graduate program in Digital Futures responds to the increasingly important and sophisticated role of digital technology as a catalyst for change.

Digital Futures has an international student cohort and faculty. The program features collaborative overseas eGlobal courses with world-wide educational and industry partners. A global perspective is key to securing our graduates’ futures in the eclectic international creative digital industries, encompassing design, arts, creative services, entertainment, media and cultural industries. The Digital Futures program is offered in partnership with the Canadian Film Centre (CFC) Media Lab.

The Digital Futures student-centred learning approach applies to both research and practice. The curriculum ensures that you gain core digital knowledge and skills as you explore your specific areas of interest through electives, industry internships, residencies and independent study.

The program focuses on practice-based learning and prototyping, with an enterprise component and supporting thesis research. Industry partnerships help students to build a career runway in advance of graduating. You are encouraged to work with industry partners in internships which lead to mentorship for your thesis research.

WHO SHOULD APPLY?

You should have a background in design, technology, culture and/or enterprise as demonstrated by an undergraduate degree and relevant work experience. Our students are designers and artists, filmmakers, architects, journalists and media specialists, scientists, engineers and business people. This diversity drives peer learning and collaboration across disciplines in the program.

THE MASTER’S DEGREE IN DIGITAL FUTURES

The master's in Digital Futures is a two-year full-time program. In the program, you will develop practice-based and scholarly research in technologically advanced design, art and media through the following:

Critical thinking
Research and practice
Business and innovation studies
Computing and emerging digital methodologies

This is a full-time, 8-credit program comprising:

Foundational courses in computation, business creation, innovation and leadership
Core courses in digital methods, research, theory and practice
Intensive digital project and prototyping courses
Individual research and creation overseen by a principal advisor and supervisory committee
Summer internship and/or study abroad
Elective choices
Creative digital thesis project and supporting paper (MFA/MDes) or a written thesis and supporting creative project (MA)

Students declare their intention to pursue the Master of Design (MDes), Master of Fine Arts (MFA) or Master of Arts (MA) at the time of application. The outcomes of the chosen degree are distinctive. The MDes and MFA focus on practice-based research creation with a supporting thesis. The MA flips that focus, with an emphasis on a scholarly research thesis and a supporting creative project.

ELECTIVE CHOICES

New elective courses are continuously created in response to trends and emerging technologies. These cutting-edge courses cover theory and practice in design, art, media, technology and enterprise. Some examples include:

Body Centric Technologies
Dialogues in Feminism and Technology
Digital Games
Information Visualization
IP: Getting Value from Your Creativity
Web + Mobile System Design
Transmedia Storytelling
Ubiquitous Computing
Affect and Emotion in Practic
Making It Real
From Data to Perception
Special Topic: Family Camera at the ROM

WHERE MIGHT YOUR GRADUATE DEGREE IN THE DIGITAL FUTURES PROGRAM LEAD YOU?

As a Digital Futures graduate, you’ll be qualified to work in positions such as:

App, web, and games designers and developers
Digital project leaders
Cultural industry producers
Managers and coordinators between art and design departments and IT
Creators and developers of your own start-ups
Film, television and digital transmedia producers
Digital strategists and educators

Graduates of the Digital Futures program will be poised to play leadership roles in research and development in the media, arts, technology, entertainment and education sectors.

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Why choose this MBA?. The Master of Business Administration (MBA) is a two-year part-time program designed especially for industry professionals wanting to advance their careers. Read more
Why choose this MBA?

The Master of Business Administration (MBA) is a two-year part-time program designed especially for industry professionals wanting to advance their careers. To accommodate work schedules, courses take place once a month for 4 days over an extended weekend (Thu-Sun). The innovative course structure consists of pre-module, core module, and post-module periods enabling you to prepare before and after the 2-4 days on campus via e-learning. All classes are conducted as interactive seminars in a stimulating learning environment, guaranteeing a high degree of collaboration and exchange with world-renowned faculty. Designed to support and inspire students in their learning process, the MBA courses employ a variety of resources and formats including books, online articles, case studies, and real-life examples taken from the industry. The program averages 18 months for completion, however study periods can be adjusted to fit your personal schedule, giving you maximum flexibility to study alongside your career. You will not only build a solid foundation in general management skills, but also have the opportunity to specialize in a specific field or industry. MODUL University Vienna has established research competencies in the fields of New Media, Public Governance, Sustainable Development, and Tourism and Hotel Development with a myriad of scientific achievements in basic and applied research. Specialized in these fields of expertise, the MBA faculty is comprised of renowned professors and experts who ensure an outstanding and thematically focused education. Courses are taught in English by an internationally experienced faculty. Furthermore, a 60% international student body provides a multicultural learning environment as well as manifold networking opportunities.
Pursuing a Master of Business Administration with MODUL University Vienna encourages out-of-the-box thinking and challenging existing limits and thought patterns and equips you with the skills to take your career to the next level.
MODUL University Vienna is an international private university in Austria owned by the Vienna Chamber of Commerce and Industry, the largest provider of private education in Austria. All programs are accredited by the Agency for Quality Assurance and Accreditation Austria.

Program Focus

The MBA concentrates on strategic analysis and planning, problem-solving, interdisciplinary skills, value-based management and critical thinking. It builds these skills upon a solid foundation of core business disciplines including human resource management, organizational behavior, accounting and finance, marketing and operations, and innovation and entrepreneurship. MBA students opting for a Major in New Media and Information Management become equipped with skills in Media Asset Management and Utilization, Big Data and Decision Support, Visualization Techniques for Management, Business Planning and Intellectual Property Rights, Telecommunication and are updates on the latest trends in New Media and Human-Computer Interaction.

The ideal MBA Student

Students enrolled in the MBA with a Major in New Media and Information Management come from all over the world and have different professional backgrounds. The industry professionals enrolling in an MBA study program are highly motivated, hold an academic degree (Bachelor or other comparable undergraduate degree), have a minimum of three years of professional experience and are fluent in English. For more details on the curriculum, the program’s faculty, and the admission criteria visit http://www.modul.ac.at, contact the MBA Program Manager Dr. Verena Peer or the Admissions Office ().

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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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This Joint Degree between HEC Paris and Ecole Polytechnique will equip students with both the technical skills and the strategic mindset to lead successfully any business career requiring a strong expertise in Big Data. Read more
This Joint Degree between HEC Paris and Ecole Polytechnique will equip students with both the technical skills and the strategic mindset to lead successfully any business career requiring a strong expertise in Big Data.

STUDY IN TWO GLOBALLY-RECOGNIZED INSTITUTIONS

Ecole Polytechnique (https://www.polytechnique.edu/en) and HEC Paris are both world leading academic institutions, renowned for the quality of their degrees, faculties and research (see HEC rankings http://www.hec.edu/Masters-programs/About/Rankings).

Their association within this Joint Degree represents the best Business/Engineering combination Europe could possibly offer, with extraordinary added value for the students who will follow this program in Big Data and Business.

LEAD THE DIGITAL TRANSFORMATION OF THE ECONOMY

Big data marks the beginning of a major transformation of the digital economy, which will significantly impact all industries. There are three main challenges to face:

> Technological: dealing with the explosion of data by managing the spread of vast amounts of information that is often very disorganized (IP addresses, fingerprinting, website logs, static web or warehouse data, social media, etc.)
> Scientific: replacing mass data with knowledge,i.e. developing the expertise that makes it possible to structure information, even out of tons of vague or corrupt data.
> Economic: managing data both to control risks and benefit from the new opportunities they offer. On the one hand, it is absolutely vital to be able to control the flow of information, anticipate data leaks, keep the information secure and ensure privacy. On the other hand, it is also essential to come up with solutions capable of transforming this flow of data into economic results and, at the same time, discover new sources of value from the data.

ACQUIRE THE SKILLS TO MAKE A DIFFERENCE IN TOMORROW’S DIGITAL WORLD

Exploiting this vast amount of data requires the following:

> A mastery of the sophisticated mathematical techniques needed to extract the relevant information.
> An advanced understanding of the fields where this knowledge can be applied in order to be in a position to interpret the analysis results and make strategic decisions.
> A strong business mindset and an even stronger strategic expertise, to be able to fully benefit from the new opportunities involved with Big Data problematics and develop business solutions accordingly.
> The ability to suggest and then decide on the choice of IT structures, the ability to follow major changes in IT systems, etc.

Therefore the program has three objectives:

> To train students in data sciences which combines mathematic modelling, statistics, IT and visualization to convert masses of information into knowledge.
> To give students the tools to understand the newest data distributing structures and large scale calculations to ease decision-making and guide them in their choices.
> To form data ‘managers’ capable of exploiting the results from analysis to make strategic decisions at the heart of our changeable businesses.

MAKE THE MOST OF WORLDWIDE NETWORKING AND ALUMNI POWER

Students will benefit not only from the close ties that HEC Paris has developed with the business world but also those of Ecole Polytechnique, through various networking events, conferences and career fairs.

The HEC Alumni network alone, consists of more than 52,300 members in 127 countries.

Program Details

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Program-Details

Campuses

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Campuses

CAREERS

As “Big Data” affects all kinds of companies and all sectors, students will have a very large range of career options upon graduation, from consulting firms to digital start-ups, not to mention very large multi-national companies.
In fact, as can be seen in all areas of cutting-edge innovation, there is a growing demand for high level managers who can combine strong technical skill with business know-how.

This is especially true when it comes to Big Data topics, and students graduating from data science and Big Data programs are therefore highly sought after on the job market.

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Careers

FAQs

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/FAQ

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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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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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What is the Master of Digital Humanities all about?. The Master of Science in Digital Humanities helps graduates from . Read more

What is the Master of Digital Humanities all about?

The Master of Science in Digital Humanities helps graduates from Humanities, Social and Behavioral Sciences programmes to develop digital competencies that will allow them to add digital dimensions to their own domain expertise. It aims to explicitly link these competencies to research questions, case studies and applications related to the domain expertise of the students.

Graduates of this programme will be able to bring their own domain expertise to a significantly higher level of functionality, using digital tools and techniques. Building both on the expertise they obtained from the programme and their prior expertise in Humanities, Social or Behavioral Sciences, graduates will be well placed to open many new digital applications to a much wider community. Moreover, those who wish to move to a professional profile involving more advanced digital competencies, are well prepared to do so.

Structure

The programme is organized around a number of clusters of course units. The central clusters are the Application Domains cluster and the Tools for the Digital World cluster. Supporting clusters are the Introductory Digitization Components cluster, the Advanced Digitization Components cluster and the Management Component. The heart of the research activities is situated in the Master’s thesis.

International and multidisciplinary

The Master’s Programme is conceived as a one year, international and multidisciplinary advanced master programme (master-after-master). The programme is unique in Flanders and one of only a few in Europe. The programme is firmly framed in an explicit collaboration between the Faculty of Arts, the Faculty of Psychology and Educational Sciences, the Faculty of Social Sciences and the Faculty of Sciences - Department of Computer Science. As such, it is supported by experts in Digital Humanities applications, who supply research expertise for the programme, as well as by experts in digital techniques and tools, who provide a sound technical basis for the students.

Objectives

Digitization affects in many ways how future scientists in Humanities and Behavioural Sciences will conduct their research. Also, graduates from Humanities and Behavioural Sciences programs enter a professional world in which digitization becomes the standard, be it in publishing, arts, libraries, teaching and many others.

The Master of Science in Digital Humanities program aims to prepare graduates from Humanities and Behavioural Sciences programs for these challenges. It aims to help such graduates to develop digital competencies that will allow them to add digital dimensions to their own domain expertise. It aims to explicitly link this knowledge and these competencies to case studies and applications related to the domain expertise of the students. It will train them to master information structures and functionalities of data, programming structures and technique to produce scripts for digital applications, tools for improving access and interactive use of data and the development of new digital applications. It will train them how to manage projects related to digitization and introduce them to emerging new digital technologies and their applications.

As an advanced master program (master-after master), it is assumed that the students entering this program have already achieved the general academic competencies defined for any master's program. Nevertheless, it is also within the aims of the program to further strengthen these competencies, within the specific context that Digital Humanities offers.

More specifically, graduates understand the basics of Digital Humanities, databases and query languages, scripting languages, the role of IT in management and of some of the emerging technologies in Digital Humanities. They are able to formulate research goals, determine trajectories that achieve these goals, collect and select information relevant to achieve the research goals and interpret collected information on the basis of a critical research attitude. They are able to communicate scientifically. They are able to model a database and use SQL, to use a scripting language, to apply tools for Digital Humanities and to study applications in Digital Humanities. They have the attitudes of valuing and fostering creative, critical and independent thinking, of applying an interdisciplinary and participative approach in innovative development and of striving towards opening the digital world to a broader society.

Career perspectives

Academically, researchers in the Humanities, Social or Behavioral Science are confronted with the need to apply digital tools to facilitate and enhance their research. The program enables graduates to enhance their research in the Humanities, Social or Behavioral Sciences through non-trivial uses of digital tools and techniques. This may include modeling and querying databases, accessing data, interconnecting andquerying web resources, extending tools with scripts to provide extra functionality, text-encoding and e-publishing, mining repositories, data visualization, analyzing social networks, adopting, adapting and enhancing e-learning environments, improvingusability of human-computer interaction. As such, graduates are very well placed to take on the challenges that novel research positions require.

Professionally, graduates of the Humanities, Social of Behavioral Sciences enter professional environments where connecting the company’s business with digital tools and techniques has become standard. Here as well, the program enables its graduates to put to use non-trivial digital techniques in their professional occupations, including e-media, publishing, arts, history, culture, music, libraries, e-education or interactions for end-user applications. Thus, graduates who want to pursue a career in the usual sectors for graduates of the Humanities, Social or Behavioral Sciences will be much better prepared to cope with the digital techniques that are currently applied there.

More generally, graduates of this program provide society with professionals and researchers who are able to bring their own domain expertise to a higher level of functionality, using digital tools and techniques. Building both on the expertise they obtained from the program and their prior expertise in Humanities, Social or Behavioral Sciences, are well placed to take part in opening the digital world to a larger community.

Graduates of this program who wish to move to a job profile involving more advanced digital competencies, are prepared to do so and will help to close to gap in an IT-focused labor market. This will require extra training at the company and aims at positions such as project analysts, project managers, service managers.



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