This course is intended for PhD students, Early Career Researchers (ECR), research associates, junior lecturers, and all researchers interested in exploring various analytics methods ranging from descriptive and predictive to prescriptive analytics.

This course offers a hands-on introduction to creative approaches to doing qualitative research. It is designed for researchers and PhD students who already have a background in qualitative research techniques and would like to expand their knowledge to include more creative techniques.

This is an introductory course aimed at Postgraduate researchers and early career researchers, as well as other researchers in humanities and social sciences or in the industry who would like to expand their methodological toolkit to include digital methods.

This course offers a comprehensive introduction to the analysis of longitudinal data. The focus will be on three core areas: estimating latent trajectories to analyse change over time, addressing ‘reverse causality’ and modelling reciprocal relationships, and leveraging panel data for causal inference within the potential outcomes framework.

This in-person course introduces you to the methodological foundations of social network analysis, and how to use qualitative and quantitative methods to collect, analyse, and interpret social network data.

This course introduces a critical but friendly approach to qualitative interviewing for those using or considering using interviews in their social science research.
Participants will be encouraged to think critically about why they are using interviews, what type of data interviews can generate and how their own role in data collection shapes the interview and the data generated.

This course provides a comprehensive introduction to using NVivo to manage the data and analyse a qualitative or mixed-methods project. Participants will be guided through all phases of setting up a project to its analysis and reporting, and how this can be facilitated through creative and systematic use of NVivo.