Seminars on AI
This immersive course, typically spanning 2-3 days, aims at equipping participants with knowledge and practical skills in using generative AI as a scientific assistant. The program covers AI fundamentals, ethical considerations, and hands-on applications. Participants will learn good practices as well as major caveats in prompt engineering, research design, scientific writing, and literature retrieval using usual web-based AI tools. The idea is to give attendees sufficient knowledge to use AI but also to more efficiently collaborate with ad hoc data scientists.
Through interactive workshops and problem-solving sessions, students will develop critical skills, all without requiring technical expertise in data science. The course particularly emphasises the responsible use of AI in research.
All participants receive comprehensive digital materials, including course PDF, examples, and reference guides. Materials remain accessible after the course on an online shared folder.
The events may be given in-person or online.
Typical contents
- A brief history of AI
- Overviews: machine learning, neural networks
- Generative AI: a global understanding
- Tokenisation and attention
- Prompt engineering for LLM
- AI hallucinations
- Tools for writing, editing and text analysis
- Tools for image generation and analysis
- Tools for research design
- General AI ethics
- Algorithmic bias
- Accountability in AI use
- Transparency
