This degree responds directly to the growing demand across research fields and by employers in society for a new generation of postgraduates who can critically engage with big data theoretically, methodologically and practically. In contrast to many big data-focused degrees (such as Data Science or Data Analytics) where the emphasis is almost exclusively on data practices and computational tools, this degree underpins key practical skills with a range of theoretical approaches to data.

How is our world influenced by big data? How are our lives represented in big data? This course will enable you, whatever your disciplinary background, to understand and act in a society transformed by data, networks and computation and develop a range of interdisciplinary capacities.

Our course offers you:

• Core knowledge in statistical modelling and programming for data-driven careers
• An extensive understanding of the relationship between big data technology and society
• Practical and critical application of these techniques to cutting-edge methods across the data spectrum

Core Modules

• Fundamentals in Quantitative Research Methods
• Advanced Quantitative Research
• Big Data Research: Hype or Revolution?
• Dissertation

Optional Modules

Previously, a selection of the following options have been offered:

• Interdisciplinary Approaches to Machine Learning
• User Interface Cultures: Design, Method and Critique
• Visualisation
• Digital Cities
• Digital Sociology
• Complexity in the Social Sciences
• Urban Resilience, Disasters and Data

Teaching

Modules in this course make use of a range of teaching and learning techniques, including, for example: blended learning including the use of an online virtual learning environment; student group and project work; lectures; seminars; reading and directed critical discussion; independent research by students; practice-based activities.

Contact Hours

7-9 hours per week, depending on optional modules chosen

Class Sizes

A typical seminar size is 12-16 students

Assessment

A combination of essays, reports, design projects, technical report writing, practice assessments, group work and presentations and an individual research project (10,000 word dissertation).

Assessment

• R programming skills (using RStudio)
• Statistics in Social Science (up to multiple linear regression and logistic regression)
• Advanced Statistics (generalised linear models, multilevel modelling and casual inference)
• Basics in Social Network Analysis, Web Scraping, Reproducible Analysis, Data Visualisation, SQL, Deep Learning, Agent-Based Modelling (From Q-Step Masterclasses)
• Writing and communication skills for analysis/discussing technical content
• Critical academic research skills with an interdisciplinary focus

Minimum requirements 2:i undergraduate degree

English language requirements 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 Students
We welcome applications from students with other internationally recognised qualifications. For more information please visit the international entry requirements page.

For up-to-date information concerning fees, funding and scholarships for Home, EU and Overseas students please visit Warwick's Fees and Funding webpage.

Additional course cost
All students on CIM degrees require a laptop computer for their studies. This is provided by the department for students to use and keep, and the cost is included in course fees.

Scholarships

A range of scholarships is available, including a CIM scholarship providing a £4,000 contribution towards tuition fees for Home/EU students (two awards are available for each of our three taught postgraduate degrees).

Graduates from these courses have gone on to work for employers including: Accenture, AXA, BaiDu, GroupM, Just Eat, Skyscanner, StatsBomb, Tableau Software, The Labour Party, University of Warwick, and YouView TV. They have also gone on to work on a PhD at schools including: University of Warwick, King’s College London, and University of Siegen. They have pursued roles such as: data analysts and product managers; marketing associate professionals; business and financial project management professionals; authors, writers and translators; quality assurance and regulatory professionals and researchers.

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
• Careers in AI and Data Science
• Discovering Careers in the Creative Industries
• Discuss What’s Next After Your CIM Master’s Degree

There are a number of different ways to visit the University of Warwick throughout the year. We host bespoke PG visits, where you can talk directly with your chosen department and explore our campus through a personalised tour. Some departments also host their own events and open days, where you can learn more about your department or course of study. To find out more about all of these opportunities, visit our Postgraduate Visits page.