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Practical AI for Biomedical Researchers
Provider: Faculty of Health and Medical Sciences
Activity no.: 3968-26-00-00
There are 33 available seats
Enrollment deadline: 21/09/2026
Date and time
19.10.2026, at: 08:30 - 15:45
Regular seats
35
Course fee
1,200.00 kr.
Lecturers
Anders Krogh
ECTS credits
0.60
Contact person
HeaDS Administration E-mail address: heads-admin@sund.ku.dk
Enrolment Handling/Course Organiser
PhD administration SUND E-mail address: phdkursus@sund.ku.dk
Enrolment guidelines
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH.
Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list.
The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee.
Learning objectives
A student who has met the objectives of the course will be able to:
1. Understand conceptually how AI models work, particularly Large Language Models (LLMs).
2. Evaluate outputs and limitations of AI models critically, particularly regarding hallucinations, privacy risks and biases.
3. Be informed about current and upcoming developments in AI.
4. Make better use of AI for scientific tasks involving searching, summarization and programming.
Content
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 LLMs. First, we will have a guest lecture from Ole Winther, a professor who has utilized AI in applied biomedical research throughout his career. The next lecture will introduce relevant concepts like tokenization, embeddings and output sampling. Then, 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.
Participants
Seats: 35
The course is targeted at beginners, no previous expertise required
Relevance to graduate programmers
The course is relevant to PhD students from the following graduate programs at the Graduate School of Health and Medical Sciences, UCPH:
All graduate programs
Language
English
Form
Lecture
Course director
Anders Krogh,
Professor, Head of Center for Health Data Science,
Center for Health Data Science,
anders.krogh@sund.ku.dk
Teachers
Stefano Pupe, PhD
stefano.pupe@sund.ku.dk
Sr. Consultant & Research Data and Computing Coordinator
Alba Refoyo Martinez, PhD
alba.martinez@sund.ku.dk
Special Consultant
Diana Andrejeva, PhD
diana.andrejeva@sund.ku.dkSpecial Consultant
Suze Roostee, PhD
suze.roostee@sund.ku.dk
Data Scientist
Valentina Sora, PhD
vaso@di.ku.dk
Postdoctoral Researcher
Dates
19 October 2026
Course location
Faculty Club 16.6.16, Panum, Blegdamsvej 3B
Registration
Please register by 21 September 2026
Expected frequency
We anticipate running this course 1-2 times per year
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