Join Warwick's Big Data and Digital Futures 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

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.

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).

• '-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

Careers

Graduates from these courses have gone on to work for employers including: AXA, BaiDu, GroupM, Just Eat, Skyscanner, The Labour Party and University of Warwick. They have pursued roles such as: authors, writers and translators; business and financial project management professionals; buyers and procurement officers; data analysts and product managers; marketing associate professionals; 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

Students can also exit with PGDip award.