Course leader: Irene Klærke Mikkelsen
Graduate school: Faculty of Health
Max seats: 24
Status: Course is closed for applications
Application deadline: 02/11/2020
Start date: 30/11/2020
Administrator: Annette Poulsen
Introduction to data analysis for health sciences using MATLAB
is being offered by the Graduate School of Health, Aarhus University, fall 2020.
Criteria for participation: University degree in medicine, dentistry, nursing, or Master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).
Aim: To provide participants basic understanding of the programming environment MATLAB. Enable participants to use built-in MATLAB functions and create own scripts and functions for data evaluation and visualization.
Learning outcomes: After completion of the course, the student should be able to understand and be able to use:
- The MATLAB program in general including editor, command window, and help
- MATLAB data structures including matrices, cells and structs
- Generic programming principles including loops, conditions, functions
- MATLAB graphics for plotting and vitalization of data
- MATLAB Debugging capability
Contents: The course is divided into three days and contains these topics:
Day 1 Fundamentals and visualization
The MATLAB environment, loading and saving data, basic matrix operations.
Basic plots, including 2D and 3D plots, image visualization.
Day 2 Basic Programming
Scripts, functions, loops, conditions, “good practice” in programming and debugging.
Day 3 Data Handling
Advanced data types (cell, struct, string etc.).
Logical Indexing, extraction of image data through matrix indexing and ROI analysis
The lessons will be a mixture of teaching and training. During the day, you will get data and script files for the training.
The audience for this course is primarily scientists within the area of health-research, who plan to employ MATLAB for analysis of data. Other scientists using MATLAB for the first time may also benefit from the course, even though data examples are on patient information, data time series and neuro-imaging data.
Course material: Lecture notes and other material are provided during the course.
Recommended knowledge for participation: No basic knowledge is required. Students must bring own laptop with MATLAB installed (version 2014 or later).
Involvement/Evaluation: The course alternates between short lectures and computational problems. Home assignments between the three course dates. Mandatory assignment (pass/fail, internal examination).
Head of course: Irene Klærke Mikkelsen
Instructors: Irene Klærke Mikkelsen, Rune Bæksager Nielsen, Peter Mondrup Rasmussen
Number of participants: 24
Dates and times: Monday, 30 November, Wednesday, 2 December and Friday, 4 December 2020 from 9:00 - 16:00
Place: Loftsalen (1266-316), The Victor Albeck Building, Vennelyst Blvd. 2-4, 8000 Aarhus
Course fee: DKK 2880
Participation in the course is without cost for:
- PhD students, Research Year students and Research Honours Programme students from Aarhus University
- PhD students enrolled at member universities of the Nordoc network
- PhD students from other institutions in the open market agreement for PhD courses
Application deadline: 2 November 2020