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Introduction to machine learning in biomedical research - Part A
Provider: Faculty of Health and Medical Sciences

Activity no.: 3926-23-00-00 
Enrollment deadline: 27/03/2023
Date and time24.04.2023, at: 09:00 - 28.04.2023, at: 16:00
Regular seats25
Course fee6,600.00 kr.
LecturersAnders Krogh
Ruth Loos
ECTS credits3.90
Contact personEleonora Nigro    E-mail address: eleonora.nigro@sund.ku.dk
Enrolment Handling/Course OrganiserPhD 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 enrolment 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 universities. 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. Understanding basic concepts in Machine Learning
2. Understand the impact of data on Machine Learning outcomes
3. Apply Machine Learning to biological and medical datasets
4. Apply Python Machine Learning modules
5. Evaluate the performance of Machine Learning system
6. Disseminate the project result in a technical report


Content

• Introduction to Data Analysis and Machine Learning
• Data wrangling, testing methods, etc.
• Classic Machine Learning approaches, such as logistic regression, support vector machine, random forest
• Introduction to Python for data analysis and machine learning (numpy, pandas, Scikit- learn)
• Exercises in classic Machine Learning
• Neural Network, including feed-forward network for biomedical data
• Small group projects with real data
• Groups present projects
• Example applications in the biomedical field. Seminars by invited speakers.


Participants

PhD students enrolled at the Graduate School of Health and Medical Sciences and postdocs
Prerequisites: Basic Knowledge of Python programming is required

Max 25 Participants


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:

All graduate programmes


Language

English


Form

Lectures, seminars, group work, discussions, exercises, project work


Course director

Anders Krogh
Professor
Center for Health Data Science and Department of Computer Science
University of Copenhagen
anders.krogh@sund.ku.dk

Ruth Loos
Professor
Novo Nordisk Foundation Center for Basic Metabolic Research
University of Copenhagen
ruth.loos@sund.ku.dk


Teachers

Anders Krogh
Professor
Center for Health Data Science and Department of Computer Science
University of Copenhagen
anders.krogh@sund.ku.dk

Shyam Gopalakrishnan
Associate Professor
GLOBE Institute
University of Copenhagen
shyam.gopalakrishnan@sund.ku.dk

Inigo Prada Luengo
Postdoc
Department of Computer Science.
Inigo.luengo@bio.ku.dk

Valentina Sora
Postdoc
Center for Health Data Science
Vaso@di.ku.dk

Viktoria Shuster
PhD student
Center for Health Data Science
viktoria.schuster@sund.ku.dk



Dates

Part A: Introduction to Machine Learning
24 - 28 April 2023


Course location

PANUM,
Room 13.1.83 (max 33 people)


Registration

Please register before 27 March 2023


Expected frequency

Once a year


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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