AI and Research Work - Useful learning materials

On this page, we are collecting learning materials related to the use of AI in research. With AI, we mean popularised generative artificial intelligence tools, like ChatGPT, which do not require actual coding or knowledge of machine learning. 

There are two perspectives taken into account in these learning materials:

1. Practical tips: understanding the basics behind generative AI with Large Language Models (LLMs), and how to use LLMs in the various stages of the research lifecycle
2. Responsible conduct of research: how to use these novel tools in a responsible way, considering research ethics as well as data protection.

Materials

• Slides from the live open training event "AI and Research Work 11/March/2024"The presentation is targeted to researchers with no background on AI, computer science topics, and other technical matters. If your level is more advanced, see the external materials below.
• Video recordings (coming soon)
• Questions and answers (constantly updated, last update 31/10/2023)The list of FAQs also has insights for more advanced users. You can submit improvements as comments. 
• Handbooks:
  1. "AI for Qualitative Data Analysis: A Practical Guide for Researchers"
  2. AI in research work (in preparation)

If you have tips on how to improve these open learning materials, please contact us at[email protected].'

 

External references

• Guidance for generative AI in education and research (target audience: everyone)
• Open materials on generative AI (including a course!) by Aalborg University(audience: anyone with no previous knowledge of AI)
• Jeremy Howard's Hacker guide to Language Models (target audience: data scientists and those who like to see what's under the hood)