Skip navigation
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 Social Sciences, Computing Sciences, and Arts & Humanities to answer employers' demands for a new generation of researchers. 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, cloud computing, and contemporary artificial intelligence (AI) 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 and AI? How are our lives represented in different formations and transformations of 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 programming and statistical modelling 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 Jupyter/IPython and RStudio)
  • Statistics for the Social Sciences (up to multiple linear regression and logistic regression)
  • Advanced Statistics (generalised linear models, multilevel modelling and casual inference)
  • Data Science (including theory, computational methods, and conceptual critique)
  • Artificial Intelligence (from machine learning and neural networks to Generative AI)
  • Cloud Computing (concepts and practical applications using Microsoft Azure)
  • 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
This information is applicable for 2024 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.

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). 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


Entry requirements

**Minimum requirements** 2:i undergraduate degree. **English language requirements** You can find out more about our English language requirements. 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 page. **Additional requirements** There are no additional entry requirements for this course.


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. Please visit the University's scholarship webpages.

Big Data and Digital Futures at University of Warwick - UCAS