Graduate School of health and Medical Sciences

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

Activity no.: 3926-22-00-00
	Enrollment deadline: 25/04/2022

Date and time	23.05.2022, at: 09:00 - 31.05.2022, at: 17:00
Regular seats	30
Course fee	3,120.00 kr.
Lecturers	Ruth Loos
ECTS credits	4.00

Contact person	Imke Thiessen E-mail address: imke.tiessen@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 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 graduate schools in the other Nordic countries. 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 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 systems 6. Disseminate the project results in a technical report Content Introduction to machine learning (5 days) Day1 Introduction to data analysis and machine learning. Data wrangling, testing methods, etc . Classic approaches, such as logistic regression, support vector machines, random forests. Intro to python for data analysis and machine learning (numpy, pandas, Scikit-learn). Practicals on PCA and classic machine learning using scikit-learn. Day2 Neural networks. Basics of feed-forward neural networks. Back-propagation. Model complexity and over-fitting. Introduction to pytorch. Practical on implementing a feed-forward network for biomedical data using Google colab. Day3 Overview of the ZOO of neural networks. Pick from: Variational autoencoders, Generative adversarial networks, recurrent networks, transformers, etc. Practicals and begin a small project to be presented on the last day. Day4 Example applications in the biomedical field. Continue work on projects. Day5 Groups present small projects. Example applications in the biomedical field. Seminars by invited speakers. Introduction to subsequent hackathon workshop and presentation of projects. Students choose top-3 projects to join. Participation in this course is a prerequisite to participate in the 4-day follow-up course 'Hackathon - Application of machine learning in biomedical research' Course code: 3927-22-00-00 Participants PhD students enrolled at the Graduate School of Health and Medical Sciences and postdocs at specific Centers/Departments with some experience in Python programming. Max 30 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 English or Danish. Note that all courses have to be provided in English if required by non-Danish participants. Form Lectures, seminars, group work, discussions, exercises, project work. Course director Ruth Loos, Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, ruth.loos@sund.ku.dk Anders Krogh, Professor, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, anders.krogh@sund.ku.dk Cameron MacPherson, Group Leader, CHIP, Centre of Excellence for Health, Immunity and Infections, cameron.macpherson@regionh.dk Teachers Anders Krogh, Professor, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen Shyam Gopalakrishnan, Associate Professor, Section for Evolutionary Genomics, GLOBE institute, University of Copenhagen Thomas Moritz, Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Tune H Pers, Associate Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Mani Arumugam, Associate Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Simon Rasmussen, Associate Professor, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen Ramtin Zargari Marandi ramtin.zargari.marandi@regionh.dk External lecturers Ole Winther, Professor, Department of Applied Mathematics and Computer Science, DTU Dates Part A: Introduction to Machine Learning May 23, 24, 25 and May 30, 31, 2022 Course location PANUM Maersk Tower Blegdamsvej 3B, 2200 Copenhagen Floor 15, room 7.15.152 Registration Please register before April 25, 2022 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.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec

New courses
Courses are published regularly. High demand courses are announced in spring and autumn.

Learn which courses are announced on fixed dates