Generative AI across the whole research workflow, from the first idea to the final presentation and publication. Bring it in thoughtfully at each step, with reflection and responsible use throughout.
The course follows three steps: Think, Prompt, Reflect. Move from understanding AI to working with it in research, weighing its consequences and shaping your own practice.
How generative AI works and where it came from, its real-world costs, and how it is reshaping science.
The privacy, disclosure and policy questions to settle before AI touches your research.
A map of where AI genuinely helps at each stage of the research workflow.
Choosing and prompting AI assistants and open LLMs, from a single prompt to using them across your workflow.
The purpose-built tools for each research stage, and how to fit them into your work.
Where AI shifts from assistant to agent, planning steps and using tools and memory to carry out multi-step work.
Where AI capability is heading, and what it could mean for how research gets done.
The epistemic risks and integrity questions that guide responsible AI use in research.
Clarifying your values and boundaries to shape a personal framework for working with AI.
Everything used in the course in one place: the AI tools by research stage, the custom GPTs and reflection framework, and a curated reading list. A live page participants can bookmark and return to whenever they need it.
Open the companion →Tell me about your research group or doctoral programme, and I'll send you a tailored proposal.
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