General entry requirements

Minimum 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.

International qualifications

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.

Additional requirements

There are no additional entry requirements for this course.

Core modules

Visualisation Foundations

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

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?

Teaching

Modules in this course make use of a range of teaching and learning techniques, including, for example:

• Student group and project work
• Lectures
• Seminars
• 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.

Class sizes

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.

Assessment

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).

Reading lists

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 timetable

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 career

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.

Our Postgraduate courses

• Big Data and Digital Futures (MSc/PGDip)
• Data Visualisation (MASc/PGDip/PGCert)
• Digital Media and Culture (MA)
• Interdisciplinary Studies (MPhil/PhD)

Tuition fees

Tuition fees are payable for each year of your course at the start of the academic year, or at the start of your course, if later. Academic fees cover the cost of tuition, examinations and registration and some student amenities.

Taught course fees  Research course fees

Fee Status Guidance

We carry out an initial fee status assessment based on the information you provide in your application. Students will be classified as Home or Overseas fee status. Your fee status determines tuition fees, and what financial support and scholarships may be available. If you receive an offer, your fee status will be clearly stated alongside the tuition fee information.

Do you need your fee classification to be reviewed?

If you believe that your fee status has been classified incorrectly, you can complete a fee status assessment questionnaire. Please follow the instructions in your offer information and provide the documents needed to reassess your status.

Find out more about how universities assess fee status

Additional course costs

As well as tuition fees and living expenses, some courses may require you to cover the cost of field trips or costs associated with travel abroad.

For departmental specific costs, please see the Modules tab on the course web page for the list of core and optional core modules with hyperlinks to our Module Catalogue (please visit the Department’s website if the Module Catalogue hyperlinks are not provided).

Associated costs can be found on the Study tab for each module listed in the Module Catalogue (please note most of the module content applies to 2022/23 year of study). Information about module department specific costs should be considered in conjunction with the more general costs below:

• Core text books
• Printer credits
• Dissertation binding
• Robe hire for your degree ceremony

Scholarships and bursaries