NSCPHD1155 Introduction to MATLAB for Multivariate Data Analysis
Volume 2013/2014
Education
PhD
Content
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.
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
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
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.
- 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.
Literature
Handouts and scientific papers provided
during the course; scripts and source code provided during the
course.
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.
Workload
- Category
- Hours
- Exam
- 1
- Lectures
- 15
- Practical exercises
- 20
- Preparation
- 25
- Project work
- 15
- Total
- 76
Sign up
Contact Jeanette Venla Hansen
jvh@food.ku.dk or José Manuel
Amigo jmar@food.ku.dk
no later that 2 weeks before the starting date.
Exam
- Credit
- 3 ECTS
- Type of assessment
- Written assignmentWritten 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.
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Course information
- Language
- English
- Course code
- NSCPHD1155
- Credit
- 3 ECTS
- Level
- Ph.D.
- Duration
- 5 day course, 7 contact hours a day
2013: September, 2 - 6
2014: April, 7 - 11 (confirmed) and September, 1 - 5 (not confirmed) - Placement
- Block 1 And Block 4
The course runs twice a year
- Schedule
- 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.
- Course capacity
- Max. 15 participants
- Continuing and further education
- Price
- No fee for PhD students from the association Danish Universities. Any other participants 1000 DKK.
- Study board
- Natural Sciences PhD Committee
Contracting department
- Department of Food Science
Course responsibles
- Franciscus Winfried J van der Berg (fb@food.ku.dk)
Lecturers
Dr. José Manuel Amigo Rubio, Dr. Frans van den Berg and Dr. Evrim Acar
Saved on the
23-07-2013