FYS401 Spectroscopy of Biological Materials and Data Analysis
Credits (ECTS):10
Course responsible:Achim Kohler
Campus / Online:Taught campus Ås
Teaching language:Engelsk
Limits of class size:5
Course frequency:Yearly
Nominal workload:40 hours colloquiums 210 hours own work
Teaching and exam period:This course starts in June block and has teaching in June block and Autumn parallel. This course has evaluation in Autumn parallel. The course is taught yearly.
About this course
The course is taught in June and in the following autumn semester. The first part of the course is a part of the BioSpec Summer School. Pre-courses need to be delivered before the start of the summer school. See https://www.nmbu.no/en/faculty/realtek/research/groups/biospectroscopy/summerschool for teaching period. In the autumn parallel, an individual study on infrared spectroscopy will be performed by all students. The study in the autumn semester will be supported by seminars.
For the BioSpec Summer School, lectures and tutorials will be evenly spread throughout the teaching period. The course covers the principles of spectroscopy and data science for analysis of data from biophotonics. It gives an introduction to biological data obtained with analytical methods, with a special focus on spectroscopy. The course contains training in data analysis through tutorials and working as an expert in a multidisciplinary team. Furthermore, special focus will be given on the development of personal presentation skills.
The course covers:
- Spectroscopic techniques
- Analytical methods in biology
- Principal Component Analysis
- Basic methods of pre-processing for spectroscopic data
- Advanced pre-processing methods such as Mie correction and fringes correction
- Multivariate methods for clustering
- Basic regression
- Machine learning methods for regression and classification
- Deep learning methods
- Data analysis of hyperspectral images
- Introduction to the machine learning software platform Orange/Quasar
Learning outcome
- Gain multidisciplinary knowledge in biology, spectroscopy and data analysis.
- Improve theoretical and practical knowledge in data analysis of high-dimensional biological data including hyperspectral imaging data.
- Acquire skills for working in an international and multidisciplinary team.
- Acquire presentation skills through presenting the results of the course project.
- Improve theoretical and practical knowledge within biophotonics and gain an overview of the analytical methods used in the field.
- Improve theoretical knowledge in the interaction between light and biological matter.
- Get insight into how the discipline has evolved and impacted society through invited lectures about applications of biophotoncis and data science.
- Be able to carry out interdisciplinary analyses with colleagues from other academic fields.
- Acquire skills to analyze and critically evaluate various sources of information and use them to structure and formulate scholarly arguments.
- Improve communication skills about academic issues, analyses and conclusions in the field, both with specialists and the general public.
- Get an overview over different spectroscopic techniques
- Get practical experience with infrared spectroscopy
- Acquire presentation skills through presenting the results of individual work
Learning activities
Teaching support
Prerequisites
Recommended prerequisites
Assessment method
Examiner scheme
Mandatory activity
Notes
Teaching hours
Preferential right
Reduction of credits
Admission requirements