Graduate School of health and Medical Sciences

Data Science for non-Data Scientists
Provider: Faculty of Health and Medical Sciences

Activity no.: 3935-24-00-00
	Enrollment deadline: 15/08/2024

Date and time	19.09.2024, at: 09:00 - 20.09.2024, at: 18:00
Regular seats	18
Course fee	3,840.00 kr.
Lecturers	Thomas Jespersen
ECTS credits	1.70

Contact person	Arnela Saljic E-mail address: arnela@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content 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 the basic principles of data science, including machine learning techniques 2. Understand the prerequisites for data science, including machine learning 3. Identify aspects of own research with and without data science potential 4. Interpret critically studies that apply data science methods 5. Communicate fluently with data scientists Content The aim of the course is to introduce key concepts of data science and machine learning to researchers with no prior knowledge of data science. Specifically, course participants will gain the basic understanding and vocabulary necessary to a) identify data science aspects of their own research, b) communicate with data scientists so that projects between the researcher and the data scientists can be collaborative, and c) critically interpret studies that employ data science or machine learning methods. Studentes are required to use software and is designed for the software R. No prior knowledge required. Key words: Diagnostics, machine learning, deep learning, epidemiology, data science Participants PhD students in health and medcial sciences with no or very little knowledge of data science. The course is designed with a cardiovascular focus Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: - Cardiovascular Research - Veterinary Clinical Sciences - Pharmaceutical Sciences (Drug Research Academy) Language English Form Lecutres, exercises, discussions Course director Thomas Jespersen, professor, Department of Biomedical Sciences, thojes@sund.ku.dk Teachers Jonas L. Isaksen, postdoc, Department of Biomedical Sciences, University of Copenhagen Jørgen K. Kanters, Associate Professor, Department of Biomedical Sciences, University of Copenhagen Oswin Krause, Assistant Professor, Department of Computer Science, University of Copenhagen Malene Nørregaard, PhD-student, Department of Biomedical Sciences, University of Copenhagen Dates September 19th and 20th, 2024 Course location Panum Institute Registration Please register before August 15th, 2024 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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