Bi9680enc Artificial Intelligence in Biology, Chemistry, and Bioengineering - practice

Faculty of Science
Autumn 2020
Extent and Intensity
0/1/0. 1 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: k (colloquium).
Taught partially online.
Stanislav Mazurenko, PhD (seminar tutor)
Guaranteed by
prof. Mgr. Jiří Damborský, Dr.
Department of Experimental Biology - Biology Section - Faculty of Science
Contact Person: Stanislav Mazurenko, PhD
Supplier department: Department of Experimental Biology - Biology Section - Faculty of Science
Tue 12:00–13:50 prace doma
Prerequisites (in Czech)
Bi9680en AI in Bioengineering || NOW ( Bi9680en AI in Bioengineering )
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The main objective of this course is to provide students with hands-on experience in programming simple examples of machine learning-based predictors in Python. The practicals will follow the theory presented during the lectures of Bi9680en. We will cover the basics of programming, some useful libraries for data analysis and machine learning, and two simple examples of predictors for biologically-relevant data. No prior experience in programming is expected at the beginning of the course.
Learning outcomes
After completing the course, a student will be able to:
- operate the Spyder editor;
- understand the basics of the code flow;
- operate with basic types of variables, functions, if-conditions, and for-loops;
- implement the necessary steps of the machine learning workflow;
- train and validate simple machine learning predictors.
  • - Introduction to programming, types of variables, your first code;
  • - Booleans, if-conditions, for-loops, basic functions;
  • - Brief introduction to Numpy and Panda;
  • - Hierarchical clustering;
  • - Decision trees;
  • - Cross-validation.
Teaching methods
practice in the computer lab, homework
Assessment methods
There will be a simple final assignment - a modification of the examples studied during the practicals sessions
Language of instruction
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms autumn 2021.
  • Enrolment Statistics (Autumn 2020, recent)
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