Hands-on online session for RTPs on using LLMs like Copilot, Gemini, ChatGPT and Claude practically, critically and responsibly.
As Research Technical Professionals (RTPs), we work across a wide range of technical and research support activities, from managing data and troubleshooting code to documenting procedures, developing training materials and communicating with researchers. Generative AI tools such as Copilot, Gemini, ChatGPT and Claude can support many of these tasks, helping you explore unfamiliar problems, work with information, draft and refine content, and develop simple scripts or automations. But using these tools effectively requires more than knowing what to ask: it means understanding their limitations, protecting sensitive information and applying your own judgement to the results.
This hands-on session introduces practical ways for RTPs to use large language models (LLMs) in your day-to-day work, alongside the skills to use them critically and responsibly. During the session, RTPs will:
- Explore what LLMs can and can't do, and understand where they tend to go wrong.
- Practice prompting for practical tasks, from summarising technical documentation and drafting guidance to troubleshooting code and developing simple scripts.
- Learn how to protect sensitive information, check AI-generated outputs and decide when AI is an appropriate tool for the job.
- Consider wider responsibilities, including bias, transparency about AI use, professional integrity and environmental impact.
No coding or previous AI experience is needed. The session isn't tied to any particular platform, so the skills you develop will carry over to whichever tools your institution provides.
Learning outcomes:
By the end of this course, you will be able to:
- Understand what LLMs are and their key capabilities and limitations
- Apply responsible practices when using AI tools in your work
- Craft effective prompts that enhance rather than replace critical thinking
- Navigate ethical considerations including bias, privacy, and environmental impact
- Implement institutional policies and guidelines in your AI usage
