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LLEK10246U  Advanced Chemometrics Volume 2014/2015

Course information

LanguageEnglish
Credit7,5 ECTS
LevelFull Degree Master
Duration1 block
Placement
Block 2
Schedule
A (Tues 8-12 + Thurs 8-17)
Course capacitymax. 25
Continuing and further education
Study boardStudy Board of Food, Human Nutrition and Sports
Contracting department
  • Department of Food Science
Course responsible
  • Rasmus Bro (2-7767456b74746933707a336970)
Saved on the 03-03-2015
Education
MSc Programme in Food Science and Technology
MSc Programme in Biology -Biotechnology
MSc Programme in Agriculture
Content

 

 

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, variable selection methods, clustering and classification techniques, calibration transfer methods, non-linear regression and multi-way methods.

Computer exercises on real data using commercial software are an integrated part of the course.

 

 

Learning Outcome

The course introduces advanced chemometric methods and their use on different kinds of multivariate data of relevance for research and development.

After completing the course the student should be able to:

Knowledge:
Summarize basic chemometric methods
Describe advanced chemometric methods for multivariate (clustering, classification and regression) data analysis
Describe advanced techniques for data pre-preprocessing
Describe advanced methods for variable selection

Skills:
Apply theory on real life data analytical cases
Apply commercial software for data analysis
Report in writing a full data analysis of a given problem including all aspects presented under Knowledge.

Competences:
Discuss advantages and drawbacks of advanced methods

Literature

See course web-site.

Scientific papers, book chapters and course notes.

Teaching and learning methods
The students will be introduced to the theory through lectures and seminars. The students will work on data analytical problems using the taught methods and software to analyse data. 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 written reports which is orally defended at the end of the course.
Academic qualifications
Competences corresponding to the course LLEF10174 Exploratory Data Analysis / Chemometrics (must have experience with PCA and PLS regression)
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Exam
Credit7,5 ECTS
Type of assessment
Oral examination, 20 min
The students will hand in a number of written reports in due time before the oral examination. At the oral examination, the student will be examined in the reports as well as the curriculum.
Exam registration requirementsAll reports must be approved before exam
AidAll aids allowed
Marking scale7-point grading scale
Censorship formNo external censorship
More than one internal examiner
Criteria for exam assesment

 

Weight: Oral examination in project reports and in the examination requirements 100%

 

Workload
CategoryHours
Exam1
Lectures69
Preparation70
Project work66
Total206
Saved on the 03-03-2015