University of Warwick

Degree level: Postgraduate

Big Data and Digital Futures (Taught)

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

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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.

Course details

Modules

Core modules:

  • Fundamentals in Quantitative Research Methods
  • Advanced Quantitative Research
  • Big Data Research: Hype or Revolution?
  • Dissertation
Optional modules Optional modules can vary from year to year. Example optional modules may include:
  • 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

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).

  • 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


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

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
Big Data and Digital Futures at University of Warwick - UCAS