Structured short courses and learning pathways for researchers at every stage.
Research questions, aims, objectives, evidence, planning and the fundamentals needed before deeper methodological work.
View full information →Argument, paragraph structure, critical synthesis, academic register, cohesion and responsible self-editing.
View full information →Searching, evaluating, organising and synthesising literature into a critical review rather than a descriptive summary.
View full information →Sampling, interviews, focus groups, reflexivity, coding, thematic analysis and qualitative research quality.
View full information →Variables, sampling, measurement, hypotheses, validity, bias and analysis planning for quantitative studies.
View full information →Descriptive statistics, inference, effect sizes, confidence intervals, regression, assumptions and interpretation.
View full information →Practical SPSS workflows from data preparation and screening to analysis and output interpretation.
View full information →Research-focused R skills for data preparation, modelling, visualisation, diagnostics and reproducible analysis.
Python for research data handling, analysis, statistics, visualisation and reproducible notebook workflows.
View full information →Qualitative data organisation, coding frameworks, queries, memoing and transparent analysis workflows in NVivo.
View full information →Consent, confidentiality, risk, data protection, recruitment, governance and ethical research planning.
View full information →Contribution, methods defence, limitations, results interpretation and examiner-style questioning practice.
View full information →