Early Stage

This software carpentry workshop introduces the building blocks of Python. Please do not sign up for the four half-days (morning) interactive workshop unless you are able to attend all four morning sessions in full.

Learn how to solve complex problems in a creative, user-centric and curious manner.

This workshop covers systematic reviews that can be used in both qualitative and quantitative studies.

This session provides best practice on how to build a pitch deck and how to deliver it compellingly.

This workshop aims to improve the academic writing skills of Higher Degree by Research students by integrating Generative AI tools like ChatGPT into the writing process, while maintaining academic integrity.

This workshop uses practical and discussion-based training to guide researchers about identifying what constitutes sensitive data, the risks of working with sensitive data, and how to appropriately manage those risks. The workshop is particularly relevant for clinical, environmental, and ecological researchers, but is applicable to all fields of research.

Learn how generative AI tools can support your thinking and development as a researcher and academic writer.

The course will cover the principles of logistic regression and includes practical sessions getting hands-on experience of logistic regression in R. You will require prior expertise in R and a basic familiarity with statistical hypothesis testing and regression analysis to attend.

Learn about research metrices and social media impact. Find out how and where you can start making an impact with your research. (Previously known as Making and measuring research impact: an introduction)

This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in SPSS. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. Prior knowledge of SPSS is required.