Advanced Chemometrics and Machine Learning
Basic chemometric methods like PCA and PLS are useful tools in
data analysis but in many data analytical problems more advanced
machine learning 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, non-linear regression and multi-way methods.
Computer exercises on real data using commercial software are an integrated part of the course.
MSc Programme in Biotechnology
MSc Programme in Environmental Science
MSc Programme in Food Science and Technology
The course introduces advanced chemometric methods and their use
on different kinds of multivariate data of relevance for research
After completing the course the student should be able to:
- 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.
- 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.
- Discuss advantages and drawbacks of advanced 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 suitable for illustrating the taught methods. The results are presented in written reports which is orally defended at the end of the course.
See Absalon for specific course literature
Competences in the field of Exploratory Data Analysis /
Chemometrics (experience with PCA and PLS regression) is highly
recommended. The course coordinator should be contacted in case of
doubt about sufficient prerequisites.
Academic qualifications equivalent to a BSc degree is recommended.
The course is identical to the discontinued course LLEK10246U
Advanced Chemometrics. Therefore you cannot register for NFOK21000U
- Advanced Chemometrics and Machine Learning, if you have already
passed LLEK10246U Advanced Chemometrics.
If you are registered with examination attempts in LLEK10246U Advanced Chemometrics without having passed the course, you have to use your last examination attempts to pass the exam in NFOK21000U - Advanced Chemometrics and Machine Learning. You have a total of three examination attempts
- 7,5 ECTS
- Type of assessment
Oral examination, 20 min
- Type of assessment details
- 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.
Weight: Oral examination, 100%
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Project work
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 3
The number of seats may be reduced in the late registration period
- Study Board of Food, Human Nutrition and Sports
- Department of Food Science
- Faculty of Science
- Rasmus Bro (2-75654369727267316e7831676e)
- Morten Arendt Rasmussen (7-71737678697276446a737368326f7932686f)
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Courseinformation of students