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Big Data and Digital Futures at University of Warwick - UCAS

There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

Join Warwick's Big Data and Digital Futures MSc/PGDip and learn to critically engage with big data. The Centre for Interdisciplinary Methodologies works across disciplines, drawing from the Arts, Humanities, Social Sciences and Sciences, to answer employers' demands for a new generation of researchers. Course overview 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
  • Python and R programming skills (using RStudio)
  • Introductory Data Science and Machine Learning / AI techniques, including Generative AI
  • 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
  • Writing and communication skills for analysis/discussing technical content
  • Critical academic research skills with an interdisciplinary focus
This information is applicable for 2025 entry. Given the interval between the publication of courses and enrolment, some of the information may change. It is important to check our website before you apply.

Modules

Core modules

  • Big Data Research: Hype or Revolution?
  • Dissertation
Optional Core Modules Term One
  • Data Science Across Disciplines: Principles, Practice and Critique
or
  • Fundamentals in Quantitative Research Methods
Term Two
  • Scaling Data and Societies
or
  • Advanced Quantitative Research
Optional modules Optional modules can vary from year to year. Example optional modules may include:
  • Introduction to Contemporary AI: Techniques and Critiques
  • User Interface Cultures: Design, Method and Critique
  • Visualisation Foundations
  • Generative AI: Histories, Techniques, Cultures and Impacts
  • Digital Sociology
  • Foundations of Data Analytics
  • Data Mining
  • Digital Methods
  • Natural Language Processing
  • Data Visualisation in Science, Culture and Public Policy
  • Approaches to the Digital
  • Urban Infrastructures
  • Platform Economy, Science & Culture
  • Advanced Visualisation Labs
  • Adventures in Interdisciplinarity
- Global Digital Health and Human Rights

Assessment method

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).


Entry requirements

Minimum requirements 2:1 undergraduate degree (or equivalent). English language requirements You can find out more about our English language requirements on our website. 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.


Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Please visit the University of Warwick website for the tuition fees for postgraduate courses: https://warwick.ac.uk/study/postgraduate/funding/fees

Sponsorship information

We offer a variety of postgraduate funding options for study at the University of Warwick, from postgraduate loans, university scholarships, fee awards, to academic department bursaries. It's important that you apply for your postgraduate course first before you apply for a University of Warwick scholarship.

Big Data and Digital Futures at University of Warwick - UCAS