Practical AI for Biomedical Researchers (Fall 2026)
A 1-day course on how to responsibly incorporate AI tools into your workflows
The course Practical AI for Biomedical Researchers will provide participants with information about the architecture, constraints and benefits of AI for scientific purposes, with a particular focus on Large Language Models (LLMs). The course will introduce relevant concepts like tokenization, embeddings and output sampling. Additionally, the course will explore limitations and risks from modern LLM architecture and deployment: potential security and confidentiality risks, hallucinations, validation, skill atrophy and sustainability concerns. Afterwards, there will be a session on the use of AI for programming, focusing on agentic tools like Claude Code, and another session on the use of LLMs for literature search, summarization and ideation. Lastly, we will have a panel discussion involving experts with applied AI experience from a variety of backgrounds.
Requirements
This course has no prerequisites.
Interested?
➡️ If you are an employee, sign up here
➡️ If you are a PhD student, sign up here
Course Disclaimers
- The course is free of charge and intended for all KU researchers, and especially PhD students, at SUND
- A no-show fee will be implemented for registrants who do not attend the course
- If you are a PhD student and you would like to receive ECTS credits for participating in this course, you must enroll through the PhD school system
- If you are not a PhD student and sign up via the PhD school registration link, you will be charged for the course
- Please be advised that course participation via the PhD school happens under the PhD school's terms and conditions which HeaDS has no influence over