AI Prompting for Biologists
About the course | Intended audience | Prerequisites | Content details | Scheduled events
About the course
As AI chatbots become more widely available, understanding how they work and how to prompt them effectively is increasingly important. This course provides background on the history of large language models and shows how prompt design can influence the quality and usefulness of the responses they generate.
The course takes a practical approach to using AI chatbots in biological data analysis. Participants explore how to prompt in a way that is useful for biologists and bioinformaticians, with hands-on examples that illustrate strategies and tactics for getting better results from AI tools. The teaching also considers why biology presents particular challenges for language models and how those limitations affect their use in research.
The course is aimed at researchers with no computational background and is designed to help them use generative AI more confidently in their work. Although no programming is used during the course, some examples may involve AI-generated code as a basis for in-class discussions.
Back to topIntended audience
This course is suitable for:
- life scientists who want to explore how AI chatbots can support data analysis
- participants who want practical guidance on prompting AI tools for biological research
- researchers looking to understand the opportunities and limitations of AI chatbots in bioinformatics
Prerequisites
No formal computational background is required.
The following experience is recommended:
- a basic familiarity with at least one programming language, such as R, Python or Bash, which will help when discussing AI-generated code
Content details
- Introduction to AI chatbots and large language models
Introduces the history of AI chatbots and explains how large language models work at a basic level. This section also clarifies why prompts matter and why language-based interaction is central to the way these systems operate. - Why biology needs careful prompting
Discusses why biological research is different from other domains and why AI-generated responses need to be treated carefully in this context. This section highlights limitations and considerations that affect the use of language models in biology. - Prompt design and practical prompting tactics
Focuses on how to create effective prompts and how to think like a bioinformatician or software engineer when interacting with AI chatbots. The course uses hands-on use cases to show how different prompting strategies can change the quality of the output. - Using AI in biological data analysis
Shows how generative AI can be applied to biological data analysis and explores ways it may open up new research opportunities for biologists without computational experience. The emphasis is on practical use rather than programming. - Challenges and opportunities
Covers policy issues and responsible use considerations associated with the use of AI chatbots in research. Also covers agentic AI applications, including specific developments in biological sciences.