Welcome to Machine learning in health technology

Program: BEN

Description: Do you want to get into machine learning but do not know where to start? This is a 3-day course with a practical approach to machine learning directed to PhD students at the Faculty of Medicine. The course includes two days of lectures from basics about machine learning to application of models and critical interpretation of the results. Students will be able to work on their own data (or data provided by the lecturers) based on learnings from the first two days and on the third day, results, and plans for optimizing their results will be discussed.

The content of the course is:

·        Getting started with machine learning

·        Extracting information from data and identifying the most relevant sources (Feature extraction and reduction of feature space)

·        Classification and regression models

·        Evaluating the performance of a model

·        Working with own data

The lecturers will use Python in teaching, but the principles and concepts are easily transferred to other environments, such as, R, MATLAB, etc.

Literature: Links to pre read distributed in Moodle by the different lecturers in due time before the course.

Prerequisites: An education in health sciences and basic knowledge about statistical concepts.

Evaluation: The student will be evaluated individually through their work with own data or data provided by the lecturers.

Organizer: Thomas Kronborg Larsen, email: tkl@hst.aau.dk

Lecturers: 

• Thomas Kronborg Larsen, email: tkl@hst.aau.dk
• Lasse Riis Østergaard, email lasse@hst.aau.dk
• Camilla Heisel Nyholm Thomsen, email: chnt@hst.aau.dk
• Carsten Wridt Stoltenberg, email: cws@hst.aau.dk

ECTS: 2

Time: 13, 14 November and 12 December 2024 (08:15-16:15)

Place: TBA

Zip code: 9220

City: Aalborg

Number of seats: 25

Deadline: 23 October 2024

Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.