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Visual Analytics MSc by Research

Middlesex University
In London (Grossbritannien)

zzgl. MwSt.
Originalpreis in GBP:
£ 4.052

Wichtige informationen

Tipologie Master
Beginn London (Grossbritannien)
Dauer 1 Year
Beginn September 2018
  • Master
  • London (Grossbritannien)
  • Dauer:
    1 Year
  • Beginn:
    September 2018

Visual analytics is a key requirement of the early 21st century. As our human activity generates rapidly increasing amounts of new data every day, there is an urgent need to make sense of it and a huge potential to elicit new knowledge and insights from it.

World events and phenomena like climate change, 9/11, global finance systems and public health are data rich and increasingly complex. Visual analytics turns large and complex, data sets into interactive visualisations that can prompt visceral comprehension and moments of insight that are compelling and offer an unparalleled richness of possibility for data analysts. In this uncharted world of boundless data, visual analytics is providing our new maps and new ways of navigating. Data analytics is recognised as a key trend that will have a major impact on the IT and Communications industry in the next 5...

Wichtige informationen
Welche Ziele verfolgt der Kurs?

Voraussetzungen: Interviews, entrance tests, portfolios and auditions Entry onto this course does not require an interview, portfolio or audition.


Wo und wann

Beginn Lage
The Burroughs, NW4 4BT, London, Grossbritannien
Karte ansehen
Beginn Sep-2018
The Burroughs, NW4 4BT, London, Grossbritannien
Karte ansehen

Was lernen Sie in diesem Kurs?

Data analysis
Human Perception
Information Visualisation
System Modelling
Operational Issues


This unique, research based course doesn’t follow the traditional model of lectures, examinations and thesis writing. We will induct you into our community through an ongoing series of workshops and then help you to build a project that meets your current needs and future plans. We’ll also tailor learning experiences for you to fill identified gaps in your knowledge and to prepare you for novel application areas. We’d expect your project to be greeted with interest in the academic sector and to give you the leverage that you need in the jobs market place. The normal study period with us will be 12 months full time or 24 months part time. We do not offer this course by distance learning as we need you to be fully engaged with our community and working actively with your peer group; visual analytics is moving fast and we intend to stay at the leading edge.

Our workshop schedule includes:

Logic and Sense making: how do we reason about the world, and how do we make sense of the information that is presented to us?

Human Perception and Information Visualisation: how does human visual perception work, and how do we navigate, interact and evaluate in domains that present information visually. What modalities can we use to represent information about entities and their relationships (e.g. temporal, locative, etc), and how do these modalities impact on human processes?

HCI and System Modelling: how do we apply the principles of user and activity centred design to VA systems? How do we design representations that support decision making? How do we determine what relationships in the data sets should be represented? How do we design the interactions that simplify analytical procedures, evidence collation and conclusion formation?

Visual Analytics System Architecture: how do we design systems architectures that bring together complex data sets so that they can be visualised to support intended applications? This could include areas such as data integrity, data granularity and data provenance.

Operational Issues and e Discovery: how do VA systems integrate into real working practices, with particular reference to environments where they will be used for e Discovery such as complex documentation sets?

Data Analysis and Knowledge Engineering: advanced techniques for analysing data sets and extracting knowledge.

In addition, there will be a series of supporting seminars to cover required areas of research methods, mathematical skills and programming.

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