The core modules – 1. Visualisation Foundations, 2. Data Visualisation in Science, Culture and Public Policy and 3. Advanced Visualisation Design Labs – engage students with the diverse knowledge and skills required for designing, developing, deploying and interpreting data visualisations. Your studies will bring together topics from the Sciences, Arts, Humanities and Social Sciences, drawing from fields as diverse as data science, digital humanities and human-centred design.You can find more information on core and optional modules below, alongside information on your 4. Final Project (Practical)

By studying Data Visualisation(s) as objects, methods and a subject, you will develop a range of skills:

• 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

Our interdisciplinary study program enables you to make this degree your own. Rather than following a degree focused on data and code, or one founded on design and theory, the MASc Data Visualisation integrates data + design + code + theory whilst allowing students to follow individual goals within projects and through optional module choices.

CIM students will have diverse backgrounds -- whether you have studied graphic design or geography, communication studies or computer science (or architecture or astrophysics!), what is most important is that you share our students’ ambition and enthusiasm for learning how data visualisations are made and influence the world; and be keen to learn through research and by doing.

CIM students benefit from being part of a diverse student cohort who bring variety of experiences, perspectives and skills from the sciences, arts, humanities and social sciences including computer science, design, media and communications, sociology, and science and technology studies. We also encourage applications from professionals already working in data and design related fields who want to expand their career opportunities by investing in this exciting subject.

The MASc in Data Visualisation equips students for exciting opportunities in sectors working with Data, Analytics and Digital or Visual interfaces. These opportunities are rarely just a coding job, or an analytics or design job. Instead, employers across Data Science, Research, Media, Journalism, Business, Government and NGOs now require the knowledge and skills that can bring fields of expertise and interdisciplinary understanding together.

Today’s careers have many components, and frequently require that candidates can understand contextual positioning (e.g. sociocultural, ethical), alongside technical skills (e.g. coding, design) and strong research, critical thinking and communication skills. Studying Data Visualisation is an ideal education into how to understand and work with our data-fied, analytics-led, media-rich, connected world.

Data visualisation is a job role in of itself, but it is also increasingly specified for any job that works with data and requires communication. As such, the MASc degree allows students to open-up new opportunities in their current field of work or in your career plans, at the same time as revealing new career opportunities.

CORE MODULES

Our core modules will enable you to develop key competences in Data Visualisation through learning that integrates across methodological and conceptual perspectives, and often through practice-based learning. After developing foundational skills and knowledge, you will develop your understanding of what visualisations do and how they are made, before developing your final project.

Visualisation Foundations (30 CATs - Autumn Term): 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 (20 or 30 CATs - Spring Term): 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. MASc Students are provided with an opportunity to choose this core module at 20 or 30 CATs

Advanced Visualisation Design Labs (20 or 30 CATs - Spring Term): 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. Masterclasses 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. MASc Students are provided with an opportunity to choose this core module at 20 or 30 CATs

Please note : Based on the CAT weightings you choose for your core modules in Term 2 (Spring Term), your total core modules will add up to 130 or 140 or 150 CATs. You then need to choose option modules worth 50 or 40 or 30 CATs to take the 180 CATs required for your master’s degree. For example, you can take 1* 20-CAT + 1*30 CATs, 2*15 + 1*20 CATs options etc., where available.

Practical Final Project: (60 CATs - Term 3 and Summer Vacation) Students produce a substantial, practice-based data visualisation project on a subject of their choosing. Students further develop their skills & knowledge through independent research leading to the visualisation outcome(s) and a report (5,000 words) that showcase their creative and critical approach, and theoretical and methodological understanding. A one-week Data-Design Camp enables students to advance their projects and to refine their design, coding and practical skills through interactions with leading visualisation professionals. During the Data-Design Camp, students will not only receive feedback on their dissertation projects but will also develop your career awareness in dialogue with external experts and understand the needs and perspectives of the related industries better.

OPTIONAL MODULES

Our interdisciplinary approach comprises a flexible structure, which enable students from varied backgrounds to complement and expand their knowledge with an individually-tailored selection of optional modules. Recent modules include:

• Digital Objects, Digital Methods (IM904)
• Approaches to the Digital (IM902)
• Digital Sociology (IM920)
• User Interface Cultures: Design, Method and Critique (IM923)
• Interdisciplinary Approaches to Machine Learning (IM931)
• Data Science Across Disciplines: Principles, Practice and Critique (IM939)
• Media Activism (IM933)
• Ecological Futures: Science, Media and Culture (IM934)
• Data Mining (CS909)
• Foundations of Data Analytics (CS910)
• Social Informatics (CS916)
• Fundamentals in Quantitative Research Methods (QS905)
• Big Data Research: Hype or Revolution (IM952)
• Urban Data (IM919)Link opens in a new window

DURATION

Full-time MASc: 1 year

Part-time MASc: 2 years

Full-time PG Diploma: 9 months

Part-time PG Diploma: 18 months

ENTRY REQUIREMENTS

2:i undergraduate degree (or equivalent). There is no requirement for prior knowledge of coding or programming.

ENGLISH LANGUAGE REQUIREMENTS

Band B

There may be the option to attend the Pre-Sessional English Programme prior to commencement of study. See the Pre-Sessional English Programme website for information, but note that CIM has the additional requirement of a minimum 6.0 in the IELTS writing component for acceptance through this programme.

2023-24 COURSE FEES

We consider all eligible applicants for bursaries and scholarship while funds are available, so do apply for the course as early as possible if you'd like to be considered.

PhD Funding is possible through a number of sources at Warwick.

Information on all funding sources available to CIM postgraduate candidates (Masters and Doctoral) is available hereLink opens in a new window.