| Department of Food Science | |||||||||||||||||||
| Earliest Possible Year | MSc. 1 year to MSc. 2 year | ||||||||||||||||||
| Duration | One block | ||||||||||||||||||
| Credits | 7.5 (ECTS) | ||||||||||||||||||
| Course Level | MSc | ||||||||||||||||||
| Examination | Final Examination written examination and oral examination All aids allowed Description of Examination: The students will handle in a written report in due time before the oral examination. At the oral examination the students present the results from their projects for fellow students and course teachers. After this presentation all students and teachers participate in a discussion on the project. Weight: The written report: 70 % Oral examination: 30 % 13-point scale, internal examiner | ||||||||||||||||||
| Organisation of Teaching | Lectures (25%), exercises (25%), colloquia (5%), project work (45%) | ||||||||||||||||||
| Block Placement | Block 2 Week Structure: A | ||||||||||||||||||
| Teaching Language | English | ||||||||||||||||||
| Optional Prerequisites | Exploratory data analysis / Chemometrics | ||||||||||||||||||
| Restrictions | 50 | ||||||||||||||||||
| Areas of Competence the Course Will Address | |||||||||||||||||||
| Competences within applied science: The student will understand the advanced chemometric methods studied during the course. The student will be able to apply principles on similar problems. The student will understand the application of MATLAB for performing multivariate data analysis. The student will obtain knowledge of downloading toolbox'es from the internet and knowledge of how to evaluate the performance of these. | |||||||||||||||||||
| Course Objectives | |||||||||||||||||||
| The course will introduce the student to advanced chemometric methods with focus on process analytical technological (PAT) relevance. The software used throughout the course is MATLAB and it is a distinct purpose of the course to make MATLAB a data analytical tool for the students. | |||||||||||||||||||
| Course Contents | |||||||||||||||||||
| Basic chemometric methods like PCA and PLS are useful tools in data analysis but in many data analytical problems more advanced methods are necessary to solve the problems. The methods studied in this course will be selected from these main topics: Data preprocessing methods, linear and non-linear classification techniques, calibration transfer methods, non-linear regression, non-linear exploratory methods, bioinformatic methods and multi-way methods. Computer exercises on real data using MATLAB software and toolboxes from the internet are an integrated part of the course. The student will receive a thorough introduction to the MATLAB software at the course introduction. It is expected that the student have competences corresponding to the course Exploratory Data Analysis / Chemometrics. The methods taught in this course will be "translated" to MATLAB in order to establish platform for introducing the advanced methods. | |||||||||||||||||||
| Teaching And Learning Methods | |||||||||||||||||||
| The students will be introduced to the theory through lectures and seminars. The students will work in groups on a data analytical problem using the taught algorithms and MATLAB to analyse the problem. The students can bring their own data analytical problems to work on; this requires that the course teachers consider the data as suitable to illustrate the taught methods. The results are presented in a written report which is orally defended at a seminar at the end of the course. | |||||||||||||||||||
| Course Litterature | |||||||||||||||||||
| Scientific papers, book chapters and course notes. | |||||||||||||||||||
| Course Coordinator | |||||||||||||||||||
| Lars Nørgaard, lan@life.ku.dk, Department of Food Science, Phone: 35333212 Rasmus Bro, rb@life.ku.dk, Department of Food Science/Quality and Technology, Phone: 35333296 Frans W.J. van den Berg, fb@life.ku.dk, Department of Food Science/Quality and Technology, Phone: 35333545 Jürgen von Frese, jvf@kvl.dk, Department of Food Science/Quality and Technology, Phone: 35283254 | |||||||||||||||||||
| Study Board | |||||||||||||||||||
| Study Committee LSN | |||||||||||||||||||
| Course Scope | |||||||||||||||||||
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