| Responsible Department | Department of Food Science
80 % Department of Human Nutrition 20 % | ||||||||||||||
| Research School | FOOD Denmark | ||||||||||||||
| Course Dates | This course is offered two times per course. Dates for academic year 2011/12: First week september 2011 (already done) Second week 7 - 11 May 2012 Second week: 7 - 11 May 2012 | ||||||||||||||
| Course Abstract | The course entitled "Introductory MATLAB" is a 5-day focused at PhD (candidate) level with an interest in using the programming and analysis software MATLAB (MAtrix LABoratory) for general Data Analysis and Chemometric modeling. The course offers a platform for students and researchers to start handling and managing their scientific data. The course gives a first impression of the possibilities of MATLAB and its structure, data handling, plotting facilities, and the beginning of programming. | ||||||||||||||
| Course Registration | To sign up for the course, please send an e-mail to: - Jeanette Venla Hansen at jvh@life.ku.dk - José Manuel Amigo jmar@life.ku.dk | ||||||||||||||
| Deadline for Registration | Latest two weeks before the starting date (to be announced) | ||||||||||||||
| Credits | 3 (ECTS) | ||||||||||||||
| Level of Course | PhD course | ||||||||||||||
| Organisation of Teaching | 5 consecutive days course, 7 contact hours per day | ||||||||||||||
| Language of Instruction | English | ||||||||||||||
| Restrictions | Maximum 15 participants. | ||||||||||||||
| Course Content | |||||||||||||||
| 1- Introduction to MATLAB interface, 2- Array structures in MATLAB, 3- Basis of Chemometrics. PCA and PLS in MATLAB, 4- Scripts, functions and loops, 5- Plotting tools 6- Tricks and useful stuff, 7- Exam | |||||||||||||||
| Teaching and learning Methods | |||||||||||||||
| - Contact Teaching: the basis of the course teaching will be done by presentations. Lectures in power-point plus examples/exercises with the computer. The students will be able to follow all the exercises in their own computers. - Learning: Apart from the exercises presented at class, the students will be given several exercises that the must solve for the report. - Educational approaches: This course is addressed to PhD student or advanced Master students. The educational background of the students will be different. | |||||||||||||||
| Learning Outcome | |||||||||||||||
| Knowledge, skills, competences: - MATLAB interface: being able to "move around" in the most important utilities and windows in MATLAB - Programming: being able to understand the structure of functions and to create small functions independently; to use loops and conditions in MATLAB programming. - Data structure: being to identify and use different arrays structures of MATLAB and different ways of creating structures for data. - Data handling: learn different ways of importing and handling data, searching tools and data managing. - Chemometrics: being able to apply the basic Chemometric tools Principal Component Analysis and Partial Least Squares regression. - Graphical representation: being able to use basic and advanced static and dynamic plots. | |||||||||||||||
| Course Literature | |||||||||||||||
| Handouts and scientific papers provided during the course. | |||||||||||||||
| Course Material | |||||||||||||||
| Handouts and scientific papers provided during the course; scripts and source code provided during the course. | |||||||||||||||
| Course Coordinator | |||||||||||||||
| Jose Manuel Amigo Rubio, jmar@life.ku.dk, Department of Food Science/Quality and Technology, Phone: 353-32570 | |||||||||||||||
| Other Lecturers | |||||||||||||||
| Miss Gözde Gürdeniz, Department of Human Nutrition Dr. Frans v.d. Berg, Department of Food Science | |||||||||||||||
| Course Fee | |||||||||||||||
| - There is no course fee for PhD candidates from ANY universities. - There is a fee of 1000 DKK for any other participant. | |||||||||||||||
| Type of Evaluation | |||||||||||||||
| Written report based on 5 short examination assignments; work out by the participants individually. The reports have to be handed in maximally one week after the last lecture and are evaluated and credited with PASS/FAIL by the course lectures. | |||||||||||||||
| Work Load | |||||||||||||||
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