Data Visualisation (MASc/PGDip) (2023 Entry)
Explore our Data Visualisation taught Master's degree.
Warwick’s Data Visualisation MASc focuses on the skills and knowledge needed to design, develop, deploy and interpret data visualisations. Open up diverse career opportunities by developing a Data Visualisation portfolio through studies spanning the Sciences, Arts, Humanities and Social Sciences at the Centre for Interdisciplinary Methodologies.
The MASc in Data Visualisation is an innovative, interdisciplinary course which enables students to acquire crucial knowledge and skills in visualisation as a methodology for data-intensive research, communication and engagement. Students will be trained in concepts, methods and techniques from data science, digital humanities and design research, whilst developing a portfolio of work that prepares them for diverse career opportunities.
The programme aims to develop the methodological, conceptual and practical skills needed to design, deploy and interpret data visualisations successfully in academic, policy and public contexts. The course combines academic training in methodological and conceptual aspects with the development of technical, creative and practical competences in data visualisation as a way of communicating knowledge, as a form of engagement, and as a way of seeing the world.
During the programme you will develop:
- End-to-end skills and joined-up understanding that enable you to design, create and code visualisations, work with data, and analyse and understand your data visualisations and those of others.
- Critical, interdisciplinary perspectives required by employers, that integrate expertise in tools, techniques, knowledges and methods of analysis, leading to a 360 view of what data visualisations are and do, and the limits of this medium.
- A portfolio of work to kickstart your career progressed through diverse projects in your modules, a practice- or theory-led dissertation, and within the Data-Design Camp.
- Expertise in the interactions between Data + Code + Design + Theory developed through learn to code as a basis for creating visualisations, as well as furthering your understanding of visualisations through critique and analysis.
What is an MASc?
The MASc is a flexible degree where students customise their learning trajectory through interdisciplinary topics and modules that might usually be isolated to either MA or MSc qualifications. Through optional module choices, project directions and final dissertation, you can tune your degree to fit your learning and career goals.
Skills from this degree
- Coding and software skills for visualisation
- Design and visual analysis skills building on the fundamentals of data visualisation
- Substantial design experience through project work
- Analytical skills to conceptually frame and relate visualisation designs to wider societal, cultural, and political debates
- Writing and communication skills for analysis/discussing technical content
- Critical academic research skills with an interdisciplinary focus
General entry requirements
2:i undergraduate degree (or equivalent). There is no requirement for prior knowledge of coding or programming.
English language requirements
You can find out more about our English language requirementsLink opens in a new window. This course requires the following:
- Band B
- IELTS overall score of 7.0, minimum component scores of two at 6.0/6.5 and the rest at 7.0 or above.
We welcome applications from students with other internationally recognised qualifications.
For more information, please visit the international entry requirements pageLink opens in a new window.
There are no additional entry requirements for this course.
Data visualisations (graphs, maps, networks) have become a fundamental currency for the exploration of data and the exchange of information. This module develops foundational understanding in what visualisations are and how they operate. Coding skills are developed alongside the conceptual understanding, allowing students to develop visualisations and their understanding in terms of design, theory, data and code.
As visualisation is such an interdisciplinary topic, students will engage with diverse topics spanning data science and psychology, graphic design and the arts, and critical cartography and data feminism.
Data Visualisation in Science, Culture and Public Policy
The module introduces concepts, methods and empirical cases that enable an understanding of the affordances, power and limitations of data visualisation in science, culture, and public policy.
Data visualisations have opened-up diverse challenges and opportunities for contemporary science, culture and public policy that show how visualisations mediate knowledge and enable communications through persuasion and real-world engagements. The module draws from social, cultural and political theory, science and technology studies, as well as digital and environmental humanities, equipping students with an ability to analyse and research the affordances of data visualisation as forms of knowledge, intervention and participation.
Advanced Visualisation Design Labs
In this module students develop three visualisation projects that further advance their independence in visualisation design, development, analysis and critique. Each project responds to a visualisation challenge drawn from methodological, societal, scientific and policy topics. At least one of the challenges involves a real-world problem proposed by an external partner.
Students respond to project briefs through hands-on workshops, prototyping, and expanding their design and technical skills in dialogue with their methodological and critical understanding. Master-classes expand students’ methodological and technical repertoire in areas such as human-centred design, typography, storytelling, stencilling, and digital cartography. In dialogue with their visualisation portfolio, students produce a design manifesto exploring their methodological and aesthetic approach, in relation to ethics and visual cultures.
Optional modules can vary from year to year. Example optional modules may include:
- Data Science Across Disciplines: Principles, Practice and Critique
- User Interface Cultures: Design, Method and Critique
- Urban Data
- Interdisciplinary Approaches to Machine Learning
- Media Activism
- Approaches to the Digital
- Complexity in the Social Sciences
- Digital Objects, Digital Methods
- Big Data Research: Hype or Revolution?
Modules in this course make use of a range of teaching and learning techniques, including, for example:
- Student group and project work
- Coding sessions
- Blended learning including the use of an online virtual learning environment
- Reading and directed critical discussion
- Independent research by students
- Practice-based activities
A one-week Data-Design Camp enables students to advance their projects through interactions with leading visualisation professionals.
A typical seminar size for this course consists of around 16-18 students.
Typical contact hours
There are typically around 7-9 hours contact hours per week, depending on optional modules chosen.
A combination of essays, reports, design projects, a portfolio, technical report writing, practice assessments, group work and presentations and an individual research project (5,000 word Final Project, MASc only).
Most departments have reading lists available through Warwick Library. If you would like to view reading lists for the current cohort of students you can visit our Warwick Library web pageLink opens in a new window.
Your personalised timetable will be complete when you have been registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules shortly before joining us.
Your training in this course puts you in a unique position for exciting job opportunities involving Data Science, Analytics, GIS and Software Engineering, as well as roles in Data Journalism, Social Research, Science Communication, Policy Research, Business Intelligence.
Data visualisation specialists are hired throughout the digital and tech sector, as well as in health and civil services, media and publishing, all the way to design and communications. Visualisation job roles blur the boundaries between disciplinary backgrounds, producing exciting careers combining expertise in data, statistics and interfaces, communications and decision making.
Our department has a dedicated professionally qualified Senior Careers Consultant offering impartial advice and guidance together with workshops and events throughout the year. Previous examples of workshops and events include:
- Warwick careers fairs throughout the year
- Presentations from Alumni on their experiences after CIM
- Careers in AI and Data Science
- Discovering Careers in the Creative Industries
- Discuss What’s Next After Your CIM Master’s Degree
Centre for Interdisciplinary Methodologies (CIM)
The Centre for Interdisciplinary Methodologies (CIM) was established at Warwick in 2012 to foster innovative and experimental forms of knowledge production through a sustained focus on methodology. CIM is dedicated to expanding the role of interdisciplinary methods through new lines of inquiry that cut across disciplinary boundaries, both intellectually and institutionally.
Method is central to the formation and transformation of disciplinary knowledges, and the challenge of working across and in between disciplines is both exciting and pressing. Our research team is drawn from across the Arts, Humanities, Social Sciences and Sciences, with expertise in a variety of substantive domains.
Within Warwick, CIM is an advocate of interdisciplinary research and study. Beyond Warwick and beyond the academy, CIM explores new forms of public engagement, both with potential research users and with the experts, experimenters and institutions in business, civil society and government that are at the forefront of applied methodological innovation.
Find out more about us on our website.
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